Analysis of Nitric Oxide and Nitrogen Dioxide Variability at a Central Mediterranean WMO/GAW Station

Abstract

The World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) observation site of Lamezia Terme (code: LMT) in Calabria, Italy, has been measuring nitric oxide (NO) and nitrogen dioxide (NO₂) (together referred to as NO_x) for a decade; however, only a limited number of studies have evaluated their variability at the site, accounting for short measurement periods. In this work, nine continuous years (2015–2023) of measurements are analyzed to assess daily, weekly, seasonal, and multi-year tendencies, also accounting for local wind circulation, which is known to have a relevant impact on LMT’s measurements. For the first time, a multi-year evaluation of LMT data also considers the local wind lidar record to integrate conventional measurements with additional information on the transport of NO_x at low altitudes. The study also considers data on local tourism and vehicular traffic to assess correlations with LMT’s measurements, thus providing new insights on NO_x variability at the site. The analysis showed peaks in early morning NO_x concentrations attributable to rush hour traffic, while in the evening NO₂ peaks are present with minor NO counterparts. Weekly cycles have yielded the most statistically significant results of any other similar evaluation at the sites, with all combinations of parameters, seasons, and wind corridors indicating tangible differences between weekday (WD, Monday to Friday) and weekend (WE, Saturday and Sunday) concentrations. The analysis of multi-year variability has shown a slightly declining tendency; however, sporadic bursts in concentrations limit the statistical significance of downward trends.

1. Introduction

During Earth’s history, atmospheric composition has been subject to major changes reflecting geodynamical mechanisms and direct influence from the biosphere [1,2,3].

Oxygen and nitrogen are the most abundant elements in the atmosphere; despite their abundance, at low temperatures these elements do not tend to interact with each other, although exceptions can occur [4]. Natural phenomena such as lightning can release ≈100 TgN yr⁻¹ of LNO_x (lightning-induced nitrogen oxides) every year on a global scale [5,6,7,8,9,10,11,12,13,14,15].

NO_x are generally not classified as greenhouse gases (GHGs); however, they play a major role in the atmospheric chemistry of compounds that do have a direct impact on Earth’s climate [16]. NO_x has in fact, a notable impact on atmospheric CH₄: NO_x emissions can, in fact, increase atmospheric hydroxyl radical (OH), which is the main sink of CH₄ [17,18,19,20,21,22,23]. It has been estimated that NO_x emissions can reduce CH₄’s concentrations by ≈1000 ppb, according to several studies [24]. Reactions with OH affect the oxidation potential of Earth’s atmosphere, or AOC (Atmospheric Oxidation Capacity), thus playing a major role in the global budget of several compounds [25,26,27]. NO_x is also known to react with tropospheric O₃ (ozone) [28,29,30,31,32,33,34,35], leading to the introduction of a new methodology, the O₃/NO_x ratio [36,37], which can be used to differentiate local and remote sources of emission [38].

Biomass and fossil fuel burning and extensive fertilizer use in the agricultural sector are known to be the main sources of anthropogenic NO_x [39,40,41,42,43,44]. Due to cooking and similar activities, indoor concentrations can match or even exceed outdoor concentrations under specific conditions [45,46,47]. The vertical profile of NO_x in the troposphere also reflects the heterogeneous nature of its sources, with natural NO_x (e.g., lightning-induced) being present at multiple altitude thresholds, while that resulting from anthropogenic emissions can be concentrated over near-surface altitudes [48,49,50,51,52,53,54], thus posing a direct hazard for human health and the environment.

NO_x are also well known in the literature in terms of negative impacts on human health and the environment [55,56,57,58,59]. At typical conditions and concentrations, NO does not pose a tangible hazard to human health; however, increased concentrations can cause a number of ailments, affecting multiple organs of the human body [60,61,62,63,64,65]. High concentrations of NO₂ are also associated with a number of diseases, mostly affecting the respiratory system [66,67,68,69,70,71,72,73,74]. The effects of NO_x are partially mitigated by their short atmospheric lifetime, which ranges between a few hours and nearly one day, depending on several factors such as seasonality (specifically, its effects on NO_x sinks in the atmosphere), reactions with O₃ and other molecules, the presence of aerosols, and even NO_x concentration itself [75,76,77,78,79,80,81,82,83,84,85,86,87]. The short lifetime, combined with notable anthropogenic inputs, makes NO_x effective tracers of anthropic activities, and several methodologies/instruments are actively employed to measure their concentrations [88,89].

At the Lamezia Terme (code: LMT) World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) regional observation site in Calabria, Italy, continuous measurements of NO_x have been in place since 2015. However, evaluations of these measurements were limited to preliminary data from the site [90] and the analysis of trends observed during the first COVID-19 lockdown in the country [91]. Due to the primary anthropogenic nature of NO_x in the region, a more detailed understanding of its variability at the WMO site would allow us to better assess anthropogenic emissions and discriminate them from natural sources. This work evaluates nine years of continuous NO_x measurements (2015–2023) to provide unprecedented detail on its variability at the site. The paper is organized as follows: Section 2 describes the LMT station and its characteristics, as well as all employed methodologies; Section 3 shows the results of this work; and Section 4 and Section 5 discuss the results and conclude the work, respectively.

2. The Observation Site and Employed Methodologies

2.1. Characteristics of the LMT Regional Site in Calabria, Italy

Operated by the National Research Council of Italy—Institute of Atmospheric Sciences and Climate (CNR-ISAC), the LMT regional observation site is located in Calabria, Italy, in the municipality of Lamezia Terme (Lat: 38°52.605′ N; Lon: 16°13.946′ E; Elev: 6 m a.s.l.) (Figure 1A). LMT is part of the World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) network and has been performing continuous measurements of GHGs, aerosols, and meteorological parameters since 2015.

Specifically, the site is located 600 m from the Tyrrhenian coast of Calabria, in the westernmost area of the Catanzaro Isthmus, which is the narrowest point in the entire Italian peninsula, as the distance between the western and eastern (Ionian) coasts is ≈32 km. The isthmus is bounded by several mountain ranges: the Sila Massif and Coastal Chain in the north and the Serre Massif in the south (Figure 1B). Its present-day configuration is the result of multiple geologic processes: in the early Quaternary, the isthmus was a tidal strait effectively connecting the Tyrrhenian and Ionian seas, as evidenced by sedimentological outcrops of 2D and 3D dunes, which highlight the evolution of the strait over time [92,93,94,95,96]. Various cycles of regression and transgression, linked to the Calabrian tectonic uplift [97,98,99,100,101], combined with major sea level oscillations, such as those caused by alternate glacial and interglacial periods [98,99,100,102,103], have ultimately resulted in sea currents being cut off between the two seas and, thus, leading to the present-day configuration with only ≈32 km separating the Tyrrhenian and Ionian coasts of the region.

The closure of the strait is the last step of a series of large-scale processes affecting the CPA (Calabria-Peloritani Arc), which also includes northeastern Sicily [104,105,106,107]. The CPA was once part of present-day southern France but became subject to intense tectonics that rifted it apart following the opening of the Alpine Tethys domain; this resulted in a continental drift in the southeastern direction, which ultimately caused the CPA to collide with the rest of the Italian peninsula and the Sicilian Maghrebides [108,109]. The process is still in place, as evidenced by seismic activity and fault lines compatible with an active southeastern drift [110,111,112]; the Tyrrhenian Sea opening, which is believed to have occurred at rates among the fastest ever documented on Earth, is further evidence of this drift [113,114].

In addition to drifting and substantial changes in the CPA’s location in the context of the developing Mediterranean Basin, the CPA itself has been widely reshaped by fault systems [115,116,117,118]. Locally, these mechanisms result in the Catanzaro isthmus being bounded by three distinct mountain ranges via active fault systems [119,120,121], including a major fault system between Lamezia Terme and Catanzaro, oriented on an east–west axis, which bounds the northern part of the isthmus [122,123], while the southern part is bounded by the Curinga-Girifalco line, which shows a W-NW/E-SE orientation [122,124,125]. The active nature of the tectonic features of the area leads to periodic seismic activity, which can reach very notable peaks: according to a database of historical records on all major earthquakes that occurred in Italy from the year 1000 AD onward, three out of ten earthquakes with an estimated magnitude of Mw 6.95 or greater have occurred in a ≈20 km radius from LMT’s current location, with major social, economic, and even geomorphological consequences [126,127].

The geomorphological framework of the area, shaped by tectonics, results in a peculiar near-surface wind circulation, with a well-defined NE/W axis measured by LMT over the course of several years [128,129,130]. While near-surface circulation is strongly affected by daily cycles of alternating westerly and northeastern winds at LMT, at higher altitudes, when the 850 hPa level is considered, the preferential wind direction is northwestern, in accordance with large-scale forcing in the area [128]. Breeze regimes and their seasonal patterns are a key factor in the regulation of near-surface wind circulation at LMT [128]. Diurnal circulation between November and February is regulated by large-scale forcing; between March and October, diurnal breezes result from a combination of large-scale and local flows; nighttime flows have been evaluated and found to be related to nocturnal breeze regimes [129].

Local wind circulation has a notable impact on air traffic: the Lamezia Terme International Airport (IATA: SUF; ICAO: LICA), located 3 km north from the WMO/GAW station and built between 1965 and 1976, has a runway orientation of 100/280° N (RWY 10/28), and the direction of inbound and outbound traffic reflects alternating wind corridors.

Figure 1. (A): Map of the central Mediterranean area with a focus on LMT’s location in the region of Calabria, Italy. (B): Regional-scale Digital Elevation Model (DEM) [131,132,133] showing the main mountain ranges of the Calabria-Peloritani Arc and the Catanzaro Isthmus, where LMT is located. (C): Local map of the western Catanzaro Isthmus, highlighting LMT’s location, the main sources of anthropogenic emissions in the area, and urban/topographic features. Farms are located over a wide area. The “Highways” label refers to a point where both the A2 Mediterranean Highway and the SS18 state highway intersect the northeastern wind corridor measured at LMT. The SS280 State Highway of the Two Seas connects the A2 Lamezia Terme junction with the eastern coast of the region, where the capital Catanzaro is located.

Figure 1. (A): Map of the central Mediterranean area with a focus on LMT’s location in the region of Calabria, Italy. (B): Regional-scale Digital Elevation Model (DEM) [131,132,133] showing the main mountain ranges of the Calabria-Peloritani Arc and the Catanzaro Isthmus, where LMT is located. (C): Local map of the western Catanzaro Isthmus, highlighting LMT’s location, the main sources of anthropogenic emissions in the area, and urban/topographic features. Farms are located over a wide area. The “Highways” label refers to a point where both the A2 Mediterranean Highway and the SS18 state highway intersect the northeastern wind corridor measured at LMT. The SS280 State Highway of the Two Seas connects the A2 Lamezia Terme junction with the eastern coast of the region, where the capital Catanzaro is located.

Preliminary data on reactive gases and methane (CH₄) at the site provided the first evidence of wind circulation’s impact on the concentration of gases at LMT [90]. These early evaluations also indicated the presence of NO_x peaks compatible with early morning rush hour traffic. Over time, the analysis of cyclic and multi-year patterns of a number of parameters has allowed us to better understand local variability and the influence of wind circulation: CH₄ has northeastern-continental peaks primarily linked to low wind speeds and low concentrations linked to high speed (HBP or “Hyperbola Branch Pattern”) [134]; ozone (O₃) is characterized by an opposite behavior, with westerly peaks during warm seasons that result from photochemical activity, higher temperatures, and exposure to solar radiation [135,136]; sulfur dioxide (SO₂) showed westerly peaks that have been attributed to maritime traffic and volcanic activity in the nearby Aeolian Arc [137]. It was also demonstrated that, under exceptional conditions, clean air masses from the northeastern sector of LMT can be channeled through the Marcellinara Gap, yielding minimal influence from anthropogenic emissions in the region and representing conditions representative of the Ionian Sea [38]. The NO_x therefore constitutes the fourth parameter to be subjected to a detailed, multi-year, and cyclic analysis at the site, as previous studies were limited to preliminary data [90] and specific time spans (i.e., the first COVID-19 lockdown) [91]. The study on the first COVID lockdown exploited a condition of exceptionally low anthropogenic emissions to demonstrate that the early morning peaks of NO_x observed before were attributable to rush hour traffic, as these emissions were minimal during the lockdown itself due to the strict regulations introduced by the Italian government at the time [138,139].

2.2. Instruments, Data, and Methodologies

NO_x measurements at the LMT observation site have been performed by a Thermo Scientific 42i-TL (Trace Level) (Franklin, MA, USA) analyzer [140]. The instrument operates by exploiting the reactions between O₃ and NO, which result in a luminescence whose intensity is linearly proportional to measured NO concentrations, and generates NO₂ [141]. Due to the abundance of NO₂ in ambient air, it must first be transformed into NO to allow the instrument to measure both parameters adequately; the instrument is equipped with a heated molybdenum converter (at a temperature of ≈325 °C). As presented by Steinbacher et al. (2007) [142], a drawback of using molybdenum converters is that other oxidized nitrogen compounds such as peroxyacetyl nitrates (PANs) and nitric acid (HNO₃) are also partly converted to NO. Several studies quantified the overestimation of NO₂ adopting this technique, which was in the order of 15–20% for a suburban site in South Korea [143], of 17–30% for a rural site and of 24–57% for a high-altitude site in Switzerland [142], and of ~30% for a peatland monitoring site in Scotland [144].

The air intake for gas measurements is composed of a Teflon tube (length: 1300 mm) with a manifold of 50 mm inner diameter. An aluminum hood is used to prevent rain entrance in the sampling line. Air is sampled at 3.7 m from the ground. The internal temperature is continuously monitored: to prevent water condensation, the tubing is heated up to 27 °C. Flow is maintained constant, minimizing the residence time of sampling inside the air intake (less than 5 s). Calibration procedures have been performed on a monthly or weekly basis. The calibration setup included a zero air generator, the Thermo Scientific 1160 (Franklin, MA, USA) and a gas dilution/gas-phase-titration (GPT) system, the Thermo Scientific 146i (Franklin, MA, USA). NO span and determination of converter efficiency by GPT were carried out by using several certified 5 ppm NO standards (in molecular nitrogen, N₂) provided by commercial laboratories (Praxair, Rivoira, and Messer Italia). Calibration procedures were performed as per the ACTRIS research infrastructure guidelines [145,146]. The instrument has a flow rate of 0.5 to 1 L per minute, an operating temperature between 15 and 35 °C, an operating range of 0–20 ppm, and a lower detectable limit of 0.40 ppb. Additional information on calibrations and instrumental setup is available in previous research on LMT NO_x measurements [90,91].

Wind speed and direction at the site have been measured by a weather station, model Vaisala WXT520 (Vantaa, Finland). The instrument measures wind variability via the implementation of a horizontal plane with ultrasonic transducers placed on top; changes in the travel time of ultrasound pulses between transducers are exploited to calculate changes in wind direction and speed. Additional information on WXT520 specifics and measurements at LMT is available in a previous study [147].

This study introduces, for the first time at LMT, vertical wind profiles to integrate WXT520 measurements in the multi-year assessment of a gas. These measurements were performed by a ZephIR 300 wind lidar (ZX Lidars, Malvern, UK), which operates as a continuous-wave focusing lidar [148]. Wind speeds and directions are measured by the instrument at several altitude thresholds by assessing the Doppler shift in the infrared laser, which is sensitive to particulate scattering in the lowermost layers of the atmosphere [149]. For this study, the 20 m AGL threshold was selected to integrate WXT520 measurements. Additional details and information on ZephIR 300 data gathering at LMT are available in a previous study [130].

Table 1. Coverage rates of NO_x (Thermo 42i), near-surface meteorological (Vaisala WXT520), and wind profile (ZephIR 300) measurements during the observation period. The NMTO dataset refers to valid NO_x and near-surface mast data, while the NLID dataset refers to valid NO_x and lidar wind profiles. ZephIR data for the year 2020 are not available due to maintenance and calibration procedures. Two leap years with 24 additional hours are present: 2016 and 2020.

Year	Hours	Thermo 42i	Vaisala WXT520	ZephIR 300	NMTO	NLID
2015	8760	92.73%	95.90%	66.32%	91.01%	61.96%
2016	8784	95.91%	96.34%	92.36%	93.23%	89.92%
2017	8760	96.39%	93.80%	97.67%	91.75%	95.95%
2018	8760	98.11%	77.05%	91.89%	75.67%	91.01%
2019	8760	96.78%	98.59%	29.48%	96.75%	28.07%
2020	8784	94.23%	99.98%	-	94.22%	-
2021	8760	87.14%	99.74%	40.70%	87.13%	38.50%
2022	8760	69%	90.11%	88.89%	67.59%	68.97%
2023	8760	81.86%	96.3%	96.43%	80.43%	79.08%
	78,888 1	90.24% 2	94.20% 2	67.08% 2	86.42% 2	61.49% 2

¹ Sum of total elapsed hours. ² Average rate for 2015–2023.

shows, for the entire study period (2015–2023), the coverage rates of each instrument used in this evaluation, and the rate resulting from merged datasets.

All data have been processed in R 4.5.1 to generate plots using the dplyr [150], ggplot [151], and tidyverse [152] packages/libraries. The normality of NO_x data at LMT was tested using the Shapiro–Wilk [153] and Jarque–Bera [154] methods, with consequent analyses based on the Kruskal–Wallis [155] methodology aimed at assessing the statistical significance of differences between specific categories. Multi-year tendencies have been calculated using the Mann–Kendall [156,157], Hirsch-Slack (SMK, Seasonal Mann–Kendall) [158], and Pettitt’s [159] methods via the zyp [160] and trend [161] packages in R. Pollution roses have been generated using the openair package [162]. The statistical significance of differences in pairs has been evaluated using the pairwise Wilcoxon test (also known as the Mann–Whitney U test [163,164]), with Bonferroni correction [165,166].

Seasons have been categorized based on the conventional JFD (winter: January, February, December), MAM (spring: March, April, May), JJA (summer: June, July, August), and SON (fall: September, October, November) trimesters. The hourly dataset used in this study is set at Coordinated Universal Time (UTC).

3. Results

3.1. Variability and General Trends During the Observed Period

The general variability observed at the site between 2015 and 2023 is shown in Figure 2. The data unequivocally demonstrate that NO₂ constitutes the majority of NO_x measured at the site.

3.2. Analysis and Evaluation of NO_x Daily Cycles

As described in Section 2.1, the LMT site is subject to a very strong daily cycle resulting from the influences of local near-surface wind circulation and geomorphology. The peaks observed during regular daily cycles are also dependent on the nature of parameters, with some of them showing nighttime peaks [134], while others are characterized by diurnal peaks [135]. A generic daily cycle of NO_x is shown in Figure 3.

A previous study, based on LMT’s preliminary data, reported the susceptibility of the daily cycle to changes between CEST (Central European Summer Time), set at UTC + 02:00, and CET (Central European Time), which is set at UTC + 01:00. These changes occur on the last Sunday of March and October, thus affecting the spring and fall seasons. In Figure 4, seasonal daily cycles are shown, indicating shifts in early morning rush hours attributable to alternating CEST and CET times.

3.3. Variability with Near-Surface Wind Speed/Direction

As reported in Section 2.1, the peculiar location of LMT also results in specific dependences of pollutant concentrations with wind speed, in addition to wind direction. Data ellipses showing a bivariate t-distribution under a 95% confidence interval [167] have been used in Figure 5 to group data falling into the same category, thus allowing us to highlight the differences between seasons and wind sectors at the site.

Seasonal pollution roses have also been computed to assess the variability of NO_x concentrations based on wind directions. Roses are shown in Figure 6.

3.4. Variability with 20 m AGL Wind Speed/Direction

This study introduces the 20 m above ground level wind data to provide additional information on low-altitude air mass transport of NO_x in the area. Previous research on LMT data variability highlighted the influence of wind inversion patterns and air mass transport at higher altitudes as driving factors of a number of peaks in measured pollutants [168]. Figure 7 shows data ellipses based on wind sector categorization of ZephIR 300 data.

Table 2. Comparison of wind corridors attributed to valid WXT520 and ZephIR 300 (20 m) measurements. MTO/LID refers to the percentage of WXT520 measurements, per sector, which falls under the corresponding category of wind lidar measurements. LID/MTO provides the opposite figure.

Sector	MTO/LID	LID/MTO
Northeast	78.44%	70.63%
West	76.01%	74.46%
Other	52.76%	61.25%

reports the agreement between wind sectors attributed by each instrument.

The agreement between wind sector categorization assigned by joint weather station and wind lidar measurements is shown in Figure 8.

The direct comparison of wind directions measured by WXT520 and ZephIR 300 instruments shows a non-negligible number of hourly measurements with conflicting wind directions. Using the pairwise Mann–Whitney U test [163,164] with Bonferroni correction [165,166], the statistical significance of the differences between pairs, in terms of hourly NO_x mole fractions, has been evaluated. For each wind corridor observed from LMT’s mast, combinations of pairs of corresponding ZephIR 300 measurements have been compared, and the results are shown in

Table 3. Results of seasonal Mann–Whitney U (Wilcoxon) pairwise tests of significance, with Bonferroni correction. The WXT520 column identifies wind sectors as observed by LMT’s mast. For each WXT520 wind sector, the p-value showing the statistical significance between NO_x averages of pairs of 20 m AGL sectors (ZephIR 300) is reported. NE = Northeast (0–90° N); W = West (240–300° N); Ot = Other (all other wind directions).

Season	WXT520	ZephIR 300
		NE-W	W-Ot	NE-Ot
Winter	Northeast	1	<0.05	<0.05
	West	<0.05	<0.05	<0.05
	Other	<0.05	<0.05	<0.05
Spring	Northeast	1	<0.05	<0.05
	West	<0.05	<0.05	<0.05
	Other	<0.05	<0.05	<0.05
Summer	Northeast	1	<0.05	<0.05
	West	<0.05	<0.05	<0.05
	Other	<0.05	<0.05	<0.05
Fall	Northeast	1	<0.05	<0.05
	West	<0.05	<0.05	<0.05
	Other	<0.05	<0.05	<0.05

. The Bonferroni correction has been applied to adjust p-values based on the number of evaluated pairs.

Due to LMT’s strong daily cycle, caused by local wind circulation and geomorphology, the agreement between wind sectors reported at the two select altitude thresholds has also been evaluated based on their hourly distribution. Figure 9 shows, for each wind sector based on WXT520 measurements, the corresponding frequency of hourly data from ZephIR 300 measurements at 20 m AGL falling in each category.

3.5. Weekly Analysis

Over time, several weekly analyses have been employed at the LMT observation site to determine the influence of anthropogenic influences [169], which—unlike natural sources—are characterized by weekly patterns. Figure 10 shows the distribution of NO_x data at LMT under a WD-WE categorization (weekday, MON-FRI; weekend, SAT-SUN) [170].

WD averages are consistently greater than their WE counterparts under all wind corridors; however, the significance of this difference requires a statistical evaluation. In order to apply the Kruskal–Wallis method [155], the normality of data distribution was evaluated using the Shapiro–Wilk [153] and Jarque–Bera [154] tests, performed independently for NO, NO₂, and NO_x mole fractions. All tests yielded statistically very significant results (p-value < 2.2 × 10⁻¹⁶), indicating that data are not normally distributed and a Kruskal–Wallis test can be used, with the results shown in

Table 4. Results of Kruskal–Wallis tests on the statistical significance of differences between WD and WE concentrations, divided by wind sector and instrument.

Parameter	Sector (WXT520)			Sector (ZephIR)
	All	Northeast	West	All	Northeast	West
NO	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
NO2	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
NOx	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05

. The test indicates the presence, under all circumstances, of a statistically significant weekly cycle between WD and WE.

Due to the influence of possible seasonal patterns on weekly cycles, the Kruskal–Wallis method was also applied on seasonality, and the results are shown in

Table 5. Results of the Kruskal–Wallis tests on the statistical significance of differences between WD and WE concentrations, divided by wind sector and instrument, and further categorized on a seasonal basis.

Season	Parameter	Sector (WXT520)			Sector (ZephIR)
		All	Northeast	West	All	Northeast	West
Winter	NO	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NO2	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NOx	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
Spring	NO	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NO2	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NOx	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
Summer	NO	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NO2	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NOx	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
Fall	NO	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NO2	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05
	NOx	<0.05	<0.05	<0.05	<0.05	<0.05	<0.05

.

3.6. Annual Cycles and Multi-Year Tendencies

The last evaluation focuses on the standard annual cycle, shown in Figure 11 and categorized by wind sector.

Multi-year tendencies of all parameters have been evaluated via the Mann–Kendall [156,157] methodology, applied to monthly averages of NO, NO₂, and NO_x. The averaged monthly values measured during the entire study period (2015–2023) are shown in Figure 12, while

Table 6. Results (tau) of the Mann–Kendall (MK) tests and their respective p-values, based on monthly aggregated data at LMT from 2015 to 2023 and categorized by wind sectors.

Parameter	Wind Sectors
	All		Northeast		West
	MK	p	MK	p	MK	p
NO	−0.126	0.05 (7)	−0.102	0.12	−0.202	<0.05
NO2	−0.12	0.06	−0.148	<0.05	−0.117	0.07
NOx	−0.131	<0.05	−0.161	<0.05	−0.143	<0.05

reports the results of trend analyses. In

Table 7. Results (z) of the seasonal Mann–Kendall (SMK, or Hirsch-Slack) test and their respective p-values, based on monthly aggregated data at LMT from 2015 to 2023 and categorized by wind sectors.

Parameter	Wind Sectors
	All		Northeast		West
	SMK	p	SMK	p	SMK	p
NO	−2.859	0.004	−1.534	0.124	−3.160	0.001
NO2	−2.197	0.028	−2.618	0.008	−1.294	0.195
NOx	−2.558	0.010	−2.618	0.008	−1.835	0.066

, the results yielded by SMK (Seasonal Mann–Kendall, or Hirsch-Slack) [158] tests are shown.

Pettitt’s test [159] for change-point detection has also been applied to LMT’s record and tested for all evaluated parameters (NO, NO₂, and NO_x) and wind sectors (total, northeastern, and western). The results indicate a change point in February 2020 for the total and northeastern corridors and March 2020 for the western corridor. These shifts in the record coincide with the first COVID-19 lockdown in the country [91].

4. Discussion

At the WMO/GAW observation site of Lamezia Terme (LMT) in Calabria, Italy, multi-year analyses of GHGs and aerosols can provide detailed information on the balance between anthropogenic and natural sources in a region characterized by a peculiar location within the Mediterranean Basin (Figure 1) [134,135,137]. Using several years of data, it is possible to assess local variability with higher detail compared to research based on limited time spans and preliminary results [90]. A multi-year study relying on data gathered by several instruments is susceptible to the presence of gaps in the record, especially when two or more instruments need to be integrated to provide joint chemical and physical (e.g., wind) parameters. During the study period (2015–2023), the reported coverage rates of NO_x and wind data are very high and, thus, allowing us to differentiate measurements by wind sector (Table 1). This study also introduces wind lidar data in a multi-year evaluation at LMT, with the scope of assessing the transport of pollutants at higher altitude thresholds and compensating for the lack of regular weather station measurements in case of maintenance issues (e.g., in the year 2018). Very low concentrations of NO_x dominate the dataset (Figure 2), which is well representative of LMT’s nature as a coastal and hybrid urban/rural site, with multiple sources of emission coexisting. This is in accordance with the findings of previous studies, which highlighted the presence of sporadic peaks in pollutants linked to fossil fuel burning and similar anthropogenic sources [38,91,134,165], with non-negligible inputs from livestock farming and agricultural activities [38,90].

At LMT, the analysis of daily cycles is a standard methodology for the assessment of gases and aerosols [38,90,91,134,135,137]. The site is heavily influenced by alternating wind corridors, each with specific characteristics and degrees of anthropogenic influences, and depending on the evaluated atmospheric parameter, diurnal or nocturnal hours may show the highest peaks. During the observation period, the daily cycle of NO_x (Figure 3) shows early morning peaks that have been attributed by previous research to rush hour traffic [90]. The same NO peaks observed in the early morning, however, lack a prominent late evening counterpart, which is attributable to NO’s reaction with tropospheric O₃. Additionally, the early morning peaks are spread over multiple hours: in previous research on LMT’s preliminary data, this was attributed to changes between CEST and CET, which caused a shift in the peaks observed using UTC [90]. The finding was used to indicate the dominant anthropogenic nature of the peak. Further evidence in this direction was found in the analysis of trends in pollutants during the first COVID-19 lockdown in Italy, during which very strict regulations [138,139] severely limited anthropic activities: the study found that the rush hour peak was considerably lower during the first lockdown, further demonstrating its anthropogenic nature [91].

Figures and data provided by ANAS, the national agency managing highways and state highways, have allowed—for the first time at LMT—to compare local measurements with local vehicular traffic. Considering this work’s study period (2015–2023), ANAS’ database includes 54 out of 108 months (50%) for the State Highway SS18 (identifier 3417) and 85 months (78.7%) of data for the Mediterranean Highway A2 (ID 1895). The SS280 State Highway of the Two Seas (ID 3386), connecting the Tyrrhenian and Ionian coasts of the region, has no available data for the study period. The highways are both toll-free, and ANAS performs regular counts via the Sistema Automatico di Rilevamento Statistico del Traffico (Automated System for Statistical Traffic Detection). Daily cycles of vehicular traffic at both the A2 and SS18 are reported in Figure 13.

Daily vehicular traffic flows are consistent with the findings of this work concerning daily NO_x variability (Figure 3 and Figure 4) and provide tangible evidence demonstrating the hypotheses reported in previous works [90,91]. During the first COVID-19 lockdown, the daily cycle of NO_x was largely affected by the reduction in vehicular traffic, especially during rush hours: data provided for the A2 Highway in Figure 13A are consistent with previous research assessing the effects of the lockdown on local greenhouse gas and aerosol variability [91].

The same shifts are observed in the multi-year assessment of this work, and in greater detail considering that previous research, combined, did not consider a full calendar year [90,91] while this work evaluates nine years of continuous measurements. The seasonal daily cycles (Figure 4) indicate changes in the early morning rush hour traffic peak, which are compatible with alternating CEST and CET. These plots also allow us to assess the behavior of NO_x between the late afternoon and the evening: during winter and fall, NO₂ concentrations show an increase from 15:00 UTC onward, while the same occurs at 18:00 UTC during spring and summer. Warm seasons also show clear minimum during diurnal hours, consistent with photolysis as evidenced by previous research [90]. This study also highlights a behavior that was not reported by previous research on NO_x variability in the late evening, i.e., from 19:00 UTC onward: during winter and fall, and to some degree in spring, observed NO_x concentrations reach a peak, followed by a clear declining pattern; during the summer season, despite the known increase of NO_x sinks such as O₃ [135], concentrations remain high and do not experience a considerable decline up until 07:00 UTC. The pattern could be representative of increased emissions attributable to tourism, as Calabria is a popular destination within the country, and, during the summer, the amount of anthropogenic emissions linked to transportation can increase considerably. A related phenomenon, which is recognized as “non trackable” by local institutions evaluating touristic flows during the season, is the temporary increase in population caused by the return of expats and other categories of individuals who study/work in other regions of the country or abroad. It is worth noting that, during the summer, O₃ concentrations during diurnal hours reach notable peaks [135], which can lead to reductions in NO_x mole fractions due to atmospheric chemical processes [38,90].

The influence of agriculture on NO_x concentrations at LMT can also be a driving factor. The use of fertilizers can result in NO_x emissions [166,171,172,173], and farms are widely spread in the area where LMT is located. Previous research found substantial evidence of peaks in local emissions of CH₄ [38,90], attributed to livestock farming and similar sources. Future research would need to isolate air masses representative of fresh emissions, up to the urban-level scale [174], and discriminate agricultural contribution from other sources. As reported in the work by Buono et al. [175], the LMT site is introducing stable carbon isotope analyses; in particular, the evaluation of CH₄ (δ¹³C-CH₄) is set to provide additional insights into the contribution of livestock and agriculture to the local balance of greenhouse gases [176,177].

The daily cycles of NO_x at the site are more consistent with rush hour traffic; however, high concentrations measured from the western sector could be attributed to agricultural emissions and wind inversion patterns, which cause diffused emissions to be measured at LMT from the western sector. The implementation of instruments assessing N₂O (nitrous oxide) [178,179] and NH₃ (ammonia) at the site would provide further evidence on the impact of agriculture on nitrogen oxide variability at LMT. NH₃’s short atmospheric lifetime, in particular, could be exploited to assess the influence of fresh local emissions from the agricultural sector.

Previous works also raised the possibility of direct influences from other means of transportation, such as maritime shipping and air traffic [90,134,137]. Influences of maritime shipping on LMT’s sulfur dioxide (SO₂) measurements have been reported in the western sector; however, a prominent natural source, i.e., volcanoes, can also contribute to these emissions, thus affecting the possibility of differentiating maritime shipping from other natural sources [137]. Aircraft movements at the nearby Lamezia Terme International Airport, located 3 km north of LMT, may also influence local measurements of NO_x, and the possibility of these emissions on LMT measurements was reported in previous research [90,134]. These contributions are also difficult to assess in detail, as aircraft take off and land with headwind alternating between the two runways of SUF/LICA airport, thus indicating that emissions resulting from takeoff and landing procedures are largely incompatible with LMT’s wind sector. In this case, a campaign of air quality studies at the airport, in conjunction with LMT’s measurements, would allow us to better assess these influences and provide a more accurate understanding of local NO_x variability.

Previous studies on the behavior of other gases have shown that assessments of concentrations based on wind speed variability can provide substantial evidence in source apportionment efforts. The HBP (Hyperbola Branch Pattern), i.e., with low speeds linked to high concentrations and vice versa, was first documented at the site of CH₄, specifically with respect to the northeastern-continental sector [134]. Consequently, the implementation of air mass aging and proximity indicators allowed us to detect similar patterns in CO and CO₂, linking higher concentrations and low wind speeds to local sources of emission; CH₄ peaks at low wind speeds were also associated with local sources [38]. Research performed on BC (black carbon) and SO₂ (sulfur dioxide) showed that the former is also characterized by a prominent HBP, while the latter showed a number of anomalies in its behavior, including the absence of HBP [180]. SO₂’s anomaly was attributed to a peculiar balance between local and remote sources, with natural outputs such as the Aeolian Arc (Tyrrhenian) and Mount Etna (Sicily) [137]. Using data ellipses (Figure 5) to group measurements based on wind sector, the same HBP seen in CO, CO₂, CH₄, and BC is also reported for NO_x across all seasons; the western-seaside corridor is known to be linked to the highest wind speeds observed at LMT, due to combinations of local and large scale flows, the absence of obstacles in the western direction, and the broader balances of wind circulation in the area [128,129,130]. When wind lidar measurements at the 20 m AGL threshold are selected (Figure 7), the same pattern emerges, although wind speeds are shifted towards higher values due to the characteristics of vertical wind profiles (Figure 8), which can also show in shifts in wind direction [130], as evidenced by the comparison between the directions measured at both altitudes (Table 2). NO_x’s reported behavior at LMT, SO₂’s anomaly reported in a previous study, and the implementation of air mass aging indicators to CO, CO₂, CH₄, and BC indicate that the HBP is typically linked to gases and aerosols characterized by local anthropogenic sources of emissions, which can lead to peaks in the case of buildup and low wind speeds.

Due to the relevant number of measurements falling under different wind sectors at the two select altitude thresholds, the disagreement was evaluated to verify the impact of vertical wind profiles on near-surface concentrations of NO_x [128,129,130]. For this reason, the Wilcoxon test (also known as the Mann–Whitney U test) [163,164] was used to verify the significance in differences between pairs of wind sectors. The Bonferroni correction [165,166] was also implemented to adjust p-values based on the number of pairs, as an increase in the number of evaluated pairs may increase the number of false positives. The results, reported in Table 3, clearly indicate that the northeastern sector (as measured by the WT520 mast) does not result in substantial differences between the northeastern-western pair as measured by the wind lidar, thus providing new evidence towards increased pollutant concentrations that occur at LMT during wind inversion patterns [168]. These disagreements were further tested to verify the impact on LMT’s daily cycle (Figure 9). The frequency of agreement between the wind sectors measured by both instruments peaks during diurnal hours from the western sector (Figure 9B), which is consistent with well-established breeze regimes regulating air mass transport over multiple altitude thresholds [128,129,130]. Conversely, the frequency of agreement is lower during diurnal hours when the local mast detects northeastern winds (Figure 9A): this is also consistent with changes in wind direction over the vertical profile, described in previous research [130]. These results indicate that westerly winds, which are more prominent at higher altitude thresholds, can contribute to the northeastward transport of air masses enriched in NO_x, some of which could be originating from Calabria itself and subject to near-surface air mass transport towards the west. The findings could be used to improve methodologies for the measurement of atmospheric background concentrations of several parameters, which presently rely on WXT520 mast wind directions alone to restrict LMT measurements to the western sector [147].

Additional information concerning the variability of NO_x peaks depending on wind direction is evaluated using seasonal pollution roses (Figure 6), which clearly show the NE/W orientation of the main wind corridors at the site and the highest peaks in concentration from the northeastern sector, observed in winter and fall. The summer season shows a higher frequency of measurements in the western sector; spring shows an intermediate behavior. The observed behavior is compatible with wind inversion patterns influencing the daily cycle at the site [168] and specific conditions such as synoptic regimes [181], which can cause air masses enriched in pollutants to return towards LMT from the Tyrrhenian Sea, thus resulting in higher concentrations observed from the western sector.

At LMT, weekly cycles have been frequently assessed to verify the presence of anthropic influences via a number of methodologies [38,134,135,136,169]. The extent of these influences changes substantially depending on the nature of each parameter and the presence of seasonal patterns. The same parameter may have a significant weekly cycle during cold seasons due to fuel burning and change drastically during warm seasons due to a shift in emission sources (e.g., wildfires). Wind sectors can also influence these cycles; hence, the requirement to adequately differentiate measurements based on wind sectors: average concentrations vary depending on the selected wind sector; however, differences between weekday (WD, MON-FRI) and weekend (WE, SAT-SUN) concentrations are reported (Figure 10). Based on the statistical methods used in previous studies, i.e., the Kruskal–Wallis method [155], these differences have been statistically evaluated to verify their significance, and the results—which account, for the first time, for dual WXT520 and ZephIR wind sectors—clearly indicate the presence of significant weekly cycles (Table 4). Further analysis, based on seasonality, shows extremely high levels of significance for all combinations of instruments, seasons, and wind sectors (Table 5), thus providing the most funded evidence ever observed at LMT on the presence of a weekly cycle and, consequently, a clear anthropogenic influence over emissions.

The ANAS database provides insights on weekly cycles, as the agency records vehicular traffic flows with the scope of determining changes over the course of the standard week. The results, categorized on a seasonal basis and showing data concerning the first COVID-19 lockdown in 2020 (available for the A2 Highway only), are shown in Figure 14.

When weekly and seasonal patterns are considered, data show a peculiar pattern: during WE, traffic is considerably lower under all circumstances, with the exception of summertime A2 traffic, which is higher compared to its WD counterparts. The SS18 and A2 have mostly parallel routes, both beginning in Naples (Campania region, ≈275 km NNW from LMT) and ending in Reggio Calabria, the southernmost city of the entire Italian peninsula, located ≈100 km SSW from LMT. The SS18 is, however, smaller and has lower speed limits (up to 90 km/h), unlike the A2 (up to 130 km/h), thus indicating that the differences between these highways in terms of traffic could be due to the A2 being a preferred choice for cross-country transportation, including routes to/from the Villa San Giovanni port (90 km SSW from LMT), connecting mainland Italy to Sicily via ferries [182]. When monthly concentrations and their respective wind sectors are considered, the hypothesis by which summertime tourism could be considered a significant driver of NO_x variability is further supported by the annual cycle (Figure 11), which allows a higher degree of detail compared to seasonal categorization. From the results, it is possible to infer that cold seasons are linked to higher emissions; however, the June–September period, which is characterized by tourism, shows a shift in concentrations compatible with the trends observed in other evaluations. More importantly, the summertime increase is linked to the northeastern sector, compatible with major transportation infrastructures such as the Mediterranean Highway A2, while the western sector is practically unaffected as it reflects the broader annual cycle. Figure 15 shows monthly aggregated data on tourist arrivals and overnight stays in the region, provided by the regional department of tourism [183]. An “overnight stay” is a fully registered night spent at an authorized accommodation facility within the region; for example, any given tourist arriving in Calabria and spending four nights at registered facilities is counted as one “arrival” and four “overnight stays”. Tourism peaks between June and September, matching the increase in NO_x concentrations observed at LMT during the warm season. Figure 16 shows monthly averages reported for the entire observation period of this study (2015–2023). COVID-19 lockdowns in 2020 have deeply impacted tourism in the region, as it took three years to reach pre-pandemic levels.

These findings underline the importance of integrating multiple evaluations (wind directions and speeds, daily and weekly cycles, annual cycles, and external data such as tourism) in source apportionment efforts, as each of these methods alone would not provide sufficient evidence to support hypotheses concerning emission sources.

With growing concern over environmental issues and the effects of air quality parameters on human health, it is also crucial to assess multi-year tendencies and verify whether specific pollutants are on the rise, declining, or experiencing shifts in global balances. Due to LMT’s nature and peculiarities, tendencies are dependent on wind sectors, which in turn are affected by the balance between local and remote sources of emission (Figure 12). Using the Mann–Kendall (MK) [156,157] method, which has previously been used at LMT to assess the multi-year tendencies of CO, CO₂, and CH₄ [147], all evaluated parameters have yielded declining tendencies (Table 6), although not all results were statistically significant and varied between NO and NO₂. The Hirsch-Slack (or Seasonal Mann–Kendall, SMK) method [158] was also applied to account for seasonal tendencies at the site and showed substantial agreement with the MK method. The general NO_x trend indicates that effective policymaking, sustainable policies, and new technologies mitigating anthropogenic emissions can lead to gradual improvements in air quality. The decline is, however, in contrast to CO₂ and CH₄, whose levels are on the rise, and CO, which experienced years of declining trends, culminating with a shift towards higher concentrations in recent years [38,147]. A major turning point in LMT’s record was found using Pettitt’s test [159] for change-point detection, which indicated February 2020 (northeastern) and March 2020 (western) as the months showing a considerable change in the record. This is consistent with major reductions in anthropic activities caused by the first COVID-19 lockdown [91], with some restrictions being in place before the lockdown itself [138]. The delay of one month between the two change points may be caused by distinct timing in terms of restrictions: the northeastern sector of LMT responded rapidly to strict regulations introduced in the country due to the known influence of local sources; the western sector, which is characterized by generally cleaner air masses, may have responded later due to other restrictions introduced in other Mediterranean regions. In 2020, Italy was in fact the first country to introduce a full-scale lockdown aimed at mitigating the COVID-19 pandemic [138,139].

Monthly averages observed during the entire observation period (2015–2023) have been compared with data on tourism issued by the regional department [183] and compared with LMT’s measurements of NO_x from the northeastern sector using Pearson’s correlation coefficient [184,185], Kendall’s tau [186,187], and Spearman’s rho [188,189] methodologies. These methods provide values between −1 (perfect negative correlation) and +1 (perfect positive correlation), as well as the respective p-values to assess the significance of these correlations. The results are shown in

Table 8. Results of Pearson’s (PCC), Kendall’s tau (Tau), and Sperman’s rho (Rho) statistical evaluations between monthly NO_x measurements at LMT, from the northeastern sector, and tourist data provided by Regione Calabria. The results are differentiated by period (all, June–September, October–May), tourist arrival type (Italian, foreign, total), and years (2015–2023 and 2015–2019 to account for the pre-pandemic period). These results refer specifically to monthly arrivals.

Period	Type	PCC		Tau		Rho
		Correl.	p-Value	Correl.	p-Value	Correl.	p-Value
All (2015–2023)	Italian	0.179	0.067	0.133	0.044	0.205	0.036
	Foreign	0.124	0.206	0.101	0.126	0.136	0.167
	Total	0.176	0.073	0.101	0.127	0.153	0.119
JUN–SEP (2015–2023)	Italian	0.341	0.044	0.243	0.040	0.358	0.035
	Foreign	0.565	<0.001	0.492	<0.001	0.638	<0.001
	Total	0.406	0.015	0.294	0.012	0.431	0.010
OCT–MAY (2015–2023)	Italian	0.098	0.418	0.068	0.407	0.116	0.341
	Foreign	−0.230	0.057	−0.055	0.500	−0.085	0.483
	Total	−0.014	0.906	−0.018	0.819	−0.010	0.933
All (2015–2019)	Italian	0.140	0.288	−0.013	0.880	−0.034	0.795
	Foreign	0.041	0.755	−0.015	0.859	−0.066	0.615
	Total	0.125	0.344	−0.059	0.508	−0.097	0.460
JUN–SEP (2015–2019)	Italian	0.360	0.129	0.321	0.058	0.433	0.065
	Foreign	0.835	<0.001	0.719	<0.001	0.873	<0.001
	Total	0.418	0.074	0.356	0.034	0.468	0.044
OCT–MAY (2015–2019)	Italian	−0.259	0.106	−0.212	0.054	−0.300	0.059
	Foreign	−0.383	0.014	−0.305	0.005	−0.460	0.003
	Total	−0.324	0.041	−0.320	0.003	−0.441	0.004
All (2020–2023)	Italian	0.231	0.125	0.133	0.201	0.209	0.166
	Foreign	0.072	0.637	0.094	0.365	0.150	0.321
	Total	0.216	0.153	0.139	0.181	0.214	0.156
JUN–SEP (2020–2023)	Italian	0.443	0.084	0.15	0.450	0.291	0.273
	Foreign	0.201	0.453	0.2	0.305	0.270	0.309
	Total	0.437	0.089	0.183	0.350	0.338	0.2
OCT–MAY (2020–2023)	Italian	−0.009	0.961	−0.078	0.564	−0.122	0.524
	Foreign	−0.249	0.191	−0.098	0.467	−0.152	0.427
	Total	−0.097	0.614	−0.073	0.589	−0.131	0.496

(arrivals) and

Table 9. Results of Pearson’s (PCC), Kendall’s tau (Tau), and Sperman’s rho (Rho) statistical evaluations between monthly NO_x measurements at LMT, from the northeastern sector, and tourist provided by Regione Calabria. The results are differentiated by period (all, June–September, October–May), and tourists arrival type (Italian, foreign, total), and years (2015–2023 and 2015–2019 to account for the pre-pandemic period). These results refer specifically to monthly overnight stays.

Period	Type	PCC		Tau		Rho
		Correl.	p-Value	Correl.	p-Value	Correl.	p-Value
All (2015–2023)	Italian	0.184	0.060	0.164	0.013	0.236	0.015
	Foreign	0.169	0.084	0.102	0.123	0.146	0.138
	Total	0.187	0.056	0.132	0.046	0.185	0.058
JUN–SEP (2015–2023)	Italian	0.355	0.035	0.344	0.003	0.471	0.004
	Foreign	0.586	<0.001	0.428	<0.001	0.621	<0.001
	Total	0.415	0.013	0.381	0.001	0.523	0.001
OCT–MAY (2015–2023)	Italian	0.155	0.201	0.120	0.144	0.165	0.174
	Foreign	0.205	0.090	−0.046	0.575	−0.068	0.574
	Total	−0.027	0.819	0.031	0.701	0.042	0.731
All (2015–2019)	Italian	0.145	0.271	0.033	0.709	0.012	0.924
	Foreign	0.065	0.622	−0.077	0.384	−0.136	0.3
	Total	0.134	0.308	0.001	0.984	−0.035	0.786
JUN–SEP (2015–2019)	Italian	0.282	0.240	0.403	0.015	0.512	0.026
	Foreign	0.642	0.003	0.403	0.015	0.608	0.006
	Total	0.318	0.184	0.426	0.010	0.533	0.020
OCT–MAY (2015–2019)	Italian	−0.191	0.235	−0.128	0.250	−0.225	0.161
	Foreign	0.394	0.011	−0.371	<0.001	−0.560	<0.001
	Total	−0.330	0.037	−0.210	0.057	−0.331	0.037
All (2020–2023)	Italian	0.250	0.097	0.163	0.115	0.233	0.122
	Foreign	0.132	0.387	0.123	0.238	0.197	0.193
	Total	0.242	0.108	0.141	0.174	0.215	0.153
JUN–SEP (2020–2023)	Italian	0.504	0.046	0.183	0.350	0.332	0.208
	Foreign	0.286	0.282	0.216	0.265	0.291	0.273
	Total	0.507	0.044	0.183	0.350	0.329	0.212
OCT–MAY (2020–2023)	Italian	−0.008	0.963	−0.024	0.867	−0.073	0.704
	Foreign	−0.206	0.282	−0.064	0.642	−0.107	0.576
	Total	−0.121	0.531	−0.068	0.615	−0.112	0.560

(overnight stays).

From the statistical evaluations, it is possible to infer that wintertime correlations do not correlate with the reduced tourism arrivals, as Calabria as a region is commonly visited during the boreal summer. Warm periods (June through September), however, show high correlation factors, especially during the pre-COVID years (2015–2019). Overnight stays also yield high correlation factors during these periods. These results, combined with data obtained from ANAS on vehicular traffic, provide substantial evidence of a summertime peak in NO_x, which is in contrast with the hypotheses of past research. In fact, previous studies on LMT data variability neglected these circumstances, associating the winter season with the highest annual activity in terms of vehicular traffic and other sources of anthropogenic pollution.

5. Conclusions

At the Lamezia Terme (LMT) WMO/GAW site in Calabria, Southern Italy, a multi-year and cyclic assessment of NO_x variability has allowed us to verify a number of hypotheses raised by previous studies based on short observation periods. The study introduced, for the first time, wind lidar measurements at a select altitude threshold to complement wind direction and speed measurements performed by the local weather station. It also integrated its results with regional data on tourism and vehicular traffic, provided by local and national institutions, to assess the hypotheses raised by previous research.

Following the methodologies applied to other gases, as well as aerosols, NO_x has been evaluated in terms of daily/weekly cycle variability, dependence on specific wind speed/direction thresholds, and multi-year tendencies. The considerably longer (2015–2023) study period compared to previous research, which was based on several months of data, has allowed us to confirm the effects of fresh anthropogenic emissions on the daily cycle, as rush hour traffic peaks in concentration shift by precisely one hour depending on clock times (CEST/CET), a pattern that is not compatible with natural sources of emission. The northeastern-continental sector of LMT, more exposed to anthropogenic emissions, has yielded higher concentrations of NO_x, especially at low wind speeds, thus confirming the influence of fresh emissions over the site’s measurements. Sporadic peaks from the western-seaside sector could be attributed to wind inversion patterns typical of the site’s geomorphology and near-surface wind circulation, which is well oriented on two main axes. The evaluation of weekly cycles has yielded the most significant results ever observed at LMT, with all combinations of wind sectors and seasons showing clear differences between weekdays (WD, MON-FRI) and weekends (WE, SAT-SUN), which in turn reflect different degrees of anthropic influence. In contrast to other parameters evaluated at the same site, multi-year tendencies—which are heavily affected by local wind circulation—show a decline in concentrations, punctuated by peaks that affect the overall statistical significance of the overall trends. Furthermore, the integration of data on tourism and highway vehicular traffic has provided new evidence in favor of increased NO_x emissions during the boreal summer season, which were largely neglected by previous research on LMT.