# Greenhouse gases (CO2 and CH4) at an urban background site in Athens, Greece: Levels, sources and impact of atmospheric circulation

K. Dimitriou, A. Bougiatioti, M. Ramonet, F. Pierros, P. Michalopoulos, E.

Liakakou, S. Solomos, P.-Y. Quehe, M. Delmotte, E. Gerasopoulos, et al.

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► To cite this version:

K. Dimitriou, A. Bougiatioti, M. Ramonet, F. Pierros, P. Michalopoulos, et al. Green-
house gases (CO2 and CH4) at an urban background site in Athens, Greece: Levels, sources
and impact of atmospheric circulation. Atmospheric Environment, 2021, 253, pp.118372.
10.1016/j.atmosenv.2021.118372. hal-03230496

HAL Id: hal-03230496

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# Greenhouse gases (CO₂ and CH₄) at an urban background site in Athens, Greece: Levels, sources and impact of atmospheric circulation

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4 K. Dimitriou¹, A. Bougiatioti¹*, M. Ramonet², F. Pierros¹, P. Michalopoulos¹, E.

5 Liakakou¹, S. Solomos³, P-Y. Quehe⁴, M. Delmotte², E. Gerasopoulos¹, M.

6 Kanakidou⁵, N. Mihalopoulos¹,⁵*

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8 1. Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Palaia Penteli, 15236 Athens, Greece

9 2. Laboratory for Sciences of Climate and Environment, Paris-Saclay University, 91190

10 Paris, France

11 3. Research Centre for Atmospheric Physics and Climatology, Academy of Athens, Athens, Greece

12 4. Climate and Atmosphere Research Center, The Cyprus Institute, 20 Konstantinou Kavafi str. 2121, Aglantzia, Nicosia, Cyprus

13 5. University of Crete, Department of Chemistry, Environmental Chemical Processes Laboratory, 70013 Heraklion, Crete, Greece

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## Abstract

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21 Year-round carbon dioxide (CO₂) and methane (CH₄) concentration measurements, performed for the first time in the city of Athens, Greece from 21/12/2018 to 31/12/2019, are presented in this study and analyzed in relation to atmospheric circulation patterns at a local, regional and long-range transport scale. Clear diurnal and seasonal variations of both greenhouse gases were detected. The observed increased levels during night and early morning hours are attributed to traffic/heating emissions and leakages of residential natural gas for CO₂ and CH₄, respectively. Using CO₂ and CH₄ levels simultaneously measured at the regional background site at Finokalia (Greece), increments in their levels due to local and regional anthropogenic sources within the city were assessed. For CO₂, maximum and minimum increments were clearly observed during winter and summer respectively, suggesting a greater impact of combustion of fossil fuel and especially of biomass on CO₂ levels during winter. On the other hand, CH₄ increments were similar in all seasons, suggesting that local sources of CH₄ remain quite constant year-round. Through the implementation of the Conditional Probability Function (CPF), the emission sources of these greenhouse gases have been localized to the northern and the eastern domains of the Athens basin. Stagnant atmospheric conditions were also associated with an increased likelihood of CO₂ and CH₄ episodes. Backward modeling simulations with FLEXPART and HYSPLIT models indicate an industrial zone and a petrochemical zone, situated to the north and to the west of Athens respectively, as possible CH₄ regional sources as well as possible CO₂ contributions from southern directions attributed to shipping emissions from the port of Piraeus. The present study provides knowledge needed for the determination of greenhouse gas emission mitigation strategies in Athens.

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47 **Keywords:** Greenhouse gases, CO₂, CH₄, CPF, PSCF, FLEXPART

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50 *Corresponding Author:* Mihalopoulos Nikolaos (nmihalo@noa.gr), Bougiatioti Aikaterini (abougiat@noa.gr)
# 1. Introduction

Carbon dioxide ($CO_2$) and methane ($CH_4$) are the first and second most important greenhouse gases, respectively. The emissions of $CO_2$ are mainly associated with fossil fuel and biomass combustion (Xia et al., 2020a), whereas $CH_4$ emissions are related to a more complex mixture of anthropogenic and non-anthropogenic sources including among others wetlands, rice paddies, livestock, landfills, fossil fuel combustion and distribution, combustion of fossil fuels and agricultural waste (Tiwari et al., 2020). Therefore, increased emissions from both the agriculture and waste sector and the fossil fuel sector are likely the dominant cause of global $CH_4$ concentration increase, highlighting the need for stronger mitigation in both areas (Jackson et al., 2020).

Many recent publications have highlighted the impact of atmospheric transport on $CO_2$ and $CH_4$, triggering an increment of their concentrations at the receptor sites. Although, these studies mostly focused on Asian regions, some analyses for Europe also exist. Air masses passing over urban areas were associated with increased mixing ratios of $CO_2$ at a sampling site in central China (Xia et al., 2020a), whilst maximum $CH_4$ levels at the same station were related to air parcels travelling above intense $CH_4$ sources from extensive rice cultivation (Xia et al., 2020b). In addition, elevated $CO_2$ and $CH_4$ levels in the megacity of Shanghai (China), were related to air masses passing over "super-emitters" of greenhouse gases such as coal-fired power plants, gas-fired combustion plants and waste-treatment plants, whereas air masses of a marine origin reduced the observed $CO_2$ quantities (Wei et al., 2020). Furthermore, parts of Yunnan Province (China) as well as India and Pakistan were identified as potential source areas of $CO_2$ and $CH_4$ at a mountain background station located in southwestern China (Cheng et al., 2019). Coal combustion, coal washing and industrial activities in Inner Mongolia of China, northern and northeastern China were identified as major sources of $CO_2$ measured in a Northeastern highland area of South Korea during winter, whereas for the same season the exogenous $CH_4$ sources included among others rice cultivation and waste landfill in eastern China and oil/gas leakages in eastern Russia (Kim et al., 2020).

In Europe, air mass back-trajectories analysis of seven $CO_2$ episodes, recorded at the high Alpine environmental research station of Mount Zugspitze (Germany), indicated that the observed extreme $CO_2$ concentrations were caused by transport of air masses from central Europe and Germany in five cases, as well as by local influences for two events (Ghasemifard et al., 2019). Moreover, maximum $CO_2$ concentrations at a station located in the Spanish northern plateau were marked by air mass trajectories from North Africa affected by nearby cities, whereas minimum concentrations for both $CO_2$ and $CH_4$ were detected in summer and corresponded to air masses originating from the ocean (Pérez et al., 2018).

The Mediterranean and especially its eastern basin is a crossroad of atmospheric air masses from Asia, N. America, Europe and Africa and an area particularly sensitive to climate change as measurements of temperature indicate that it is warming faster compared to the global mean temperature increase (Giorgi 2006). In addition, for an "average" future emissions scenario (A1B), the climate models predict an increase in temperature of the order of 3.5 - 4.0° C, with a decrease in rainfall by about 30% by the end of the century (Giorgi 2006, Giorgi and Lionello, 2008). However all up-to-date studies regarding greenhouse gases in the area and especially in Greece are limited to their emissions from specific sectors of the Greek economy (Koutsou et al., 2018, Samiotis et al., 2018, Papaefthimiou et al., 2016, Sintori et al., 2019). To our knowledge no published work regarding $CO_2$ and $CH_4$ levels in the area, as well as the factors controlling their levels exists.

One of the greatest challenges facing humanity in the coming decades is to produce more energy with lower GHG emissions at acceptable costs. The first step for cities in order to
realize their potential is to identify and measure where their main sources of emissions are. This study presents one year of CO₂ and CH₄ measurements performed in the city of Athens, Greece, one of the most populated urban areas in the Eastern Mediterranean with about 4 million inhabitants. These measurements constitute not only the first long-term dataset of CO₂ and CH₄ in the city of Athens but also in the Eastern Mediterranean in general and thus provide new information regarding greenhouse gas emissions in the area. CO₂ and CH₄ concentrations were elaborated in conjunction with wind speed/direction data and state-of-the art atmospheric dispersion and trajectory models, in order to identify possible emission sources at a local, regional and long-distance scale. In addition, the contribution of Athens city and the anthropogenic influence in the measured CO₂ and CH₄ levels in Athens were evaluated by using simultaneously measurements at the regional reference site of Finokalia, Crete in the Eastern Mediterranean.

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## 2. Data and Methodology

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### 2.1. Description of sampling sites and measurements

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The Thissio urban air quality sampling site of the National Observatory of Athens (NOA, latitude: 37.97° N, longitude: 23.72° E, altitude: 105m Above Sea Level (ASL)) is situated at the Nymphs hill located in the historical center of Athens (Greece) (Figure 1). More details on the site can be found in Courtziou et al. (2017) and Stavroulas et al. (2019). The sampling site was equipped with a Picarro G2401 cavity ring-down spectrometer (CRDS) for the monitoring of greenhouse gasses (CO₂, CO, CH₄ and H₂O) with a 1 s time resolution (Picarro, 2018). These measurements were then averaged to hourly values and the concentration time series of CO₂ (ppm), CH₄ (ppb) and CO (ppb), covering the interval from 21/12/2018 to 31/12/2019, were subsequently acquired and analyzed. The system has been calibrated 20 times over this period, using a suite of three cylinders which have been prepared and calibrated at the Laboratory for Sciences of Climate and Environment (LSCE, France). The dataset is calibrated according to the WMO-X2007 and WMO-X2004A reference scales for CO₂ and CH₄ respectively. In addition one target cylinder of known CO₂ and CH₄ concentrations has been measured twice a day since 17/05/2019. The measurement repeatability's estimated from this target cylinder over the last 7.5 months are 409±5 ppm and 2018±10 ppb for CO₂ and CH₄, respectively.

Concurrent Black Carbon (BC) concentrations were monitored at the site using a dual spot 7-wavelegth Magee Scientific AE-33 Aethalometer (Drinovec et al., 2015) operating at a 1-min resolution and a 5 L min⁻¹ flow rate. In addition, hourly wind speed (m s⁻¹) and wind direction (decimal degrees) measurements for the same time period were obtained from the co-located meteorological station of NOA. The exact position of the NOA Thissio sampling site in the Athens basin, along with the locations of emission source areas around the city, possibly affecting the observed levels of greenhouse gases in Athens, are depicted in Figure 1b. Hourly concentrations of CO₂ and CH₄ were also obtained from the rural background station of Finokalia (latitude: 35.33° N, longitude: 25.67° E, altitude: 250m ASL) located at the North coast of the island of Crete (Greece) (Figure 1a). More details about the Finokalia site can be found in Mihalopoulos et al. (1997). No significant human activities occur within a radius of 15 km around Finokalia station and thus the measurements at Finokalia were considered as a reference in order to perform comparisons with data from the Thissio sampling site.

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<figure><img src="image_3.png" /><figcaption>Figure 1: a) Map of Greece with the locations of Athens and Finokalia b) Map of Attica region which depicts the positions of Thissio urban background sampling station in Athens (yellow dot), oil refineries (red dots), Liquefied Natural Gas (LNG) transfer point (blue dot), industrial zone to the North of Athens (red square), waste water plant (green dot), landfill (black dot)</figcaption></figure>

## 2.2. Methodology

The present study focuses on the identification of possible associations among the levels of the two major greenhouse gases (CO₂ and CH₄) in Athens and the atmospheric circulation at a local, regional and long-range scales. Depending on the origin of the air masses sampled at Thissio, CO₂ and CH₄ concentrations will be influenced by different regions and therefore different processes. CO was used in conjunction with BC, as a marker of combustion of fossil fuel and biomass.

Conditional Probability Function (CPF)roses, which connected each wind sector with a probability (%) for the occurrence of hourly CO₂ and CH₄ episodes, were calculated on a seasonal basis based on the methodology presented by Dimitriou and Kassomenos (2017) The pollution threshold, which had to be exceeded by an hourly CO₂ or CH₄ concentration in order to be characterized as an episode, was set to the 90th percentile of all hourly CO₂ and CH₄ concentrations, respectively. CPFᵢ probability values for each wind sector (i) are provided by Equation 1, in which nᵢ and mᵢ are the total number of hourly concentrations and the number of episodes, respectively, which correspond to sector (i), thus the proportion of episodic hourly concentrations in each wind sector is generated.

$$CPF_i = \frac{m_i}{n_i} \times 100 \quad (1)$$

In order to identify possible regional contributions of CO₂ and CH₄, suspicious cases of extreme hourly concentrations were studied with 12-hour backward simulations of air tracers performed by the Lagrangian particle dispersion model FLEXPART version 10.4 (Pisso et al., 2019) coupled with meteorological input data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). The arrival of air tracers over the receptor site was set in the 500 – 1000m Above Ground Level (AGL) vertical zone,
184 in order to be generally within the boundary layer over Athens which during daytime (12:00 UTC) has a mean height of ~1617±324 m, varying from 982 m (December) up to 2090 m (July), whilst during nighttime (00:00 UTC) its height is approximately stable with a mean value of ~892±130 m (Alexiou et al., 2018).

188 Moreover, aiming to identify possible contributions of long-range transport to CO₂ and CH₄ levels in the atmosphere of Athens, 72-hour air mass back trajectories ending at the Thisissio station every hour of each day (from 00:00 – 23:00 UTC that is 24 trajectories per day), were generated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model of the National Oceanic and Atmospheric Administration (NOAA) (Rolph et al., 2017; Stein et al., 2015). For the computation of the trajectories, NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) meteorological data from the Reanalysis 1 package were used as input for the HYSPLIT model. Daily mean concentrations of CO₂ and CH₄ were calculated only when at least 75% of the hourly concentrations of each day were available. Nevertheless, because the completeness of the Picarro data series was excellent, daily CO₂ and CH₄ concentrations of 374 out of the 377 studied days were calculated and separately associated with the backward trajectories through the Potential Source Contribution Function (PSCF) algorithm (Karaca et al., 2009; Polissar et al., 2001). Each backward trajectory consisted by 73 hourly trajectory points (72 hours backwards + 1 arrival point) composing the pathway of the corresponding air parcel, thus 655,248 trajectory points (374 days × 24 trajectories per day × 73 points per trajectory) were produced and distributed in the cells of a 0.5° × 0.5° resolution grid (25°W to 45°E and 20°N to 60°N). Only 5572 (0.9%) of these points exceeded the grid boundaries and thus were not considered in our analysis as being highly distant from the receptor site. The episode probability at the receptor site, when the incoming air masses fly over each grid cell ij, is calculated by the PSCF algorithm based on Equation 2 and is attached to the corresponding ij cell.

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$$PSCF_{ij} = \frac{m_{ij}}{n_{ij}} \quad (2)$$

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213 In Equation 2, nᵢⱼ is the total number of trajectory points passing through the ij cell, whilst mᵢⱼ is the number of trajectory points in the ij cell which belong to trajectories related to daily CO₂ or CH₄ pollution episodes in Athens. The limit of daily exceedances was set to 90th percentile of all daily concentrations. Finally, in order to avoid possible extreme PSCF values in distant grid cells with sparse trajectory coverage, PSCFᵢⱼ results were multiplied with a Wᵢⱼ weight function (Equation 3, Liu et al., 2016; Dimitriou and Kassomenos, 2018), aiming to reduce these highly unsure values. In Equation 3, nₐve is the average number of trajectory points in all grid cells having non-zero trajectory point content.

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$$W_{ij} = \begin{cases} 1.0 & (3n_{ave} \le n_{ij}) \\ 0.7 & (1.5n_{ave} \le n_{ij} < 3n_{ave}) \\ 0.4 & (n_{ave} \le n_{ij} < 1.5n_{ave}) \\ 0.2 & (n_{ij} < n_{ave}) \end{cases} \quad (3)$$

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## 3. Results

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### 3.1. Seasonal variations of CO₂ and CH₄

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The examination of the CO₂ and CH₄ diurnal variations per season at the Thissio sampling site (Figure 2), indicated a clear diurnal variability for both greenhouse gases in all seasons, characterized by an increment of hourly concentrations during evening/night and early morning hours. In urban areas such as Athens, CO₂ is mainly produced from the combustion of petroleum-based fuels in car engines and central heating systems (Gioli et al., 2013), but the atmospheric concentrations are also influenced by exchanges with local or regional vegetation. This biospheric signal is depending on the green areas in the city and the type of vegetation. Regarding CH₄ the main emissions may be due to leakages from residential natural gas units (Fischer et al., 2018; Sanchez et al., 2018), natural gas automobiles (Sanchez et al., 2018; Hu et al., 2018) and natural gas pipeline networks (Gioli et al., 2013). A study conducted in the megacity of Los Angeles from 2011–2017, using a mountaintop remote sensing mapping spectrometer, reported that the city's CH₄ emissions are strongly correlated with the consumption of natural gas by residential and commercial consumers, with a leakage rate of (1.4 ± 0.1)% (He et al., 2019), however the leakage rate is expected to vary strongly from one city to the other depending on the age and the maintenance of gas distribution infrastructure (Schneising et al., 2020). Thus, the observed intraday variations of CO₂ and CH₄ hourly levels in Athens were attributed to traffic/heating emissions and leakages from residential natural gas units and distribution systems respectively. Moreover, the examination of hourly Mixing Layer Height (MLH) values over Athens for the period February 2016 – February 2017 (Figure S1), which were estimated with HYSPLIT model using the turbulent kinetic energy profile method (Dumka et al., 2018; Liakakou et al., 2020), showed that the stabilization and reduction of CO₂ and CH₄ levels during morning hours in all seasons (Figure 2) occurs after the initiation of the MLH increment related to the enhancement of solar irradiance (Alexiou et al., 2018, Tsaknakis et al., 2011), which facilitates air exchange with higher atmospheric layers.

For CO₂, an enhancement of hourly concentrations during spring, summer and autumn is observed primarily during early morning hours (Figure 2b, 2c, 2d), a finding that was attributed to the intensification of traffic emissions. During winter the observed double peak during early morning and night (Figure 2a) is probably related to the traffic rush hours and residential heating emissions, respectively. This is drastically reduced in spring and autumn when residential heating emissions are low and is practically removed in summer (Figure 2c) in the absence of such emissions. These findings are in accordance with BC measurements at the site and especially the two different BC components attributed to fossil fuel and wood combustion (Liakakou et al., 2020). Due to the financial crisis, which struck Greece after 2010, an extensive use of biomass for residential heating has replaced the burning of fossil fuels in many households of Athens (Fourtziou et al., 2017; Gratsea et al., 2017; Grivas et al., 2019; Liakakou et al., 2020). Biomass burning consequently remains an important source of CO₂ affecting its atmospheric loading particularly in the cold season (Xia et al., 2020a; Liu et al., 2018).

<figure><img src="image_4.png" /><figcaption>(c)</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>(d)</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Figure 2: Diurnal variations of CO₂ and CH₄ at the Thissio station per season: a) winter (December to February) b) spring (March to May) c) Summer (June to August) d) autumn (September to November) (all hours are in UTC). The error bars depict standard error of the values.</figcaption></figure>

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<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>
Figure 3: Seasonal a) CO₂ – CO and b) CH₄ – CO scatterplots with linear regression for the Thisissio station in Athens based on hourly values. winter in blue, spring in green, summer in red and autumn in olive color. Average seasonal CO₂ and CH₄ concentrations from Finokalia reference station are also provided in the inserted rectangle.

Maximum and minimum hourly concentrations of CO₂ are clearly observed in winter and summer respectively, whereas CH₄ hourly concentrations among the four seasons are similar with slightly elevated levels in winter (Figure 2). A study conducted in the megacity of Shanghai (China), also showed that although both CO₂ and CH₄ have strong diurnal variations, only CO₂ exhibited seasonal differences (Wei et al., 2020). This finding is indicative of the greater impact that fossil fuel combustion and biomass burning have on CO₂ levels than on CH₄ levels. A simple linear regression model analysis implemented among both CO₂ and CH₄ hourly levels with CO hourly concentrations, also verified this finding through the calculation of higher seasonal coefficients of determination (R²) in the CO₂ – CO analysis in comparison with the CH₄ – CO analysis (Figure 3).

The excellent correlation of the two carbon oxides (Figure 3a) suggests that both of them share a common source throughout the year, while this correlation is stronger during winter (R²=0.96) and somewhat lower during the warmer periods (0.69 ≤ R² ≤ 0.86). On the other hand when comparing CH₄ and CO₂ it is apparent that there are at least two different sets of data, one exhibiting a good correlation between them and indicative of a common source (combustion). Therefore a clear difference in origin can be seen between CO₂ and CH₄ which indicates that although combustion is the main source for CO₂, for CH₄ the presence of additional important sources is clearly evident. For both CO₂ and CH₄, the correlations with CO₂ were stronger in winter and weaker in summer (Figure 3), thus the impact of combustion emissions on both greenhouse gases was more evident in the cold period of the studied dataset.

Although chemistry of CO₂ could account for the lower correlation with CO₂ in summer, the absence of correlation between CO₂ and CH₄, especially in summer, indicates again the impact from sources other than combustion, such as natural gas leakages transported to the area by winds. This assumption is backed by the excellent correlation between CO₂ and BC at 880 nm for the whole measurement period (R²=0.82), while for methane the respective correlation is very low (R²=0.26) (Figure S4). Finally, the intercepts of the CO₂ – CO linear regressions for all seasons, had very small differences with the average CO₂ concentrations which were acquired by the Finokalia rural reference station (Figure 3). More specifically, the differences for CO₂ ranged from 9.9 ppm to 15.3 ppm, which is within the observed seasonal standard deviation values, showing that urban anthropogenic emissions in Athens could be considered as additions on the levels of CO₂ monitored in the Eastern Mediterranean basin. The fact that CO₂ baseline concentrations at Finokalia were marginally higher than the calculated linear regression intercepts in all seasons (Figure 3) was attributed to the weak secondary regional influences that affect the reference monitoring site of Finokalia.

## 3.2. The effect of wind on CO₂ and CH₄ levels

### 3.2.1. Wind speed

Figure 4 presents the scatterplots between wind speed and CO₂ (4a) and CH₄ (4b) levels. Increased concentrations of both CO₂ (5a) and CH₄ (5b) at Thisissio station are mainly associated with wind speeds less than 2 m s⁻¹. A threshold value of 3 m s⁻¹ (light breeze conditions) has already been used in the area as a criterion favoring the accumulation of high pollution loads within the mixing layer (Fourtziou et al., 2017; Panopoulou et al., 2018).
Thus, atmospheric stagnation triggering the accumulation of greenhouse gas emissions from local sources is identified as a primary cause of the episodes. Nevertheless, some sparse cases of elevated CH₄ concentrations were also related to wind speeds up to 5 m s⁻¹ approximately (Figure 4b), a fact which was interpreted as an indicator of possible CH₄ transport from regional sources.

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### 3.2.2. Wind direction

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The influence of specific wind directions on CO₂ and CH₄ levels, due to the transport of emissions from local sources, was studied initially with seasonal pollution roses by using CPF and the results are presented in Figure 5. It is clear that calm winds (<0.3 m s⁻¹) were associated with high episode probabilities primarily during winter (for CO₂ and CH₄) and spring (only for CO₂) (Figure 5). Moreover, pollution roses of CO₂ and CH₄, included in Figure S3 and Figure S4 respectively, showed that increased hourly levels of both greenhouse gases mainly occurred in conjunction with winds blowing from northern and eastern directions in all seasons, whilst according to the CPF roses included in Figure 5, the prevalence of winds from northern and eastern sectors was associated with increased likelihood of episodes exceeding the 90th percentile limit. Therefore, possible transport of CO₂ and CH₄ from emission sources situated to the northern and the eastern domains of the Athens basin was indicated. Moreover, the residential and commercial center of Athens, which also includes many high volume traffic arteries, is located northwards and eastwards of the Thissio station, thus CO₂ and CH₄ emissions are expected to occur in these areas and are then transported to the Thissio station following the airflows. According to CPF roses, peak episode likelihood for CO₂ was related to winds originated from the eastern sector whereas winds from the northern sector had a stronger impact on CH₄ concentrations primarily during spring and summer (Figures 5f, 5g). Consequently, a special emphasis must be given to the areas crossed by these specific wind flows, aiming to identify potential emission sources of CO₂ and CH₄.

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<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /><figcaption>Figure 4: Seasonal scatterplots of hourly a) CO₂ and b) CH₄ concentrations vs wind speed.</figcaption></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>
<figure><img src="image_15.png" /><figcaption>Figure 5: Seasonal CPF roses for CO₂ for winter (a), spring (b), summer (c) and autumn (d) and for CH₄ for winter (e), spring (f), summer (g) and autumn (h).</figcaption></figure>

## 3.3. Local versus regional contributions of CO₂ and CH₄ in Athens

### 3.3.1. A comparison with Eastern Mediterranean CO₂ and CH₄ baseline levels

A direct comparison among monthly concentrations of CO₂ in Athens and Finokalia, showed that CO₂ levels in Athens were strongly enhanced in cold seasons (Figure 6a), due to the addition of emissions from local sources such as biomass burning and fossil fuel combustion for residential heating. Despite the fact that the station is located in the center of Athens we cannot exclude the additional emission from the respiration by the urban and/or regional vegetation, which has been shown to be significant in other cities (Decina et al., 2016; Miller et al., 2020). On the contrary, during the warmest months of 2019, with special emphasis on July and August, reduced CO₂ concentrations in Athens were observed quite similar with the Eastern Mediterranean CO₂ concentrations monitored at the Finokalia rural and marine background reference station (Figure 6a). The carbon uptake by the vegetation present in the footprint of the Thissio site tends to compensate for the CO₂ offset due to anthropogenic emissions. With respect to CH₄, the situation is quite different with constantly higher levels in Athens compared to Finokalia year-round. Most probably, the continuous use of residential natural gas in Athens and the related leakages, maintained CH₄ concentrations to higher levels in comparison with Finokalia throughout all seasons (Figure 6a).
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Regarding the intraday patterns of CO₂ and CH₄ concentrations at Finokalia during the most characteristic seasons of winter and summer (Figure 6b), no diurnal variations were found due to the absence of local emissions in the vicinity of the sampling site, and the smaller variability of the boundary layer height more characteristic of a marine site (Kalivitis et al., 2015; Bougiatioti et al., 2016). Therefore, during night and early morning hours, when CO₂ and CH₄ emissions from local sources in the urban area of Athens are amplified and boundary layer height is low favoring accumulation of pollutant near the surface, hourly concentrations are considerably higher than those monitored at Finokalia, particularly in winter. In summer, impact of local sources on CO₂ concentrations was weaker due to the mitigation of combustion emissions (Figure 6b). On the other hand, hourly CO₂ and CH₄ levels in Athens dropped during midday and became similar to those at Finokalia, and even lower for CO₂ due to the stronger impact of the biospheric carbon uptake, compared to Finokalia. Exception to this pattern are the CH₄ hourly concentrations during winter, which despite the mid-day reduction, maintained higher values than Finokalia (Figure 6b), probably due to the prolonged use of natural gas for residential purposes (heating/cooking) and in the industrial sector.

<figure><img src="image_16.png" /><figcaption>(a)</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>(b)</figcaption></figure>

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>
Figure 6: a) Monthly concentrations of CO₂ and CH₄ in Athens and Finokalia. b) Diurnal variations of CO₂ and CH₄ in Athens and Finokalia during winter (left panels) and summer (right panels). All hours are given in UTC.

Based on the above analysis, it can be estimated that for CO₂, the additional burden due to the anthropogenic activities, plus the effect of the biospheric fluxes, in the urban environment is on average in the order of 3.6% for the period of one year. When considering the monthly variability, the CO₂ offset in Athens range between 5.5 to 7.7% during winter, while during summer the differences are minimal (ranging between 0.6 to 1.3%). For CH₄ the additional burden due to the urban environment and activities is once again in the order of 3.5% for the whole period, but does not exhibit a seasonal difference. When considering all months, differences range between 2.1 and 4.9% with the somewhat higher values observed during winter, but not as striking differences as for CO₂.

### 3.3.2. Regional contributions of CH₄ in Athens

As shown in Figure 3 hourly extreme greenhouse gas episodes combined with low CO levels were observed only for CH₄ (Figure 3b) but not for CO₂ (Figure 3a). These hourly CH₄ extreme events, which were defined by CH₄ concentrations higher than or equal to 2400 ppb and CO concentrations less than or equal to 500 ppb (Figure 3b), were considered as indicative of regional contributions from emission sources located around the Athens basin (Figure 1). A total of 86 hourly measurements of CH₄ fulfilled the above criterion and were primarily found in summer (44.2%) and secondarily in winter (23.3%), spring (17.4%) and autumn (15.1%). In order to analyze the possible air mass origins for the above 86 cases we performed 12-hour backward emission sensitivity simulations with FLEXPART driven by GFS meteorology. The simulated air mass patterns revealed four major atmospheric circulation types related with the CH₄ episodes: north flow (80.2%), west flow (8.2%), east flow (2.3%) and stagnant flow (9.3%). Characteristic examples of simulations belonging in each one of the four orientation categories are given in Figure 7. Regional contributions from northern directions highlight the industrial zone located to the north of the Athens basin (Figure 1), as a potential source of the transported CH₄ emissions (Figure 7a). Industrial activity there, among others, includes chemical industries and food industries. Air masses approaching Athens from the west, are likely enriched with CH₄ from the three major oil refineries, the landfill, the LNG transfer station and the primary waste water plant of Athens, all located west of the measurement station of Thissio (Figure 1b). On the other hand, air masses approaching Athens from the Aegean Sea (Figure 7c), are related with only one CH₄ episode and thus seem to have minimal impact on the CH₄ concentrations at Thissio station. Finally, the arriving air masses during stagnant conditions may originate from a wide region around the Athens metropolitan area (Figure 7d) and thus may accumulate CH₄ from all the local facilities which are associated with CH₄ releases (Figure 1b).
<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /><figcaption>Figure 7: Examples of FLEXPART emission sensitivity 12-hour backward simulations corresponding to a) north b) west c) east and d) stagnant flow categories. The air tracers arrived over Athens at 500 – 1000m AGL.</figcaption></figure>

Additional factors modifying the local atmospheric circulation over Athens are related with the complex topographic terrain of Athens basin and the extended coastline. Local flows like sea breeze and katabatic/anabatic winds etc, play an important role for the distribution of atmospheric pollutants inside the city. Such local patterns are evident in Figure 8, for the severe air pollution episode of 15 March 2019, when CH₄ concentration at Thissio station reached a maximum of 3355 ppb. This specific event is analyzed with the FLEXPART model driven by high resolution WRF fields at 3×3 km grid space (Skamarock et al., 2020), thus allowing the representation of local scale circulations. Figure 8 represents the residence time for air masses arriving directly at the measurement station (0-1 m height a.g.l.) while originating only from surface sources (0-10 m a.g.l.). The resolved air-mass trajectory indicates a possible synergistic effect of multiple sources along the atmospheric path, all contributing to the extreme CH₄ levels.
<figure><img src="image_26.png" /></figure>

Figure 8. FLEXPART-WRF 12-hour backwards calculation for air masses measured at Thisio station between 01:20-01:45 UTC, 15 March 2019. The colored dots and the red rectangular correspond to the locations shown in Figure 1b.

### 3.4. PSCF results

The implementation of the PSCF model on daily CO₂ and CH₄ concentrations at Thisio station, did not associate the occurrence of daily episodes of the two studied greenhouse gases with the arrival of air masses from a specific origin (Figure 9). Contrariwise, daily CO₂ and CH₄ episodes were found to be associated with air masses approaching the station from multiple directions, thus no direct connection of these extreme events with transboundary contributions was revealed. This finding further supports the assertion that the variations of CO₂ and CH₄ in Athens mostly depend on both local and regional emissions. Nevertheless, the emergence of daily CO₂ and CH₄ episodes was more strongly associated with southern airflows through the eastern Mediterranean basin (Figure 9), thus possible long-distance contributions from the southeast Mediterranean region can be assumed. The results regarding those possible contributions, exogenous to the Athens extended region, were much clearer and perspicuous for CO₂ than for CH₄ (Figure 9), hence an influence from shipping emissions can be presumed. Total shipping emissions accounted for 3.1% of global CO₂ emissions for the period 2007 – 2012 and only for 0.24% of global CH₄ emissions for the period 2000 – 2009 (IMO, 2014). Thus, a stronger impact of shipping on CO₂ levels is demonstrated. Ekmekçioğlu et al. (2019) showed that at the two important international ports of Turkey in the East Mediterranean the amount of CO₂ emissions of Mersin port (~100 kt y⁻¹), which has a higher number of ship movements, was higher than that of Izmir port (~45 kt y⁻¹). In addition, with regard to shipping within the Greek seas, the utilization of the fuel-based (fuel sales) analysis for domestic shipping and the activity-based (ship traffic) analysis for international shipping showed that the annual ship-generated CO₂ emissions for the year 2008 reached 7000 kt y⁻¹ (Tzannatos, 2010). At this point, we should underline the fact that the evidence from the PSCF analysis, denoting a possible effect of CO₂ shipping emissions from the eastern Mediterranean basin on CO₂ levels in Athens through atmospheric transport, are not exhaustive and therefore must be further examined.
<figure><img src="image_27.png" /><figcaption>Figure 9: PSCF results for a) CO₂ and b) CH₄</figcaption></figure>

4. Conclusions

This study presents the first long-term measurements of greenhouse gases that have been conducted in the metropolitan area of Athens, Greece, covering a period of one year. CO₂ and CH₄ concentrations were analyzed in terms of atmospheric circulation at a local, regional and long-range transport scale, in order to identify sources and processes possibly affecting greenhouse gas concentrations within the Athens basin.

Increased levels of both CO₂ and CH₄ were observed during night and early morning hours in all seasons, due to the enhancement of traffic/heating emissions and residential natural gas leakages respectively, whilst the shrinkage of atmospheric mixing layer during these specific hours also facilitated the entrapment of local greenhouse gas emissions near the surface. Moreover, CO₂ presents a profound seasonal pattern with higher levels during winter and
lower levels during summer, whereas CH₄ concentrations remain similar in all seasons
implying greater contribution of fossil fuel and biomass combustion from heating on CO₂
than on CH₄ loadings. A comparison with the regional remote background reference station of
Finokalia also showed highly increased CO₂ concentrations in Athens during cold seasons
due to local emissions from combustion sources, estimating an additional burden due to the
anthropogenic influence in the order of ~6%. There remains a strong uncertainty, on the role
played by biospheric fluxes, and the regional contribution compared to that of the city. A
~3.5% CH₄ enhancement in Athens was similarly derived but did not show any seasonality.
Pollution and CPF roses suggest the existence of CO₂ and CH₄ emission sources to the north
and to the west of Thisio sampling site. Low wind speeds were also associated with
increased CH₄ and CO₂ concentrations, thus the influence of atmospheric stagnation
triggering the accumulation of local emissions also emerged.

Increased hourly CH₄ concentrations combined with low CO levels, a finding not seen for CO₂ due to the greater dependence of CO₂ on combustion sources, were considered as highly suspicious for regional contributions and thus were studied with FLEXPART dispersion model backward simulations. Regional sources of CH₄ were isolated primarily to the north and to the west of the Athens basin where an industrial zone and a petrochemical zone are situated, respectively. As regards long-range transport contributions, the implementation of PSCF algorithm coupled with backward air mass trajectories obtained by the HYSPLIT model, did not reveal any clear pattern related to episodes of the two studied greenhouse gases. Hence, local and regional sources were verified to be the primary factors affecting CO₂ and CH₄ concentrations in Athens. Possible CO₂ contributions from southern directions attributed to shipping emissions must be further examined.

Hourly levels of CO₂ and CH₄, monitored for the first time systematically in the metropolitan area of Athens, Greece, revealed seasonal and diurnal variations which were not previously known and are strongly dependent on the urban character of the sampling area. In addition, the greenhouse gas concentration dataset was elaborated with multiple source – receptor tools that enabled the localization of greenhouse gas sources affecting the Athens basin. Furthermore, the impact of atmospheric conditions on CO₂ and CH₄ levels in Athens was also demonstrated and categorized. Nevertheless, the findings of this study must be further examined in the future, when more greenhouse gas concentration data from Athens will be available. Accordingly, the enrichment of the existing original dataset with more recent data is ongoing.

544

545

## Acknowledgments

547

The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model used in this publication. This work has been supported by the Action titled "National Network on Climate Change and its Impacts (CLIMPACT)" which is implemented under the sub-project 3 of the project "Infrastructure of national research networks in the fields of Precision Medicine, Quantum Technology and Climate Change", funded by the Public Investment Program of Greece, General Secretary of Research and Technology/Ministry of Development and Investments. Authors greatly acknowledge the support of the SNO-ICOS-France network and its technical staff for the installation and maintenance of the instrumentation at Finokalia and Thisio monitoring stations. NM acknowledges support by the EU project (H2020) RINGO - 730944.

558

## Credit author statement

560
561 K. Dimitriou: Methodology, Formal analysis, Visualization, Writing—Original draft preparation; A. Bougiatioti: Data curation, Writing-Reviewing and Editing, Visualization; M.
562 Ramonet: Conceptualization, Writing-Reviewing and Editing, F. Pierros: Data curation, P.
563 Michalopoulos: Visualization, Software, E. Liakakou: Writing-Reviewing and Editing; S.
564 Solomos: Visualization, Software, Writing-Reviewing and Editing; P.-Y. Quehe: Writing-
565 Reviewing and Editing; M. Delmotte: Validation; E. Gerasopoulos: Writing-Reviewing and
566 Editing; M. Kanakidou: Conceptualization, Writing-Reviewing and Editing; N.
567 Mihalopoulos: Conceptualization, Supervision, Funding
568

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781
CO₂ & CH₄
Monitoring in Athens
Greece

<figure><img src="image_28.png" /><figcaption>Residential heating emissions</figcaption></figure>

<figure><img src="image_29.png" /><figcaption>Industrial emissions</figcaption></figure>

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /><figcaption>Traffic emissions</figcaption></figure>

<figure><img src="image_34.png" /></figure>

<figure><img src="image_35.png" /><figcaption>Natural gas leakages</figcaption></figure>

<figure><img src="image_36.png" /></figure>