Evolution of the chemical composition of fogwater collected at four sites in the Alsace region between 2015 and 2021

doi:10.21203/rs.3.rs-4016030/v1

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Evolution of the chemical composition of fogwater collected at four sites in the Alsace region between 2015 and 2021

https://doi.org/10.21203/rs.3.rs-4016030/v1

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Four sites representing urban (Strasbourg), suburban (Geispolsheim and Cronenbourg), and rural (Erstein) in the Alsace region, north east of France are sampled to investigate the evolution of the chemical composition of fog water between 2015 and 2021. For this aim, forty-two fog samples are collected using a Caltech Active Strand Cloud Collector (CASCC). The samples are analyzed for their inorganic species (metals and ions) and their physico-chemical properties (pH, dissolved organic carbon (DOC), liquid water content (LWC), and conductivity (K)). Temporal and spatial evolutions have been also investigated between the four sampling sites. Our results are then compared to previous studies performed in 1990’s at Strasbourg. Since 1999, there is a lack of fog knowledge in Strasbourg metropolitan and complete absence of fog studies. That’s why it is interesting to resume fogwater collection in order to re-build a solid background regarding air quality in France, particularly in Alsace, and assess the effectiveness of the rules and regulations that have been implemented over time.

Inorganic analysis

physico-chemical parameters

Strasbourg metropolitan

pearson analysis

principal component analysis

Fog is able to scavenge inorganic and organic species, and therefore may act as reservoir for the formation of new particles through the aqueous-phase reactions. It may also act as a natural cleaner of the lower atmosphere through the wet deposition phenomena (Elbert et al., 2000; Herckes et al., 2013; Giulianelli al., 2014; Van Pinxteren et al., 2016 ; Seinfeld and Pandis 2016; Li et al., 2017; Kim et al., 2019; Izhar et al., 2020). The formation of fog is facilitated not only in areas characterized by their high loadings of pollutants but in remote areas affected by the long-range transport (LRT) of pollutants from near-by sites and regions as well (Goodman, 1977; Zannetti et al., 1977; Watanabe et al., 2010; Yue et al., 2012). However, researchers found that fog occurrence is decreasing in Europe which is mainly related to the amelioration in air quality, in particular the decrease in nitrate and sulfate levels (Vautard et al., 2009; Quan et al., 2011; Fu et al., 2014; Giulianelli et al., 2014). For these reasons, fogwater chemistry has become a critical topic for investigation over the last few decades. The multi-dimensional characterization of fog is important for the identification of pollutant sources in the region. In-depth analyses of its sources are a major path to create some management methods to ameliorate the air quality and limit its formation and negative consequences on human’s health and ecosystem.

Field research concerning fog chemistry has initiated since the 1900’s (Herckes et al., 2015) and received more consideration since the 1980’s (Yang et al., 2011). At the beginning of the 1990's, the first urban radiation fog samples have been collected in the Alsace region during winter 1990/1991 at Strasbourg. The measurements have been continued until 1999 to study the evolution of fog chemistry (Herckes et al., 2002). The investigations of such field studies at Strasbourg have been well detailed and previously reported in many scientific papers (Millet et al., 1995, 1996, 1997; Millet, 1994; Herckes et al., 2002). After that, fog studies are not sufficiently performed compared to the international assessment and evolution of the fog research (Asif et al., 2022). Fog collection has been resumed in winter 2015 to study its evolution until winter 2021 at different sampling locations in the Alsace region (Strasbourg, Geispolsheim, Erstein, and Cronenbourg). So far, a recent investigation has been published concerning the analysis of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) to study fog evolution over the sampling years and suggest some possible sources of pollutants (Khoury et al., 2024). This aims to build a long database of its chemical composition that represents a valuable tool to evaluate the effectiveness of the regulations and policies that have been implemented, and can be used as a solid base for future policy actions in the region. This study intends to address the following questions regarding the chemical composition of fog and its evolution: (1) what are the dominant ions and metals? (2) have their concentrations increased or decreased over time (evolution vs time)? (3) has the fog nature changed from acidic to basic over time? (4) what are the probable sources of pollutants that influence fog chemistry based on different source identification techniques?

2.1. Sites description

Forty-two samples were collected at 4 different sites during October, November, and December from 2015 to 2021 at Strasbourg metropolitan covering many characteristics (see Table 1). The samples are distributed as follows: 3 samples are taken from Strasbourg in 2018 and 2021; 23 samples from Geispolsheim in 2015, 2016, 2017, and 2018; 5 samples from Cronenbourg in 2018 and 2021; and 11 samples from Erstein in 2015, 2016, and 2018. Sampling map of the different locations is illustrated in Fig. S1.1 in the Supplementary information (SI.1).

Table 1

Characteristics of the sampling sites.
Characteristic/ Site	Geispolsheim	Erstein	Strasbourg	Cronenbourg
Coordinates	48.51469° 7.64373°	48.42273° 7.66326°	48.58461° 7.75071°	48.59449° 7.71621°
Population	7,000	11,000	284,677	21,000
Superficies (Km²)	21.9	36.2	78.26	7.03
Topology	Suburban	Rural	Urban	Suburban
Sampler position	4 meters AGL	4 meters AGL	20 meters AGL	4 meters AGL
AGL: above ground level

Strasbourg site: It is surrounded by huge residential areas. At 500 m in the Northeast, 2 Km in the Southwest, and 1.5 Km in the South, there is a high load of traffic and cars. At 2 Km there is a highway through which more than 50,000 vehicles pass daily, of which 10% are heavy-duty. At 3 Km, there is the industrial zone in Kehl known as “Port du Rhin”.
Cronenbourg site: It is a district of Strasbourg (13 Km in the Northwest of the city), added to our study due to the low fog frequency at Strasbourg. It has almost the same characteristics as Strasbourg. It is surrounded by lots of residential areas and has limited agricultural fields. Besides, at 3 Km, there is the A35/A4 highway which is highly loaded by vehicles. At 4 km in the Southeast, there was the biggest brewery “Kronenbourg” in the Grand Est, which was closed in 2000.
Geispolsheim: At 300 meters in the North, there is the A35 highway which loaded with vehicles and trucks. Small commercial areas are situated at 300 meters and 1 Km away. Different commercial and medium-sized industrial areas are located in the nearby villages and towns (Illkirch Graffenstaden, Lingolsheim, Fegersheim, and Duppigheim). The sampling point is situated in a residential district where people mainly use wood for heating. The usual heating periods vary from 15 October to 15 February. There is also Strasbourg airport in the municipality “Entzheim” situated 3 km away in Northwest (NW).
Erstein: It is enclosed by rural areas involving around 10 farms. At 2 Km in the Southeast, there is a sugar industry. Also, at 1.5 Km in the West, there is a small industrial area. Erstein is surrounded by many nearby rural villages such as (Nordhouse, Schaeffersheim, and Osthouse). People tend to use more wood than those living at Geispolsheim. At 1.2 Km in the West, there are almost 55,000 vehicles that pass daily through the D1083 highway, of which 20% are heavy-duty.

2.2. Analysis protocol

The analysis protocol of fog water samples is found elsewhere (Khoury et al., 2024), and is summarized in Fig. 1. Data concerning the collected fog samples are found in Table S2.1 in the SI.2.

2.3. Statistical analysis

The data are analyzed using Microsoft Excel (version 2021) and reported as mean ± standard deviation (SD). Pearson and principal component analyses are executed on R (version 4.3.2) correlated with RStudio (version 2023.12.0 + 369). The correlation coefficient matrix is performed among the different species to identify the relationship among each other and suggest possible ionic and metal sources. The statistical benchmark is considered significant more than 0.5 for the correlation analysis.

3.1. Physical parameters

Table S2.2 to S2.6 in the Supplementary Information (SI.2) show the results for the analysis of the physical parameters for each fog sample.

The mean pH values at Geispolsheim, Erstein, Strasbourg, and Cronenbourg are respectively 6.8 ± 0.7, 6.9 ± 0.9, 6.7 ± 0.9, and 7.4 ± 0.2, which are in accordance with the WHO guidelines. There is no remarkable yearly variation during all sampling years, except for a small increase in the pH values from 2016 to 2018 at Geispolsheim, Erstein, and Strasbourg attributed to the probable decrease in the sulfate and nitrate concentrations (will be discussed below). The nature of pH has changed over time from acidic to basic. For instance, the average pH range in Strasbourg has increased from 3.5-4 to 6.1–7.4 between 1996 and 2018 (Millet et al., 1996; Herckes et al., 2002), as other cases in Europe, Asia, and other parts of the world (Giulianelli et al., 2014; Li et al., 2017; Watanabe et al., 2022). This is mainly attributed to the increase in \({\text{N}\text{H}}_{4}^{+}\) levels and the decrease in \({\text{N}\text{O}}_{3}^{-}\) and \({\text{S}\text{O}}_{4}^{2-}\) levels. The ratio of \({\text{N}\text{H}}_{4}^{+}\)/ (\(\left[{\text{n}\text{s}\text{s}-\text{S}\text{O}}_{4}^{2-}\right]+\left[{\text{N}\text{O}}_{3}^{-}\right]\)) has increased over time mainly due to the decrease in \({\text{S}\text{O}}_{4}^{2-}\) and \({\text{N}\text{O}}_{3}^{-}\) (around 20 times) concentrations and the continuous increase in \({\text{N}\text{H}}_{4}^{+}\) and \({\text{C}\text{a}}^{2+}\)levels (around 3 times). This is consistent by the observed decrease in the emissions of SO₂ in Europe and other countries, primarily because of the use of fuels containing less sulfur. Similar pH range is also observed in other countries such as Lebanon (Khoury et al., 2024), Bangladesh (Nahar et al., 2022), India (Ambade et al., 2014), Switzerland (Michna et al., 2015), and some parts of the US (Raja et al., 2005), and Poland (Błaś et al., 2010).

The mean conductivities at Geispolsheim, Erstein, Strasbourg, and Cronenbourg are respectively 106.1 ± 10.9, 121.2 ± 11.4, 114.4 ± 15.9, and 188.7 ± 68.5 µS cm^− 1. The reported values are almost identical to those observed in previous studies such as Kopisty in Czech Republic (171.9 µS cm^− 1) and Baton Rouge in USA (255 µS cm^− 1) (Fisak et al., 2002; Raja et al., 2008).

DOC levels at Geispolsheim, Erstein, Strasbourg, and Cronenbourg respectively vary between 17.4 and 44.9 ppm (mean of 29.5 ± 12.2 ppm), 16.3 and 35.4 ppm (mean of 25.2 ± 9.6 ppm), 13.0 and 15.5 ppm (mean of 14.3 ± 1.8 ppm), and 11.5 and 19.1 ppm (15.3 ± 5.4 ppm). There is a decrease in the average DOC concentrations at Geispolsheim (by 25%) and Erstein (by 30%) between 2015 and 2018, despite of the increase between 2016 and 2018 (by 34%). There is also a slight decrease at Strasbourg between 2016 and 2018 by 16%. However, DOC levels at Cronenbourg have increased by 40% between 2018 and 2021. There are mainly two reasons explaining the increasing trend: either the pollutant levels have increased in Alsace after 2018 (weather conditions, worse air quality, etc.) or the pollutant levels are affected by the COVID-19 period. For instance, France experienced the total confinement period for a period at which people stayed at home suggesting some additional anthropogenic activities such as more coal and wood burning for domestic/residential heating. The average DOC concentrations at suburban and rural sites are always found to be higher than those at the urban site. The highest DOC levels are obtained at Geispolsheim and Erstein, while Cronenbourg and Strasbourg have almost the same average of DOC levels. The mean DOC levels are lower than those observed in the Po Valley (62 ppm), but much higher than Delta Barrage (9.7 ppm), Houston (11.5 ppm), Mt. Eden (9 ppm), and Baton Rouge (6 ppm) (Raja et al., 2008; Straub et al., 2012; Salem et al., 2017). Besides, the DOCs at Cronenbourg and Strasbourg are also lower than those reported in Bakersfield (27 ppm) and Fresno (20 ppm). In contrast with Geispolsheim and Erstein whose DOCs vary in the same order of magnitude as those found in Bakersfield and Fresno (Ehrenhauser et al., 2012).

3.2. Inorganic analysis

Table S3.1 to S3.10 in the SI.3 show the results for the analysis ions and heavy metals for each fog sample.

3.2.1 Ions

Figure 2 illustrates the evolution of the total ionic concentration (TIC) (µEq L^− 1) at the different sites in Alsace. The highest mean TIC is obtained at Cronenbourg and Strasbourg with mean values respectively of 2164.7 and 2055.5 µEq L^− 1, followed by Geispolsheim and Erstein whose values are respectively 1720.1 and 1565.5 µEq L^− 1. The decreasing order of TIC is Cronenbourg > Strasbourg > Geispolsheim > Erstein, which is not consistent with that of the conductivity. The average TIC at Geispolsheim and Erstein has decreased between 2015 to 2018 respectively from 1893.4 to 1556.5 µEq L^− 1 (by 18%), and 1968.6 to 1305.6 µEq L^− 1 (by 34%). However, there is an increase in the TIC at Strasbourg between 2016 and 2018 from 1615.7 to 2495.2 µEq L^− 1 (by 54%), and Cronenbourg between 2018 and 2021 from 1785.8 to 2543.5 µEq L^− 1 (by 42%). Wet deposition can be one of the main reasons for the yearly trend in the TIC. It is also well known that temporal evolution of air pollutant loadings is very correlated with weather conditions (wind, relative humidity, and temperature), which lead either to their dispersion or accumulation in the ambient atmosphere. Differences in emissions could be also another factor responsible for the decrease/increase in the TIC (Lu et al., 2010; Cuhadaroglu and Demirci, 1997). In the current study, the ionic strength at Strasbourg is much lower than those reported previously (Millet et al., 1996; Herckes et al., 2002).

Figures 3 and 4 respectively show the evolution of individual anion and cation strengths (µEq L^− 1) at the four sampling locations over the sampling period.

The main cations found in fogwater samples are ammonium (\({\text{N}\text{H}}_{4}^{+}\)) and calcium (\({\text{C}\text{a}}^{2+}\)), while the dominant anions are nitrate (\({\text{N}\text{O}}_{3}^{-}\)) and (\({\text{S}\text{O}}_{4}^{2-}\)). For instance, the mean concentrations of \({\text{N}\text{H}}_{4}^{+}\), \({\text{C}\text{a}}^{2+}\), \({\text{N}\text{O}}_{3}^{-}\), and \({\text{S}\text{O}}_{4}^{2-}\) at Geispolsheim are respectively 582.2 ± 201.5, 272.6 ± 101.2, 264.7 ± 173.6, and 233.9 ± 123.9 µEq L^− 1. At Erstein, their mean concentrations are respectively 494 ± 197.4, 265.6 ± 182.4, 181.7 ± 138.3, and 182.3 ± 111.6 µEq L^− 1. At Strasbourg, their mean concentrations are respectively 1041.5 ± 285.8, 361.2 ± 353.7, 150.3 ± 107.9, and 181.1 ± 96.1 µEq L^− 1. At Cronenbourg, their mean concentrations are respectively 835.3 ± 265.9, 596.4 ± 87.2, 29.2 ± 9.2, and 111.7 ± 82.1 µEq L^− 1. \({\text{S}\text{O}}_{4}^{2-}\) and \({\text{N}\text{O}}_{3}^{-}\) account together for an average of 81%, 64%, 73%, and 66% of the total anion concentration respectively at Geispolsheim, Erstein, Strasbourg, and Cronenbourg. \({\text{N}\text{H}}_{4}^{+}\) and \({\text{C}\text{a}}^{2+}\) account together for an average of 74%, 72%, 82%, and 74% of the total cation concentration respectively at Geispolsheim, Erstein, Strasbourg, and Cronenbourg.

The highest concentrations of \({\text{C}\text{a}}^{2+}\) are obtained at Cronenbourg and Strasbourg, followed by Geispolsheim and Erstein. Its emissions may result from the mineral dust released from cement produced during the different construction activities and land erosion (renovation of Strasbourg University, construction of new buildings, etc.) as well as from sea water. The \({\text{n}\text{n}\text{s} \text{C}\text{a}}^{2+}\) is calculated using Eq. (1) (all concentrations are in µg L⁻¹).

\(\text{n}\text{s}\text{s} {\text{C}\text{a}}^{2+} ={\text{C}\text{a}}^{2+} -0.044\text{*}{\text{N}\text{a}}^{+}\) Eq. (1)

The results show that the mean ratios of \({\text{n}\text{n}\text{s}-\text{C}\text{a}}^{2+}\) to the total \({\text{C}\text{a}}^{2+}\) fraction at all sites are higher than 95%. This indicates that the contribution of \({\text{C}\text{a}}^{2+}\) from sea salts is negligible, since all sites are far from seas and oceans. It can be further emitted from the soil nature at Strasbourg and its vicinity composed of loess, which is very rich in \({\text{C}\text{a}}^{2+}\) involving fine dust particles that are easily spread by air currents (Millet et al., 1996). The concentration of \({\text{C}\text{a}}^{2+}\) has increased at Geispolsheim and Strasbourg, whereas it has decreased at Erstein and Cronenbourg over the sampling years.

The presence of \({\text{N}\text{H}}_{4}^{+}\) is directly linked to the input of ammonia (NH₃) into fog droplets especially those coming from agricultural activities and fertilizer industries, and indirectly associated to the input coming from NH₃ aerosols. The highest mean concentration of \({\text{N}\text{H}}_{4}^{+}\) is observed at Strasbourg, followed by Cronenbourg, Geispolsheim, and Erstein, which is inconsistent with the expected order. This suggests the probable effect of long-range transport (LRT) on pollutant loadings that leads to the higher \({\text{N}\text{H}}_{4}^{+}\) concentrations at the urban site than rural and suburban sites. There is a continuous increase in \({\text{N}\text{H}}_{4}^{+}\)concentrations at all locations during the sampling period, where agriculture becomes more and more important with time. For instance, \({\text{N}\text{H}}_{4}^{+}\) emissions have increased by 88%, 138%, 49%, and 59% respectively at Geispolsheim, Erstein, Strasbourg, and Cronenbourg.

Geispolsheim, which is a suburban site, has the highest \({\text{N}\text{O}}_{3}^{-}\) and \({\text{S}\text{O}}_{4}^{2-}\) concentrations even higher than those reported at the urban site Strasbourg. This could be attributed to the large consumption of coal, where coal burning is their primary energy source that releases \({\text{N}\text{O}}_{3}^{-}\) and \({\text{S}\text{O}}_{4}^{2-}\) (Shen et al. 2008; Zhang et al., 2015). The presence of \({\text{N}\text{O}}_{3}^{-}\) is further related to the direct input of gaseous HNO₃ released from vehicular exhaust, as well as to the indirect input resulted from \({\text{N}\text{O}}_{3}^{-}\) aerosol scavenging. \({\text{S}\text{O}}_{4}^{2-}\) is derived either from \({\text{S}\text{O}}_{4}^{2-}\) aerosol scavenging or in situ oxidation of its precursor gas, SO₂, released from the combustion of fossil fuels (Collett et al., 2002). The concentrations of \({\text{S}\text{O}}_{4}^{2-}\) at Geispolsheim, Strasbourg, and Cronenbourg vary within the same order during 2016 and 2018. Its concentration is mainly linked to some steel and aluminum factories in the industrial city, whose emissions can be transported by winds to other nearby regions. \({\text{S}\text{O}}_{4}^{2-}\) may have further emissions attributed to sea salts (marine contributions). The ratios of \({\text{S}\text{O}}_{4}^{2-}\) to \({\text{N}\text{a}}^{+}\) at Geispolsheim, Erstein, Strasbourg, and Cronenbourg are respectively 1.48 ± 1.19, 1.22 ± 1.04, 2.16 ± 2.28, which are all much higher than that of sea water (0.12) implying that \({\text{S}\text{O}}_{4}^{2-}\) does not originate from sea salt particles, and the marine contributions is, therefore, very weak or negligible. Thus, most of the \({\text{S}\text{O}}_{4}^{2-}\) originates from the direct input of SO₂ as well as its collection contained in aerosols. The average ratios of \({\text{N}\text{O}}_{3}^{-}\)to \({\text{S}\text{O}}_{4}^{2-}\) at Geispolsheim, Erstein, and Strasbourg are almost equal to unity, except at Cronenbourg. Their average ratios are respectively 1.00 ± 0.41, 0.86 ± 0.36, 0.79 ± 0.17, and 0.32 ± 0.16. This indicates that at most sampling sites the contribution of \({\text{S}\text{O}}_{4}^{2-}\) is almost the same as that of \({\text{N}\text{O}}_{3}^{-}\). Furthermore, the average ratios of \({\text{N}\text{O}}_{3}^{-}\)to \({\text{S}\text{O}}_{4}^{2-}\) have decreased over the sampling period proving that the concentrations of \({\text{S}\text{O}}_{4}^{2-}\) have gradually decreased. For instance, the average ratios of \({\text{N}\text{O}}_{3}^{-}\)to \({\text{S}\text{O}}_{4}^{2-}\) have decreased from 1.38 to 0.48 (by 65%), 1.04 to 0.42 (by 59%), 0.92 to 0.65 (by 30%), and 0.42 to 0.2 (by 52%) respectively at Geispolsheim, Erstein, Strasbourg, and Cronenbourg. The non-sea salt sulfate (nss \({\text{S}\text{O}}_{4}^{2-}\)) fraction is calculated using Eq. (2) (Morales et al., 1998; Lu et al., 2010; Watanabe et al., 2006; Warneck and Williams, 2012). All concentration units are given in µEq L⁻¹.

\(\text{n}\text{s}\text{s}{\text{S}\text{O}}_{4}^{2-}={\text{S}\text{O}}_{4}^{2-}-0.12\text{*} {\text{N}\text{a}}^{+}\) Eq. (2)

Other ions such as sodium (\({\text{N}\text{a}}^{+}\)) and chloride (\({\text{C}\text{l}}^{-}\)) are generally derived from droplet scavenging of sea salt, particularly in regions impacted by oceanic air masses. In addition to sea salts, \({\text{C}\text{l}}^{-}\) might derive from fossil fuel combustion, waste incineration, and vehicular emissions since gasoline contains lead bromo-chloride as an additive. However, the unleaded gasoline is banned in Europe, thus \({\text{C}\text{l}}^{-}\) emission released from leaded gasoline is not significant in the current study. The most probable emission source for \({\text{C}\text{l}}^{-}\) is the incinerator that is far almost 4 Km from Strasbourg. Other sampling sites might be also affected since the discharges are emitted in all directions around the incinerator (Millet et al., 1996). \({\text{C}\text{l}}^{-}\)can be further released from paper industries which use chloride in the vapor phase, but such factories are not present near our sampling sites. One another source of \({\text{N}\text{a}}^{+}\) is soil dust and biomass combustion used for cooking. The average ratios of \({\text{C}\text{l}}^{-}\) to \({\text{N}\text{a}}^{+}\) at Geispolsheim, Erstein, Strasbourg, and Cronenbourg are respectively 0.43 ± 0.21, 0.91 ± 0.42, 0.41 ± 0.13, and 0.24 ± 0.05 which are all lower than that in sea water (1.17) confirming the terrestrial origin of \({\text{N}\text{a}}^{+}\). Magnesium (\({\text{M}\text{g}}^{2+}\)), which is most frequently originated from sea salt as well as re-suspended road dust and long-range dust transport, is only detected in few samples taken during 2018 and 2021 at Strasbourg and Cronenbourg. However, it is not detected in any of the samples taken between 2015 and 2017.

The average non-sea salt fractions of \({\text{K}}^{+}\) (\({\text{n}\text{n}\text{s} \text{K}}^{+}\)) are calculated using Eq. (3). All concentrations are given in µEq L^− 1

\({\text{n}\text{n}\text{s} \text{K}}^{+}={\text{K}}^{+}-0.022\text{*}{\text{N}\text{a}}^{+}\) Eq. (3)

The average \({\text{n}\text{n}\text{s}-\text{K}}^{+}\) fractions at Geispolsheim, Erstein, Strasbourg, and Cronenbourg are found to be respectively 23.5%, 51.8%, 27.9%, and 23.7%. This indicates that it might have a marine contribution in addition to its terrestrial origin.

The neutralization factors (NFs) are calculated using Eq. (6) to determine the neutralization capacity for the basic components (\({\text{N}\text{H}}_{4}^{+}\), \({\text{C}\text{a}}^{2+}\), and \({\text{K}}^{+}\)) (Possanzini et al., 1988; Di Girolamo et al., 2014; Yadav and Kumar, 2014).

\(\text{N}\text{F}\left(\text{X}\right)= \frac{\left[{\text{n}\text{n}\text{s}-\text{X}}^{+}\right]}{\left[{\text{n}\text{s}\text{s}-\text{S}\text{O}}_{4}^{2-}\right]+\left[{\text{N}\text{O}}_{3}^{-}\right]}\) Eq. (6)

where “X” is the neutralizing cation and \({\text{n}\text{n}\text{s}-\text{X}}^{+}\) is its non-sea salt equivalent concentration.

The calculated NFs for \({\text{C}\text{a}}^{2+}\), \({\text{K}}^{+}\), and \({\text{N}\text{H}}_{4}^{+}\) at all sampling sites during all sampling years are shown in the Supplementary Information (SI.4) in Table S4.1. The highest NFs are obtained in 2018, where \({\text{S}\text{O}}_{4}^{2-}\) and \({\text{N}\text{O}}_{3}^{-}\) levels are the lowest. Same order of neutralization is observed during all sampling years \({\text{N}\text{H}}_{4, }^{+}{\text{C}\text{a}}^{2+}\), and \({\text{K}}^{+}\).

The acidifying potential (AP) and neutralizing potential (NP) are respectively calculated using Eqs. (7) and (8) (Tsuruta, 1989; Blaś et al., 2010).

\(\text{A}\text{P}=\text{n}\text{s}\text{s} {\text{S}\text{O}}_{4}^{2-}+{\text{N}\text{O}}_{3}^{-}\) Eq. (7)

\(\text{N}\text{P}=\text{n}\text{s}\text{s} {\text{C}\text{a}}^{2+}+{\text{N}\text{H}}_{4}^{+}\) Eq. (8)

The average AP, NP, and AP/NP at all sampling sites and years are shown in the Supplementary Information (SM4) in Table S4.2. The results shows that the NP is higher than the AP proving the effect of alkaline components toward the neutralization of the acidic species. The average \({\text{N}\text{H}}_{4}^{+}\) concentrations, in some of the samples, are lower than their corresponding AP values showing that \({\text{N}\text{H}}_{4}^{+}\) is not capable alone to neutralize the acidity. The average NP is lower than AP at Geispolsheim during 2015 suggesting that an unknown species might be responsible for the basic state. Moreover, many samples have an excess of \({\text{N}\text{H}}_{4}^{+}\) compared with AP which is responsible for the high pH values. Thus, fog water neutralization is mainly caused by both coarse particles and NH₃ scavenging. If the latter is the main process, \({\text{N}\text{H}}_{4}^{+}\) would be in excess. However, if the former process dominates, then \({\text{N}\text{H}}_{4}^{+}\) would be less than AP. In case \({\text{N}\text{H}}_{4}^{+}\) is in excess, it might also neutralize other anions such as organic acids (Lu et al., 2010).

3.2.2 Heavy metals

The results for the analysis of heavy metals at all sites are shown in the Supplementary Information (SI.5) from Table S5.1 to S5.5. Mn, Fe, Ni, Cu, and Zn are dominated in fog samples, whereas As, Cd, Cr, Pb, and Hg are detected at very low levels ranging from 0.6 to 7.7 µg L^− 1 accounting for less than 0.6%. The highest elemental strength is observed at Cronenbourg (4525.3 µg L^− 1), followed by Strasbourg (1819.7 µg L^− 1), Geispolsheim (1721.1 µg L^− 1), and Erstein (1553.1 µg L^− 1). The most two abundant elements are Zn and Ni accounting for more than 77%, and their mean concentration levels vary respectively in the range of 942.5–2084.9 µg L^− 1 (average of 1274.8 µg L^− 1) and 170.6–1312.8 µg L^− 1 (average of 566.9 µg L^− 1). Then it comes Cu (34% of the total fraction) whose mean concentration levels vary in the range of 174.2–639.1 µg L^− 1 (average of 328.5 µg L^− 1). Other metals like Al, Mn, and Fe account together for less 10% of the total elemental fraction, and their concentrations vary respectively in the range of 21.8–76.2 µg L^− 1 (average of 48.9 µg L^− 1), 38.4–171.8 µg L^− 1 (average of 91.5 µg L^− 1), and 23.3–217.1 µg L^− 1 (average of 80.5 µg L^− 1). The decreasing order of the five least metals detected in fog water is Hg, Cr, Pb, Cd, and As, whose average levels vary from 0.4 to 7.7 µg L^− 1. Those 5 heavy metals are known for their high toxicity to human health and environment. The low Pb concentrations can be explained by shifting to the use of unleaded fuels in France and surrounding regions since 1989.

Figure 5 shows the evolution of heavy metals concentration (µg L^− 1) at all sampling sites between 2015 and 2021. It shows that the elemental concentrations at Geispolsheim and Erstein have decreased between 2015 to 2018 respectively from 2758.7 to 1473.3 µg L^− 1 (by 53%) and from 2125.5 to 1200.9 µg L^− 1 (by 63%). However, there is an increase (almost 4 times) in the concentration levels at Strasbourg between 2016 and 2018 from 725.2 to 2914.3 µg L^− 1 (by 4 times), and Cronenbourg between 2018 and 2021 from 1894.7 to 7155.9 µg L^− 1 (by 4 times). Same observations are also obtained for the ionic strength.

The enrichment factor (EF) is calculated for the analyzed heavy metals, taking Iron (Fe) as the crustal reference using Eq. (9) (Tripathee et al., 2014; Islam et al., 2015).

\(\text{E}\text{F}=({\text{X}/\text{F}\text{e})}_{\text{f}\text{o}\text{g}}/({\text{X}/\text{F}\text{e})}_{\text{c}\text{r}\text{u}\text{s}\text{t}}\) Eq. (9)

The mean EFs for the analyzed elements at all sites are presented in Table 6. It shows high EFs (higher than 100) for Ni, Cu, Zn, Hg, As, and Cd. This indicates highly enriched conditions (human-made activities), except at Cronenbourg in which the EF for As is 40.1 (moderately enriched). The average EFs for Al and Cr are lower than 10 ranging respectively from 0.2 to 0.9, and 1.4 to 7.7, and thereby are considered to be non-enriched. The average EFs for Pb at all sites are all between 10 and 100, and are considered moderately enriched. Most of the EFs for Mn are lower than 10, which are considered non-enriched at all sampling sites, except at Strasbourg in which its EF is 37.5 (moderately enriched).

Table 6

Average EF values for the analyzed elements at the four locations.
	Al	Cr	Mn	Ni	Cu	Zn	Hg	As	Cd	Pb
Geispolsheim	0.8	1.6	7.7	773.2	1134.7	1911.5	1085.1	222.2	1611.3	12.4
Erstein	0.9	2.2	8.3	473.1	1082.4	2568.2	1013.3	137.5	1711.5	48.6
Strasbourg	0.7	7.7	37.5	1882.3	2639.6	3501.6	3004.8	218.0	4495.6	20.7
Cronenbourg	0.2	1.4	6.2	608.2	663.3	832.2	412.2	40.1	1002.7	11.3

The concentration levels found in the current research vary within the same range as those observed in Riverside (California) (Munger et al., 1983), New Delhi (India) (Ali et al., 2004), and Po Valley (Italy) (Gelencser et al., 2000), but lower than those observed in Baton Rouge (Louisiana) (Raja et al., 2005), Milesovka (Czech) (Fisak et al., 2009), Delta Barrage (Egypt) (Salem et al., 2017), and Coastal Island (Bangladesh) (Nahar et al., 2022). Additionally, the elemental concentration levels of heavy metals reported at Strasbourg are also lower than those found previously by Millet et al. (1996) at the same site.

3.3. Pearson correlation

Pearson correlation coefficients for fogwater quality data is shown in Fig. 6. The correlation analysis shows a reasonable significant relationship among different chemical parameters such as \({\text{C}\text{l}}^{-}\)- \({\text{N}\text{a}}^{+}\), \({\text{S}\text{O}}_{4}^{2-}\)-\({ \text{N}\text{O}}_{3}^{-}\), Mn -\({\text{C}\text{a}}^{2+}\), Zn -\({ \text{C}\text{l}}^{-}\), heavy metals - \({\text{N}\text{a}}^{+}\), heavy metals - \({\text{K}}^{+}\), and heavy metals - \({\text{N}\text{H}}_{4}^{+}\). The good correlation (0.78) observed between \({\text{C}\text{l}}^{-}\) and \({\text{N}\text{a}}^{+}\)suggests that a part of them is originated from marine sources, which is mainly transported by different air masses. The good correlation between \({\text{S}\text{O}}_{4}^{2-}\)and\({ \text{N}\text{O}}_{3}^{-}\) (0.83) suggests that both originates from the same source mainly anthropogenic. The intercorrelations among the heavy metals themselves show that they share the same pollution source (a mixture of anthropogenic and natural). Weak correlation is found between heavy metals with \({\text{N}\text{H}}_{4}^{+}\) and \({\text{K}}^{+}\), whereas that found with \({\text{N}\text{a}}^{+}\)is stronger.

3.4. Principal Component Analysis (PCA)

The emission sources are further assessed based on the principal component analysis (PCA). The eigenvalues for the first three principal components (PCs) and their cumulative variance (%) are shown in Table 3.

Table 3

Eigen values for the first three PCs.
PC (or eigenvector)	1	2	3
Eigenvalue	6.13	2.06	1.67
% Variance	47.17	15.81	12.85
% Cumulative variance	47.17	62.98	75.83

PC1 (62.9%) and PC2 (15.8%) representing about 62.98% of the total variance (shown in Fig. 7) are the key factors for controlling fog chemistry. All variables, except \({\text{C}\text{a}}^{2+}\)and \({\text{N}\text{H}}_{4}^{+}\), are well represented on the plan defined by the first two PCs with communality values varying from 0.57 to 0.97. The first eigenvector is positively correlated with \({\text{N}\text{H}}_{4}^{+}\), \({\text{C}\text{a}}^{2+}\), \({\text{N}\text{a}}^{+}\), \({\text{K}}^{+}\), Zn, Cu, Cr, Mn, Ni, and Fe, whereas the second one is positively correlated with \({\text{S}\text{O}}_{4}^{2-}\), \({\text{C}\text{l}}^{-}\), and \({\text{N}\text{O}}_{3}^{-}\). Grouping of variables (\({{\text{C}\text{l}}^{-}, \text{S}\text{O}}_{4}^{2-}\), and \({\text{N}\text{O}}_{3}^{-}\); \({\text{N}\text{a}}^{+}\), \({\text{K}}^{+}\), and Zn; and Cu, Cr, Mn, Ni, and Fe) in the loading plot indicates their mutual positive relationship. The major emission source of \({\text{S}\text{O}}_{4}^{2-}\), \({\text{C}\text{l}}^{-}\), and \({\text{N}\text{O}}_{3}^{-}\) is the oxidation of their precursors from combustion sources originating from anthropogenic activities (mainly from vehicular transport and industries). The correlation between \({\text{N}\text{a}}^{+}\)and \({\text{K}}^{+}\)proves that a significant part of \({\text{K}}^{+}\)results from natural origin (sea salt). \({\text{N}\text{H}}_{4}^{+}\) seems to have a unique anthropogenic source resulting from the use of fertilizers in the agriculture activities. The strong correlations among heavy metals themselves prove that they all are well originated from mixed sources including anthropogenic (industries, combustion, etc.) and natural (soil and sea water).

A comprehensive fog experiment in the Alsace region is conduced successfully between 2015 and 2021 at four sites: Strasbourg, Geispolsheim, Erstein, and Cronenbourg. aimed to assess the evolution of fogwater chemistry. Such analyses are interesting due to the lack of fog studies in this region since 2000. For this purpose, a total of forty-two radiation fog samples are collected and analyzed for their major inorganic ions, heavy metals, and physico-chemical properties. The investigations show that the pH nature has changed over time from acidic to basic. This found to be correlated with the decrease in sulfate and nitrate (around 20 times) and the increase in ammonium (around 3 times). The main ions found at all sites are \({\text{N}\text{H}}_{4}^{+}\), \({\text{C}\text{a}}^{2+}\), \({\text{N}\text{O}}_{3}^{-}\), and \({\text{S}\text{O}}_{4}^{2-}\). The marine contribution to \({\text{C}\text{a}}^{2+}\)and \({\text{M}\text{g}}^{2+}\) is found to be negligible, whereas that to \({\text{S}\text{O}}_{4}^{2-}\) is weaker and that of \({\text{K}}^{+}\) is higher. The total inorganic concentration (TIC) has decreased between 2015 and 2018 at Geispolsheim and Erstein by 18% and 34%, respectively, whereas it has increased at Strasbourg (2015–2018) and Cronenbourg (2018–2021) by 54% and 42%, respectively. Same observations are also obtained for the heavy metals. A decrease by 53% and 63% in the total elemental concentration at Geispolsheim and Erstein, and an increase (around 4 times) at Strasbourg and Cronenbourg. The two dominant elements found at all sites are Zn and Ni which account together for an average of 77% of the total elemental fraction. The principal component analysis (PCA) and Pearson correlation matrix for all variables show that a mixture of different anthropogenic and natural sources in the region controls fogwater chemistry.

Ethical responsibilities of authors

All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors.

Credit authorship contribution statement

Dani Khoury and Olivier Delhomme collected the samples; Dani Khoury, Yasmine Jabali, Olivier Delhomme, and Thomas Weissenberger analyzed the samples; Dani Khoury wrote the original manuscript. Maurice Millet, Yasmine Jabali, and Olivier Delhomme supervised, reviewed, and edited the manuscript.

Declaration of Competing Interest

The authors declare that they have no known competing interest or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

The dataset used for this study is available upon request to the corresponding author.

Funding Declaration

Not applicable

Acknowledgements

We gratefully acknowledge the University of Strasbourg and the University of Balamand, in particular the Institute for Chemistry and Processes for Energy, Environment and Health (ICPEES) and Environmental Engineering laboratory (EEL) for providing me all required materials and equipment for the good of this work.

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Evolution of the chemical composition of fogwater collected at four sites in the Alsace region between 2015 and 2021

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Abstract

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1. Introduction

2. Experimental

2.1. Sites description

2.2. Analysis protocol

2.3. Statistical analysis

3. Results and discussion

3.1. Physical parameters

3.2. Inorganic analysis

3.2.1 Ions

3.2.2 Heavy metals

3.3. Pearson correlation

3.4. Principal Component Analysis (PCA)

4. Conclusions and Recommendations

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References

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