Inorganic and organic pollutants in the snow cover of the northern city

ABSTRACT Snow cover is a good indicator of air pollution and accumulates trace elements and organic pollutants. At the same time, the analysis of snow cover is simple and allows you to assess the presence of these pollutants in the atmosphere. We have studied the snow cover of an urban agglomeration located in the northern part of Europe, with a large number of inhabitants, and therefore with a large anthropogenic load on the atmosphere. We have identified trace elements in the snow cover at many city crossroads. Also we determined the presence of PAHs as the main organic pollutants that are typical for urban agglomerations. Inorganic pollutants were detected in all samples. We found that trace elements contamination advised 1 to 5 according to Nemerow index (PiNemerow). In 50% of the samples, the contamination index corresponded to type V (heavy pollution); 30% to type III and 20% to type IV, respectively. We also determined PAHs in the same places. We can conclude that the values of the investigated substances are low throughout the city. About half of PAHs come from the combustion of wood, the other from the combustion of petroleum products. Since different sources prevail at different sampling points, therefore, it can be assumed about anthropogenic sources, which is also confirmed by the HMW/LMW ratio. No correlations we were found between heavy PAH and Trace elements, no associations were found.


Introduction
With the aim of studying the anthropogenic impact on the atmospheric air, both organic and inorganic contaminants are currently being determined [1,2].One of the tools for assessing air pollution can be the study of snow cover, as a good deposition matrix for many pollutants [ 3-8 ].Many authors believe that the snow cover serves as a good depositing matrix not only for moving elements, but also for organic pollutants, since snow pollution correlates with the general air quality index and the level of atmospheric pollution [3,9,10].
Since the middle of the 20th century, the volume of emissions of many inorganic elements belonging to the group of heavy metals in the composition of pollutants of anthropogenic origin exceeds the scale of natural processes of their migration and accumulation [1,2].The accumulation and transformation of chemicals in the snow cover is known to have an impact on groundwater and terrestrial environments.The impact of chemical pollution of the atmosphere, snow, water, and soil is felt not only in the immediate vicinity of large industrial enterprises, but also at a considerable distance from them from 1 to tens of kilometres [3,4,11].
Intense motorisation is currently contributing to the emergence of new problems that require solutions when organising environmental monitoring in large cities [12,13].Studies have shown that the real load from road transport currently exceeded urban planning calculations performed in the middle of the 20th century [13,14].
Pollution of cities and industrial regions is rarely mono-element, usually it is multi-element.Multi-elemental pollution is estimated through the indices of total exposure to pollutants.Until the problem of the interaction of several heavy metals and metalloids has been resolved, the researchers have taken the path of formally calculating various coefficients of total pollution, which are based on a number of assumptions [5,15].A significant number of works have been devoted to the total pollution by heavy metals and metalloids [1,3,16].
Determination of the content of heavy metals is carried out by various methods, for example, atomic adsorption spectroscopy (AAS) [17]; inductively coupled plasma atomic emission spectroscopy (ICP-OES) [9]; ion chromatography method [10]; inductively coupled plasma mass spectrometry (ICP-MS) [18].In the present study, we used X-ray fluorescence analysis of total external reflection (TXRF).This method is highly reproducible, and its sensitivity is comparable to ICP-OES и FAAS, slightly inferior ICP-MS and ETAAS.TXRF is considered the most effective for detecting small amounts of elements with atomic numbers above 20 [19].This method makes it possible to simultaneously determine the content of 20 . . .30 elements in a sample with a volume of less than 1 millilitre with a minimum number of consumables.The study of organic pollutants is much more difficult task due to the large number of different pollutants.One of the priority class of such pollutants is polyaromatic hydrocarbons (PAHs) [18,[20][21][22].They are included in the group of priority pollutants, the most dangerous for human health and natural ecosystems due to their high mutagenic, teratogenic and carcinogenic activity.The interaction of PAHs with animals and humans during respiration and physical contact can cause dangerous effects (disruption of the reproductive and endocrine systems, neurotoxicity and oxidative stress).It should be noted that the accumulation of PAHs in living organisms increases their toxic effect [17,18].
Currently, Russia has a system of sanitary and hygienic monitoring with an extremely small list of pollutants, and this system differs significantly from the systems of other countries [23][24][25].At the same time, the US uses a list of 16 priority PAHs containing from 2 to 6 carbon rings in their structure.For example, only 2 PAHs are regulated in Russia: benz[a]pyrene and naphthalene.The Environmental Protection Agency (EPA) establishes requirements for the control of PAHs such as benz [26][27][28][29][30][31].Recently, popular methods used to determine polyaromatic hydrocarbons in various samples are high performance liquid chromatography tandem mass spectrometry; HPLC coupled with a fluorimetric detector; GC-MS/MS [32][33][34].
The aim of this study was to detect the contents of heavy metals and PAHs, as well as the relationships between them in the snow cover of northern urban agglomerations using the example of Arkhangelsk as the largest city in the world above 64 north.

Field of study
The study area was Arkhangelsk, which is the largest urban agglomeration in the North of Europe (64 ° 32 ' north, 40 ° 31 ' east).The population is about 350,000 people.The main sources of environmental pollution are a large number of vehicles (> 144,000).The snow cover in Arkhangelsk is formed in October and persists until May.Thus, snow in Arkhangelsk should absorb pollutants for a long period of time.In addition, the city is known as one of the industrial centres of Russia with a developed pulp and paper industry, shipbuilding, electricity and transport.The large seaport is located in the city centre.The annual emission of all controlled atmospheric pollutants from the territory of the Arkhangelsk region is about 250,000 tons: 59% -stationary sources, 41% -transport.The State Service of Russia determines some pollutants in the air.Such as benz(a)pyrene, black carbon and others.Concentrations of these substances are usually below the established standards in Russia [35].

Sampling strategy
Snow sampling was carried out using a cylindrical sampler 10 cm in diameter at most intersections in Arkhangelsk.The sampling date was 13 January 2020, the temperature and humidity were −13°C and 66%, respectively.There was no atmospheric precipitation for 5 days before sampling, while the monthly amount of precipitation was 22-48 mm, which corresponds to 63-97% of the norm.The average height of the snow cover was 15 cm.We placed the collected snow samples in special 1-litre dark glass bottles and thawed them at room temperature.The glass container was preliminarily prepared by washing with nitric acid and deionised water.Snow sampling locations are presented on Figure 1.

TXRF analysis
After melting snow samples were immediately filtered through a Blue Ribbon filter paper and acidified with concentrated nitric acid to pH < 2. Addition of acid in the sample was used to prevent the hydrolysis and to transfer metals from colloidal to ionic form.High purity nitric acid was additionally purified by Rayleigh distillation on a Savillex DST-1000 apparatus.The concentration of metals was determined on an S2 Picofox spectrometer using the internal standard method.We mixed an aliquot of the sample (0.100 cm 3 ) with an equal volume of an internal standard (Ga) solution with a concentration of 500 μg/dm 3 in a 1.5 cm 3 microcentrifuge tube using an IKA MS3 Digital shaker, stirring duration -60s, frequency -1500 min −1 .An internal standard solution was prepared by diluting a standard gallium solution for ICP (concentration 1.000 ± 0.002 g/dm 3 ), Panreac (Reference standard acc.NIST SRM 3119a).We considered the results of the analysis of the blank sample (Bkg) when calculating the concentration of metals.A blank sample was deionised water obtained using a Simplicity UV ultrapure water preparation unit, acidified similarly to snow samples.
The TXRF analysis method was carried out using an X-ray fluorescence spectrometer S2 Picofox (Bruker, Germany) in a modification with a highly efficient module and automatic loading of samples for determining the concentration of trace elements.An X-ray tube served as an excitation source with a maximum power of 37 W (50 kV, 750 μA) with a Moanode, equipped with a Ni/C multilayer monochromator (energy 17.5 keV).We used a thermoelectric cooled silicon drift detector with an area of 30 mm 2 .The maximum count rate exceeded 100,000 counts/s.The energy resolution was <150 eV for the MnKα line.We have performed a search for the maximum number of elements that can be determined using this tool.However, concentrations of some elements (cobalt, arsenic, cadmium, mercury, thallium, bismuth) they were below the detection limit.Unsatisfactory statistics were obtained for a number of other elements (sodium, magnesium, sulphur, chlorine, bromine).Therefore, in our study we evaluated the content of only K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr, Ba, Pb.

Assessing the impact of trace elements
Based on the results obtained, we calculated the Sum of contamination (total contamination index) (PI sum ) and the Nemerow pollution index (PI Nemerow ) for trace elements for all selected samples.We considered the contents of elements as Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr, Pb without K, Ca, and Ba because of its negative impact on the soil.The correlation with the soil pollution classes was made, since the elements accumulated in the snow can be transferred to the soil during the melting of the snow.Proceeding from this.we considered it expedient to compare with the classes of soil contamination.
To calculate the Sum of contamination index.we used the formula [15]: The Nemerow pollution index was calculated using the following formula:

GC MS analysis
We took a 500 ml sample of melt water after defrosting.Extraction of PAHs was carried out by adding 10 ml of hexane (Cryochrome, Russia) and exposure for 20 min with vigorous stirring using an automatic shaker (LabTech, Italy).We separated the hexane extract from water by pouring it into a glass flask and evaporating at 40°C in a nitrogen flow to a volume of 1 ml.The extract was transferred quantitatively into a 1.5 ml vial.We carried out the determination of PAHs using an Agilent 7890A gas chromatography system equipped with an Agilent 7000 MS/MS series triple quadrupole system (Agilent, USA).An Agilent GC column (DB-XLB, 30 m x 0.250 mm x 0.1 x μm) was used to separate PAHs.Samples, 1 μL were injected using a multi-mode injector with pulsed mode without separation (injection pulse pressure of 50 psi up to 0.9 min, purge flow to separation of 30 ml/min at 0.75 min), glass wool frit (Agilent 5190-2293) was used.
The injector temperature was 300°C.The rate of collision and quench gas flows was 1.5 ml min −1 .We used helium as a carrier gas and a quenching gas, and nitrogen as a collision gas.The oven temperature programme was as follows: the sample was heated to 50°C for 3 min; thereafter, the sample was heated to 150°C at a rate of 40°C per minute; further, the sample was heated to 280°C at a rate of 15°C per minute.This temperature regime was maintained for 2 minutes, and then the sample was heated to 340°C at a rate of 40°C per minute.The specified temperature regime was maintained for 3 min.The total run time was 20.7 minutes with 1 additional minute for backflash at 340°C.A constant pressure mode (25 psi) was used.The mass spectrometer was operated in the electron ionisation (EI) mode (70 eV).The temperature of the transmission line and the temperature of the ion source were maintained at 320°C.
For quantitative GC MS Analysis, we used a multistandard (Supelco, Bellefonte, PA, USA), which contained known amounts of 18 basic PAHs (16 priority PAHs and 2 alkylated naphthalene derivatives, which are more hazardous than naphthalene).The multistandard includes: Naphthalene (Nap); Pyrene (Pyr); 2-Methylnaphtalene (2-MNap); Benzo For compounds benzo[a]anthracene and chrysene, their total amount (B[a]A + Chr) was determined, due to the impossibility of chromatographic separation of peaks at such a low concentration level.We did the same with the quantitative determination of benzo As internal standards, we used acenaphthylene-d8, benzo[g,h,i]perylene-d12, fluoranthene-d10, naphthalene-d8, phenanthrene-d10, pyrene-d10 (from Sigma Aldrich, Germany).The accuracy of the determination was verified by the addition method.
The graded dependences of each PAH were constructed for quantitative analysis using the prepared multistandard.
Acetonitrile UV-IR-HPLC-gradient (Cryochrome, Moscow, Russia) was used to prepare samples and standard solutions, as well as a component of the mobile phase in chromatographic analysis.High purity water was obtained using a Milli-Q system (Millipore, Molsheim, France).

Assessment of the impact of PAHs and sources of occurrence
We calculated the equivalence of toxicity at each sampling point using the formula: This formula considers the contribution of each PAH to the total toxicity of the most dangerous compound B[a]P.The contribution of other PAHs (Ci) was calculated according to the coefficients: Nap (0.001), 2-MNap (0.001), 1-MNap (0.001), Acy (0.001), Ace (0.001), Flu (0.001), Phe (0.001), Ant (0.01), Flt (0.

Statistical analysis
For the statistical analysis, we used the IBM SPSS STATISTICS Version 23 software.We performed regression statistics, calculated the mean deviation between the values of the concentrations of each elements and PAHs.Coupled correlation coefficients (r) at specific significance level (p ≤ 0.05) was calculated.We found statistical relationships both between the concentrations of individual elements and between the concentrations of elements and PAHs.

Inorganic pollutants
During the TXRF analysis method, the concentrations of the studied elements were determined in the snow samples, presented in Table 1.
The highest concentrations were observed for elements that cannot be classified as heavy metals, such as K and Ca.It is noted that in all samples, the values of manganese concentration were observed in the range from 13.2 μg/L to 45.1 μg/L.The results obtained were significantly higher than the background value (Bkg = 2.8 μg/L).
The Pb content was the lowest in the samples.It ranged from 0.6 to 2.4 μg/L.Also, the lead content was below the detection limit at most sampling points.Point 7 corresponded to the maximum value of the Ba concentration, which was 99.8 μg/L.A value that did not differ from the background (23.Determination of zinc content in samples showed that at most sampling points the concentration did not significantly exceed Bkg (8.6 μg/L), however, a huge difference was noted at two points.At point No 11, the concentration of Zn was 603 µg/L, and at point No 10, 480 µg/L.
The chromium content in the analysed samples was at the background level (Bkg = 5.1 µg/L), except for one point, at which the content was 16.5 µg/L (sample No 7).
The vanadium concentration in many samples did not differ from the background values (points 1, 2, 5, 7, 10, and 11) and corresponded to 0.6 µg/L.However, at several points, the V content reached a level of 7.9 μg/L.Such points included No 14 (7.9 µg/L), as well as No 3 and 13 (5.7 µg/L).
As a result of the correlation analysis (Figure 2 and table S1), we observed correlations between the elements chromium and potassium, manganese and calcium, manganese and chromium, zinc and nickel, barium and potassium, lead, and iron.The revealed correlations can serve as an indicator of the general origin of these pairs of elements in the environment.Other researchers note that correlations between concentrations of elements in different environmental objects indicate their common source [36,37].However, low concentrations of elements, as well as a small number of correlation pairs, indicate the natural origin of these elements.In addition, the same is evidenced by the lack of correlation for the elements accompanying anthropogenic activity.Such as zinc (one correlation pair), nickel (no correlation pairs), lead (one correlation pair).
It can also be noted that the elements are divided into groups according to the correlations between their content.These are three groups of elements which include: Cu, Ni, Zn (1 group); K, Ka, Sr, Cr, Ba (2 group); Fe, Pb, Ti (3 group).Thus, this indicates that these groups have different origins.
However, it is correct to assess the possible pollution not through the analysis of individual heavy metals, but as the sum of their mutual influence.The calculated pollution factors are presented in Table 2.The obtained values were correlated with the classes of soil contamination [15].
If we evaluate the pollution of the snow cover by individual heavy metals, we will not get objective data on the possible impact on the environment.Concentration of each individual element has a weak impact on the environment, but their combined impact is significant.When determining the classes of pollution, such points as No 4,6,7,8,10,11,12, and 13 refer to the V class of pollution and correspond to Quality of soil -Heavy pollution.The maximum value of Pi Nemerow is observed at location No 4 (26.67).Additionally, points 2, 5, 14 belong to the IV class, which is classified as Moderate pollution.The maximum among them is noted at point 14 (2.73).The remaining places No 1, 3, 9, and 15 have a coefficient ranging from 1.01 to 1.89, which corresponds to III (Slight pollution) class.
It is noteworthy that not a single place near the main intersections of the city of Arkhangelsk can be attributed to I (Clear) or even II (Warning limit) class.Thus, we can conclude that the snow cover of the city of Arkhangelsk is subject to significant pollution trace elements.When comparing the results obtained with 2020, carried out by us earlier [31], to identify the pollution class, unfavourable dynamics is observed.Class deterioration was detected at almost all sampling points.The largest increase in pollution was found to be points 4, 6, 7, 11, and 13, in which the pollution class rose from I to V. At points No 2, 5, and 14, the studied indicator increased from I to IV class.At the same time, point No 9 became an exception, the indicator of which decreased from V to IV class.In comparison with 2020, the pollution index has increased.This may be due to both the general deterioration of the environmental pollution situation and the sampling features in 2020 and 2021.

Organic pollutants
In addition to the content of heavy metals in the atmosphere of urban agglomerations, there are significant amounts PAHs, which are formed because of the combustion of various types of fuel, such as combustion of fuel in internal combustion engines, during the combustion of fuel in a heat and power plant, as well as in individual boiler plants and other industries that are abundant in Arkhangelsk.In Arkhangelsk, there is a high automobile traffic, which can affect the content of the compounds under study, both in the atmosphere and in the snow cover, which serves as a good deposition matrix for atmospheric pollution.In addition, Arkhangelsk has an extremely long heating season due to its climatic features.Natural gas combustion at a central thermal power plant is used to heat houses.In addition, there are several boiler houses in Arkhangelsk that run on various types of fuel (for example, wood pallets, fuel oil), and stove heating is not uncommon in the city.The Arkhangelsk Pulp and Paper Mill operates not far from Arkhangelsk, which processes 3.4 million m 3 of wood per year into pulp and paper.All lignin formed in the technological cycle goes to combustion in order to extract heat energy, which can also lead to the formation of PAHs [27].
We analysed the content of 18 PAHs (table S2), 16 of which were identified by the US EPA as priority compounds.Two additional compounds were selected as potentially more hazardous, being alkylated PAHs.The content of naphthalene in most cases was below LOQ, but at several points, the content reached 2.63 ng/kg, 3.65 ng/kg, and 3.85 ng/kg at points 2, 8, 10, respectively.The content of alkylated naphthalene derivatives was below the detection limit, except for 1-MNap at point No 2 (2.51 ng/kg).Significant concentrations of Acy were at points 5 (2.48 ng/kg) and 15 (3.14 ng/kg).PAHs such as Ace, Flu, and Ant were also extremely low and below the detection limit.Phenanthrene was detected at several points (No 6, 10, 12, and 15).The maximum concentration was 6.35 ng/kg, and the minimum is 3.07 ng/kg.Significantly higher concentrations of Flt were observed, which ranged from 3.50 ng/kg to 54.00 ng/kg, with the exception of points 1, 4, 7, 11, 13, and 14 (contents below the detection limit).The presence of pyrene was found at all points, with a maximum of 123.60 ng/kg at sampling point No The total concentration of benzo[b]fluoranthene and benzo[k]fluoranthene was observed in the range of 4.00 ng/kg (point No 6) to 39.00 ng/kg (point No 15), with an average of 10.97 ng/kg.Dibenzo[a,h]anthracene was not detected in all samples.In addition, Indeno[123-cd]pyrene was not found in most samples.The exception was point No 15, where its concentration was 10.00 ng/kg.The content of benzo[g,h,i] perylene at points 3, 6, and 9 did not exceed the limit of detection.However, at the rest of the sampling points, this hydrocarbon varied in concentration from 2.00 ng/kg (point No 10) to 18.00 ng/kg (point No 5).
Based on the obtained results, the total concentration of PAHs (Sum) was calculated.The lowest total concentration was determined at point No 1 (29.50 ng/kg) and the maximum -at point No 5 (189.94ng/kg).
In general, the determination of the total concentration of PAHs is not correct, since different PAHs have different toxic properties.Therefore, it is accepted to calculate the toxic equivalence (Table 3).TEQ data are presented in Figure 1 along with sampling locations.
It should be noted that TEQ is extremely low for benzo[a]pyrene (maximum permissible concentration (MPC) = 0.02 mg/kg) and is 0.022% of MPC in soil on average and reaches a maximum of 0.125% of MPC at point No 15.
We investigated the ratio of high molecular weight PAHs to low molecular weight PAHs (HMW/ LMW) The high values of this ratio indicate a high proportion of petrogenic compounds, while lower values indicate a larger percentage of PAHs burned.Ours values of PAHs attained 10, which was considerably higher than > 1 and mainly implied the pyrogenic sources of PAH inputs [18].As lower molecular weight PAHs (like phenanthrene, anthracene, and pyrene) dominate the higher molecular weight PAHs during low temperature maturation of organic matter.These ratios indicate that these three stations were contaminated mainly by petrogenic PAHs.It is known that the ratio Flu/(Flu + Pyr) is a marker for compounds with a molecular weight of 202.Its value < 0.4 is an indicator of oil supply as a source; values 0.4-0.5 are indicators of burning liquid fossil fuels, and a value > 0.5 is an indicator of burning coal/ grass/forest (wood).
In this regard, we can assume various sources of PAH input, such as the burning of liquid fossil fuels/coal, wood, or grass [18].
Indicators (Pyr + B[a]P)/(Phe + Chr) turned out to be either close or greater than one, which means anthropogenic origin.The Flu/(Flu + Pyr) indicates that it came from different sources.About half of the PAHs from sampling sites originated from the combustion of wood, the other half from the combustion of oil and its refined products.Due to the low quantities, different sources predominate at different points.The HMW/ LMW ratio also speaks of the anthropogenic origin.
We tried to find correlations between the content of heavy metals and PAHs (table S3).However, we did not observe any significant correlations.At the same time, noting the sources of combustion as the source of PAHs, we can conclude that the elements have a natural, not anthropogenic source.
At the same time, we observed correlations between heavy PAHs, which have a large molecular weight, and are formed because of anthropogenic activity.As a result of the correlation analysis, we observed several links between heavy polyaromatic hydrocarbons: benzo

Conclusions
Determination of trace elements in the snow makes it possible to judge the class of pollution.Based on the results obtained, it can be concluded that most of the sampling points belong to the V class of pollution.They meet Quality of soil -Heavy pollution.Several points (No 2, 5, and 14) belong to the IV class (Moderate pollution), and points (No 1, 3, 9, and 15) -to the III class (Slight pollution).During the work, no points were found that would correspond to I (Clear) or II (Warning limit) pollution class according to Nemerow.
Comparison of the results for the class of snow pollution with similar results in 2020 allows us to judge that in the territory of the city of Arkhangelsk there is a significant deterioration in the situation with pollution of snow, and, accordingly, soil and atmosphere.
Analysing the content of PAHs in the snow, we can conclude that the values of the investigated substances are low throughout the city.After calculating indicators such as (Pyr + B[a]P)/(Phe + Chr), HMW/LMW, Flt/(Flt + Pyr), we identified their sources.About half of PAHs come from the combustion of wood, the other from the combustion of petroleum products.Since different sources prevail at different sampling points, therefore, it can be assumed about anthropogenic sources, which is also confirmed by the HMW/LMW ratio.
When determining correlations according to Pearson's criterion between heavy PAH and Trace elements, no associations were found.This indicates the natural origin of Trace elements.Revealing correlations between heavy PAHs also allows us to judge about their anthropogenic source.
Values range from 520 (point No 2) to 4901 µg/L (point No 7) and from 1164 (point No 2) to 27,241 µg/L (point No 7) (K and Ca, respectively).It is noteworthy that for these elements the minimum and maximum values correspond to the same points (point's No 2 and No 7).In addition, high Fe concentration have been found.Its values significantly exceeded background values at all sampling points.The maximum was observed at point No 4 (776.0µg/L) and the minimum is at point 8 (41.5 µg/L).
2 µg/L) was recorded at point No 9.A significant excess of Bkg values in the Ti content was observed at points No 4 (19.2 μg/L), No 12 (17.1 μg/L), and No 6 (7.3 μg/L).No obvious differences in titanium content were found in the rest of the samples.The strontium concentration in all samples exceeded the background values.The maximum Sr concentration matched to 123.0 µg/L (point No 7), and the minimumto 4.9 µg/L.It should be noted that the contents of Ni and Cu differed slightly from the background values, however, both elements had concentration peaks at point 11.The concentration of Ni was 9.2 µg/L, and the concentration of Cu was 28.4 µg/L.

Figure 2 .
Figure 2. Analysis of bilateral correlations between elements in the snow of Arkhangelsk (correlation analysis according to Pearson).Legend: * straight thick arrows -correlation is significant at the level of p ≤ 0.01; dashed arrows -correlation is significant at the level p ≤ 0.05.Correlation values are indicated in brackets.
5 and a minimum at point No 2 of 3.60 ng/kg.The total values for benzo [a] anthracene + chrysene ranged from 3.00 ng/kg (No 6) to 23.20 ng/kg (No 15).The exception was point No 5, where the content was below the detection limit.The maximum concentration for the PAH pair benzo[b]fluoranthene + benzo[k]fluoranthene was 39.00 ng/kg (point No 15), and the minimum was 4.00 ng/kg (No 6).

Figure 3 .
Figure 3. Analysis of two-way correlations between heavy PAHs in the snow of Arkhangelsk (Pearson correlation analysis).Legend: * straight thick arrows -correlation is significant at the level of p ≤ 0.01; dotted arrows -correlation is significant at the p ≤ 0.05 level.Correlation values are indicated in brackets.

Table 1 .
Element concentrations in snow samples in 2021.

Table 3 .
The toxic equivalence and PAH ratios for source identification.