Dioxins
Dioxins mean concentrations in reindeer liver and meat depending on sampling place location are presented in Table 2. Mean concentrations depending on region, including values of standard deviation and concentrations ranges in 95% Confidence Intervals are shown in Table 3.
Table 2. Dioxins concentrations in reindeer liver and meat depending on sampling place location
Region
|
Sampling place
|
Latitude, DMS
|
Longitude, DMS
|
Mean LB, ng WHO-TEQ/kg of fat
|
Mean UB, ng WHO-TEQ/kg of fat
|
Range, ng WHO-TEQ/kg of fat
|
N of samples
|
Liver samples
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
40.7
|
40.7
|
11.6-118.5
|
34
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
28.3
|
28.3
|
6.8-49.2
|
91
|
Nenets autonomous okrug
|
Mgla, Zapolyarni district
|
66.498855
|
44.449269
|
76.5
|
76.5
|
76.48
|
1
|
Nes', Zapoliarni district
|
66.600876
|
44.678905
|
31.7
|
31.7
|
12.9-59.0
|
23
|
Oma, Zapolyarni district
|
66.641769
|
46.492496
|
31.4
|
31.4
|
21.0-36.4
|
8
|
Verhniaia Pesha, Zapolyarni district
|
66.609449
|
47.953301
|
26.9
|
26.9
|
20.6-32.8
|
5
|
Indiga, Zapolyarni district
|
67.655217
|
49.037136
|
30.1
|
30.1
|
17.2-54.3
|
16
|
Khongurey, Zapoliarni district
|
67.557642
|
51.955412
|
17.6
|
17.6
|
10.5-21.4
|
4
|
Naryan-Mar
|
67.63805
|
53.006926
|
25.2
|
25.2
|
15.9-56.1
|
10
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
20.7
|
20.7
|
8.9-32.8
|
13
|
Charyaginski, Zapolyarni district
|
67.214359
|
56.774622
|
47.2
|
47.2
|
24.7-84.0
|
17
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
32.2
|
32.2
|
23.3-45.1
|
3
|
Nenets autonomous okrug
|
Khorey-Ver, Zapoliarni district
|
67.42082
|
56.988744
|
32.1
|
32.1
|
10.7-61.8
|
23
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
23.9
|
23.9
|
26.3-52.5
|
11
|
Komi Republic
|
Inta, Inta City district
|
66.03682
|
60.115367
|
30.4
|
30.4
|
25.4-37.9
|
3
|
Petrun', Inta City district
|
66.472032
|
60.742615
|
36.9
|
36.9
|
26.4-49.8
|
3
|
Abez', Inta City district
|
66.520928
|
61.756166
|
23.6
|
23.6
|
4.5-34.6
|
3
|
Vorkuta
|
67.4935
|
64.050113
|
18.4
|
18.4
|
17.0-22.2
|
4
|
Yamalo-Nenets Autonomous Okrug
|
Muzhi, Shurishkarskiy district
|
65.400443
|
64.70556
|
13.3
|
13.3
|
11.4-16.0
|
3
|
Gorki, Shuryshkarskiy district
|
65.055353
|
65.273825
|
20.6
|
20.6
|
20.6
|
1
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
10.9
|
10.9
|
5.2-26.6
|
17
|
Beloyarsk, Priuralskiy district
|
66.868108
|
68.143053
|
11.1
|
11.1
|
8.2-13.5
|
3
|
Panaevsk, Yamalskiy district
|
66.744918
|
70.086244
|
13.5
|
13.5
|
10.1-15.9
|
5
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
13.3
|
13.3
|
7.0-25.2
|
19
|
Se-Yakha, Yamalskiy district
|
70.167798
|
72.511058
|
15.4
|
15.4
|
13.8-16.8
|
4
|
Nyda, Nadymskiy district
|
66.629301
|
72.923663
|
15.8
|
15.8
|
14.8-16.6
|
3
|
Antipayuta, Tazovskiy district
|
69.101507
|
76.865075
|
14.2
|
14.2
|
11.5-16.9
|
6
|
Tarko-Sale, Purovskiy disctrict
|
64.911819
|
77.761055
|
13.0
|
13.0
|
10.7-14.5
|
5
|
Samburg, Purovskiy district
|
67.003022
|
78.223471
|
15.3
|
15.3
|
8.8-18
|
5
|
Tazovskiy, Tazovskiy district
|
67.469359
|
78.701905
|
12.1
|
12.1
|
6.9-17.4
|
2
|
Krasnoselkup, Krasnoselkupskiy district
|
65.707158
|
82.466035
|
14.0
|
14.0
|
10.3-17.6
|
2
|
Taymir Peninsula (Krasnoyarsk Krai)
|
Dudinka, Taymir Dolgano-Nenets Autonomous okrug
|
69.404172
|
86.190953
|
1.2
|
4.4
|
1.2-1.3
|
5
|
Volochanka, Taymir Dolgano-Nenets Autonomous okrug
|
70.976083
|
94.541377
|
4.4
|
3.5
|
2.7-5.3
|
10
|
Kamchatka krai
|
Esso, Bystrinskiy district
|
55.928058
|
158.707517
|
3.5
|
3.5
|
2.3-5.2
|
4
|
Khailino, Olutorskiy district
|
60.958573
|
166.84867
|
0.0
|
1.0
|
0
|
2
|
Slautnoe, Penzhiskiy district
|
63.170231
|
167.973181
|
0.0
|
1.0
|
0.00
|
2
|
Apuka, Olutorskiy district
|
60.442644
|
169.605636
|
0.6
|
1.1
|
0-1.2
|
2
|
Achayvayam, Olutorskiy district
|
61.007986
|
170.507868
|
1.7
|
2.2
|
0-3.5
|
2
|
Chukotka Autonomous Okrug
|
Komsomolskiy, Pevek City district
|
69.132383
|
172.745939
|
0.0
|
1.0
|
|
1
|
Anadyr
|
64.735814
|
177.518904
|
1.4
|
1.4
|
1.0-1.7
|
8
|
Meat samples
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
1.1
|
1.3
|
0-1.6
|
6
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
1.2
|
1.6
|
0.-2.5
|
3
|
Nenets autonomous okrug
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.0
|
1.0
|
0.00
|
10
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
0
|
1.0
|
|
3
|
Nenets autonomous okrug
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
0.0
|
1.0
|
|
1
|
Komi Republic
|
Yustydor, Inta City district
|
66.054149
|
60.087914
|
2.0
|
2.0
|
2.0
|
1
|
Abez', Inta City district
|
66.520928
|
61.756166
|
0.00
|
1.00
|
|
1
|
Vorkuta
|
67.4935
|
64.050113
|
0.3
|
1.1
|
0-1.3
|
10
|
Yamalo-Nenets Autonomous Okrug
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
0.0
|
1.0
|
|
4
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
0.0
|
1.0
|
0-0.4
|
7
|
Republic of Sakha (Yakutia)
|
Udachniy, Mirniy municipal district
|
66.406966
|
112.306389
|
0.0
|
1.0
|
|
1
|
Iengra, Nerungri district
|
56.223391
|
124.848397
|
0.0
|
1.0
|
|
1
|
Chukotka Autonomous Okrug
|
Egvekinot, Egvekinot City district
|
66.32159
|
179.11981
|
0.0
|
1.0
|
|
3
|
Table 3. Mean concentrations of dioxins in liver depending on the region.
Region
|
Number of samples
|
Dioxins, mean concentration, pg WHO-TEQ/g of fat
|
Standard deviation
|
Concentration range in 95% confidence interval, pg WHO-TEQ/g of fat
|
Kola Peninsula (Murmansk oblast)
|
125
|
31.7
|
14.3
|
26.6-31.2
|
Nenets autonomous okrug
|
131
|
31.0
|
13.9
|
25.9-30.5
|
Komi Republic
|
16
|
27.7
|
11.4
|
18.4-33.3
|
Yamalo-Nenets Autonomous Okrug
|
75
|
13.1
|
4.6
|
11.3-13.3
|
Taymir Peninsula (Krasnoyarsk Krai)
|
15
|
3.3
|
1.7
|
2.0-4.0
|
Kamchatka and Chukotka
|
21
|
1.4
|
1.4
|
0.8-2.0
|
The overall number of meat samples from 13 locations was 51. Dioxins concentrations found in meat were relatively low, for most part of samples being under the Limit of Quantification of 1 pg WHO-TEQ/g. The highest concentration was found in one individual sample originating from Murmansk oblast (2.5 pg/g of fat WHO-TEQ). There are no regulatory limits for dioxins in reindeer meat in Russian and Eurasian Economical Union Legislation. Providing the low concentration, no conclusions could be made on geographical trends of reindeer meat pollution by dioxins.
The overall number of liver samples from 40 locations was 383, ranging from 1 to 91 samples for each sampling location. Dioxins concentrations varied from those below the Limit of Quantification (1 pg WHO-TEQ/g) up to 76.5 pg WHO-TEQ/g of fat, found in one individual sample from Nenets Autonomous Okrug.
In 31 locations mean Upper-Bound estimate (UB) dioxins concentration in liver exceeded the National and Eurasian Economical Union maximum levels for dioxins from the Customs Union Technical Regulation TR TS 021/2011–6 pg WHO-TEQ/g of fat, and only in 9 locations (all locations from Krasnoyarsk Krai, Chukotka and Kamchatka) the mean UB concentrations were lower than the maximum level.
A clear trend in geographical distribution in dioxins concentration in liver is shown with the highest concentration in the western part of the country and than gradually decreasing as one proceeds to the east. Heatmap of dioxins concentrations is presented in Fig. 2. Diagram of dioxins concentrations in liver depending of latitude is shown in Fig. 3. Coefficients of correlation between dioxins concentrations in liver and latitude are presented in Supplementary Table 1.
Providing that dioxin concentrations are generally higher in calves than in adult hinds, [4] and that we had no detailed information on age and sex of the animals for most part of the samples, the absence of data stratification by age group could be a source of bias.
Several factors, that may contribute to discovered trend in geographical distribution of reindeer liver dioxin contamination, are discussed below.
Generally, chemical industry is one of well-known sources of dioxin pollution [EFSA 2018]. In Russia, several hot-spots of dioxins pollution originating from organochlorine compounds production plants were investigated e.g. Chapayevsk, Samara oblast [Akhmedkhanov et al. 2002], Dzerzhinsk, Nizhniy Novgorod oblast [Petrlik et al. 2005] and Ufa, Bashkortostan [Amirova et al. 2015]. All of the abovementioned hotspots and most part of other chemical object, that may be a source of dioxin emission, are located in the western part of the country, while to the east from the Ural mountains there are quite few of them. The overwhelming majority of Russian chemical industry objects started functioning during the Soviet era and dioxins emmited and accumulated in the environment during this period and later are still likely to be among the most significant contributors to the Russian Far North pollution [AMAP 2004].
Soviet Union chemical and oil-refining industry is shown on the map in Fig. 4. Providing that dioxins emitted from chemical plants migrate first-of all to the closer regions [AMAP 2004], the conclusion may be made that dioxin concentration in reindeer liver has signs of correlation with the density of chemical industry objects. Among the Asian countries sharing the borders with Russia, China and Japan have the most developed chemical industry. Heavy chemically industrialized provinces of China e.g. Shandong, Jiangsu, Hubei, Henan and Inner Mongolia are located in more than 3000 km from the nearest sampling place in Kamchatka [Chen et al. 2020]. Japan is located much closer, the northern Japanese isle Hokkaido is approx. in 1500 km from the sampling place in Kamchatka. However, in Nenets Autonomous okrug, high concentrations of dioxins were found, and the closest chemical industry objects are located in approx. 1000 km from the plants. This indicates that nearest chemical industry is not the single factor making the critical contribution to the pollution.
It should be noted that not only chemical industry objects are a notable sources of dioxins, but other types of industry, waste incinerators and dumps, automobiles etc. as well [AMAP 2004]. However, the density of chemical industry objects in Figure corresponds well with the density of population and anthropogenic activity. The most part of cities are located in the Western part of Russia or along it’s South border, while there are quite few cities in the Nothern part of the country to the east of Ural mountains.
In 2013, the global air-borne dioxin deposition model was made by Booth et al. [Booth et al. 2013], and our results partly match with this model. According to the model, dioxin deposition is intensive in European part of the Russian Far North (in Kola Peninsula, Nenets Autonomous okrug and Komi Republic), much lower in middle part of Russian Far North (Yamalo-Nenets Autonomous okrug and Taymir Peninsula), and that distribution matches well our results. However, in eastern part of the country (Chukotka and Kamchatka) we have found the same low concentrations as in the middle part and, while according to the abovementioned model, dioxin deposition in Chukotka and Kamchatka should be higher than in the middle part (Yamalo-Nenets Autonomous okrug and Taymir Peninsula). Only parts of the regions, whence the samples were taken, were subject to comparison with Booth model of dioxins deposition.
Other important factor, that may contribute to dioxin pollution geographical trend, is the density of reindeers at pastures. The more animals graze on one area, the higher is the probability that due to lack to reindeer moss and other lichens and plants, more particles of soil will be ingested by the animals. Soil is a well-known reservoir of dioxins [EFSA 2011]. Western part of Russian far North, including Kola Peninsula, Nenets AO, Komi Republic and Yamalo-Nenets AO are marked by much higher density of reindeers comparing to the eastern regions: Taymir Peninsula, Yakutia, Kamchatka and Chukotka [Ministry 2013], see Fig. 5.
Cadmium and Mercury
Cadmium and mercury were determined in 505 samples of liver, 315 samples of kidneys and 22 samples of meat from 41 location. Cadmium and mercury concentrations depending on the sample place in reindeer liver, kidneys and meat are presented in the Tables 4 and 5, respectively. Mean concentrations depending on the region, including values of standard deviation and 95% Confidence Intervals are shown in Table 6.
Table 4. Cadmium concentrations in liver and kidneys depending on sample place location
Region
|
Sampling place
|
Latitude, DMS
|
Longitude, DMS
|
Cadmium, mean LB, mg/kg
|
Cadmium, mean UB, mg/kg
|
Range, mg/kg
|
Number of of samples
|
Kidneys
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
2.3
|
2.3
|
1.1-4.9
|
25
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
5.1
|
5.1
|
1-19
|
65
|
Nenets autonomous okrug
|
Nes', Zapoliarni district
|
66.600876
|
44.678905
|
2.0
|
2.0
|
0.011-6.5
|
25
|
Oma, Zapolyarni district
|
66.641769
|
46.492496
|
0.73
|
0.73
|
0.46
|
4
|
Verhniaia Pesha, Zapolyarni district
|
66.609449
|
47.953301
|
0.57
|
0.57
|
0.56-0.58
|
2
|
Indiga, Zapolyarni district
|
67.655217
|
49.037136
|
1.2
|
1.2
|
0.82-2
|
4
|
Khongurey, Zapoliarni district
|
67.557642
|
51.955412
|
0.8
|
0.8
|
0.52-1.6
|
7
|
Naryan-Mar
|
67.63805
|
53.006926
|
3.2
|
3.2
|
3.1-3.2
|
2
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.76
|
0.76
|
0.48-0.91
|
3
|
Khorey-Ver, Zapoliarni district
|
67.42082
|
56.988744
|
0.97
|
0.97
|
0.61-1.2
|
4
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
1.8
|
1.8
|
0.44-6.7
|
10
|
Nenets autonomous okrug
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
6.7
|
6.7
|
1.4-12
|
2
|
Komi Republic
|
Inta, Inta City district
|
66.03682
|
60.115367
|
5.5
|
5.5
|
4.6-6.5
|
3
|
Petrun', Inta City district
|
66.472032
|
60.742615
|
2.8
|
2.8
|
1-9.3
|
12
|
Abez', Inta City district
|
66.520928
|
61.756166
|
3.0
|
3.0
|
0.7-9.2
|
10
|
Vorkuta
|
67.4935
|
64.050113
|
6.0
|
6.0
|
1.2-21
|
7
|
Yamalo-Nenets Autonomous Okrug
|
Muzhi, Shurishkarskiy district
|
65.400443
|
64.70556
|
7.3
|
7.3
|
5.9-9.2
|
4
|
Gorki, Shuryshkarskiy district
|
65.055353
|
65.273825
|
3.5
|
3.5
|
1.2-6
|
4
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
3.4
|
3.4
|
0.42-7.8
|
16
|
Beloyarsk, Priuralskiy district
|
66.868108
|
68.143053
|
2.9
|
2.9
|
1-7.6
|
8
|
Panaevsk, Yamalskiy district
|
66.744918
|
70.086244
|
5.0
|
5.0
|
0.52-13
|
12
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
4.0
|
4.0
|
1-6.5
|
12
|
Se-Yakha, Yamalskiy district
|
70.167798
|
72.511058
|
4.0
|
4.0
|
1.1-8.9
|
10
|
Nyda, Nadymskiy district
|
66.629301
|
72.923663
|
3.85
|
3.85
|
0.9-12
|
8
|
Antipayuta, Tazovskiy district
|
69.101507
|
76.865075
|
1.3
|
1.3
|
0.42-3.5
|
8
|
Tarko-Sale, Purovskiy disctrict
|
64.911819
|
77.761055
|
4.0
|
4.0
|
0.89-8
|
5
|
Samburg, Purovskiy district
|
67.003022
|
78.223471
|
6.8
|
6.8
|
0.43-12
|
5
|
Tazovskiy, Tazovskiy district
|
67.469359
|
78.701905
|
2.0
|
2.0
|
0.36-4.6
|
4
|
Krasnoselkup, Krasnoselkupskiy district
|
65.707158
|
82.466035
|
2.8
|
2.8
|
0.95-6.6
|
4
|
Taymir Peninsula (Krasnoyarsk Krai)
|
Dudinka, Taymir Dolgano-Nenets Autonomous okrug
|
69.404172
|
86.190953
|
0.74
|
0.74
|
0.056-1.6
|
10
|
Kamchatka krai
|
Esso, Bystrinskiy district
|
55.928058
|
158.707517
|
1.0
|
1.0
|
0.63-1.2
|
4
|
Khailino, Olutorskiy district
|
60.958573
|
166.84867
|
5.3
|
5.3
|
4.1-6.4
|
2
|
Slautnoe, Penzhiskiy district
|
63.170231
|
167.973181
|
2.9
|
2.9
|
2.2-3.5
|
2
|
Achayvayam, Olutorskiy district
|
61.007986
|
170.507868
|
2.4
|
2.4
|
2.1-2.6
|
2
|
Chukotka Autonomous Okrug
|
Anadyr
|
64.735814
|
177.518904
|
5.5
|
5.5
|
3.4-8.3
|
10
|
Liver
|
Murmansk oblast
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
0.76
|
0.76
|
0.26-1.5
|
49
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
1.13
|
1.13
|
0.062-2.4
|
105
|
Nenets autonomous okrug
|
Mgla, Zapolyarni district
|
66.498855
|
44.449269
|
0.2
|
0.2
|
0.2
|
1
|
Nes', Zapoliarni district
|
66.600876
|
44.678905
|
0.41
|
0.41
|
0.17-0.78
|
29
|
Oma, Zapolyarni district
|
66.641769
|
46.492496
|
0.55
|
0.55
|
0.15-1.1
|
8
|
Verhniaia Pesha, Zapolyarni district
|
66.609449
|
47.953301
|
0.31
|
0.31
|
0.19-0.44
|
5
|
Indiga, Zapolyarni district
|
67.655217
|
49.037136
|
0.17
|
0.17
|
0.071-0.34
|
16
|
Khongurey, Zapoliarni district
|
67.557642
|
51.955412
|
0.24
|
0.24
|
0.16-0.33
|
4
|
Naryan-Mar
|
67.63805
|
53.006926
|
0.21
|
0.21
|
0.099-0.44
|
12
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.28
|
0.28
|
0.15-0.37
|
13
|
Charyaginski, Zapolyarni district
|
67.214359
|
56.774622
|
0.23
|
0.23
|
0.081-0.7
|
17
|
Khorey-Ver, Zapoliarni district
|
67.42082
|
56.988744
|
0.31
|
0.31
|
0.14-0.7
|
29
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
0.53
|
0.53
|
0.16-1.2
|
10
|
Nenets autonomous okrug
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
0.46
|
0.46
|
0.1-2
|
15
|
Komi Republic
|
Inta, Inta City district
|
66.03682
|
60.115367
|
0.33
|
0.33
|
0.2-0.42
|
3
|
Petrun', Inta City district
|
66.472032
|
60.742615
|
0.51
|
0.51
|
0.24-1.2
|
12
|
Abez', Inta City district
|
66.520928
|
61.756166
|
0.43
|
0.43
|
0.2-0.73
|
10
|
Vorkuta
|
67.4935
|
64.050113
|
0.76
|
0.76
|
0.44-1.2
|
7
|
Yamalo-Nenets Autonomous Okrug
|
Muzhi, Shurishkarskiy district
|
65.400443
|
64.70556
|
1.23
|
1.23
|
0.85-1.9
|
4
|
Gorki, Shuryshkarskiy district
|
65.055353
|
65.273825
|
0.83
|
0.83
|
0.45-1.3
|
4
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
0.61
|
0.61
|
0.24-1.4
|
24
|
Beloyarsk, Priuralskiy district
|
66.868108
|
68.143053
|
0.48
|
0.48
|
0.26-0.76
|
8
|
Panaevsk, Yamalskiy district
|
66.744918
|
70.086244
|
0.82
|
0.82
|
0.19-2
|
12
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
0.71
|
0.71
|
0.33-1.7
|
23
|
Se-Yakha, Yamalskiy district
|
70.167798
|
72.511058
|
0.74
|
0.74
|
0.22-1.7
|
10
|
Nyda, Nadymskiy district
|
66.629301
|
72.923663
|
0.69
|
0.69
|
0.29-1.7
|
8
|
Antipayuta, Tazovskiy district
|
69.101507
|
76.865075
|
0.41
|
0.41
|
0.14-0.86
|
8
|
Tarko-Sale, Purovskiy disctrict
|
64.911819
|
77.761055
|
0.49
|
0.49
|
0.16-0.73
|
5
|
Samburg, Purovskiy district
|
67.003022
|
78.223471
|
0.55
|
0.55
|
0.28-1.2
|
5
|
Tazovskiy, Tazovskiy district
|
67.469359
|
78.701905
|
0.34
|
0.34
|
0.19-0.49
|
4
|
Krasnoselkup, Krasnoselkupskiy district
|
65.707158
|
82.466035
|
0.46
|
0.46
|
0.27-0.62
|
4
|
Taymir Peninsula (Krasnoyarsk Krai)
|
Dudinka, Taymir Dolgano-Nenets Autonomous okrug
|
69.404172
|
86.190953
|
0.51
|
0.51
|
0.22-1.2
|
8
|
Volochanka, Taymir Dolgano-Nenets Autonomous okrug
|
70.976083
|
94.541377
|
0.41
|
0.41
|
0.12-1
|
10
|
Tura, Evenki district
|
64.272252
|
100.206396
|
1.3
|
1.3
|
|
1
|
Kamchatka krai
|
Esso, Bystrinskiy district
|
55.928058
|
158.707517
|
0.64
|
0.64
|
0.42-0.82
|
4
|
Khailino, Olutorskiy district
|
60.958573
|
166.84867
|
0.33
|
0.33
|
0.31-0.35
|
2
|
Slautnoe, Penzhiskiy district
|
63.170231
|
167.973181
|
0.55
|
0.55
|
0.33-0.76
|
2
|
Achayvayam, Olutorskiy district
|
61.007986
|
170.507868
|
0.49
|
0.49
|
|
2
|
Vaegi, Anadyrskiy district
|
64.165339
|
171.040631
|
0.52
|
0.52
|
|
1
|
Khatyrka, Anadyr district
|
62.061584
|
175.288773
|
0.17
|
0.17
|
|
1
|
Chukotka Autonomous Okrug
|
Anadyr
|
64.735814
|
177.518904
|
0.81
|
0.81
|
0.49-1.4
|
10
|
Meat
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
0.0031
|
0.0060
|
0-0.0087
|
7
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
0.0074
|
0.0099
|
0-0.023
|
8
|
Nenets autonomous okrug
|
Nelmin nos, Zapolyarni district
|
67.979742
|
52.956746
|
0.00
|
0.00
|
|
2
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.00
|
0.00
|
|
4
|
Charyaginski, Zapolyarni district
|
67.214359
|
56.774622
|
0.00
|
0.00
|
|
1
|
Table 5. Mercury concentrations in liver and kidneys depending on sample place location
Region
|
Sampling place
|
Latitude, DMS
|
Longitude, DMS
|
Mercury, mean LB, mg/kg
|
Mercury, mean UB, mg/kg
|
Range, mg/kg
|
N of samples
|
Kidneys
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
0.34
|
0.34
|
0.23-0.52
|
25
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
0.73
|
0.73
|
0.34-1.8
|
65
|
Nenets autonomous okrug
|
Nes', Zapoliarni district
|
66.600876
|
44.678905
|
0.65
|
0.65
|
0-1
|
25
|
Oma, Zapolyarni district
|
66.641769
|
46.492496
|
1.1
|
1.1
|
1-1.2
|
4
|
Verhniaia Pesha, Zapolyarni district
|
66.609449
|
47.953301
|
0.44
|
0.44
|
0.4-0.48
|
2
|
Indiga, Zapolyarni district
|
67.655217
|
49.037136
|
0.73
|
0.73
|
0.53-1.1
|
4
|
Khongurey, Zapoliarni district
|
67.557642
|
51.955412
|
0.63
|
0.63
|
0.51-0.71
|
7
|
Naryan-Mar
|
67.63805
|
53.006926
|
0.9
|
0.9
|
0.86-0.93
|
2
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.4
|
0.4
|
0.3-0.49
|
3
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
0.48
|
0.48
|
0.29-0.8
|
10
|
Nenets autonomous okrug
|
Khorey-Ver, Zapoliarni district
|
67.42082
|
56.988744
|
0.6
|
0.6
|
0.44-0.78
|
4
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
0.75
|
0.75
|
0.61-0.88
|
2
|
Komi Republic
|
Inta, Inta City district
|
66.03682
|
60.115367
|
0.59
|
0.59
|
0.45-0.67
|
3
|
Petrun', Inta City district
|
66.472032
|
60.742615
|
0.32
|
0.32
|
0.19-0.51
|
12
|
Abez', Inta City district
|
66.520928
|
61.756166
|
0.45
|
0.45
|
0.28-0.6
|
10
|
Vorkuta
|
67.4935
|
64.050113
|
0.46
|
0.46
|
0.25-0.78
|
7
|
Yamalo-Nenets Autonomous Okrug
|
Muzhi, Shurishkarskiy district
|
65.400443
|
64.70556
|
0.71
|
0.71
|
0.61-0.77
|
4
|
Gorki, Shuryshkarskiy district
|
65.055353
|
65.273825
|
0.46
|
0.46
|
0.37-0.53
|
4
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
0.56
|
0.56
|
0.22-0.79
|
16
|
Beloyarsk, Priuralskiy district
|
66.868108
|
68.143053
|
0.53
|
0.53
|
0.36-0.78
|
8
|
Panaevsk, Yamalskiy district
|
66.744918
|
70.086244
|
0.4
|
0.4
|
0.21-0.7
|
12
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
0.6
|
0.6
|
0.43-0.92
|
12
|
Se-Yakha, Yamalskiy district
|
70.167798
|
72.511058
|
0.5
|
0.5
|
0.38-0.71
|
10
|
Nyda, Nadymskiy district
|
66.629301
|
72.923663
|
0.6
|
0.6
|
0.43-0.82
|
8
|
Antipayuta, Tazovskiy district
|
69.101507
|
76.865075
|
0.34
|
0.34
|
0.2-0.54
|
8
|
Tarko-Sale, Purovskiy disctrict
|
64.911819
|
77.761055
|
0.84
|
0.84
|
0.47-1.2
|
5
|
Samburg, Purovskiy district
|
67.003022
|
78.223471
|
0.38
|
0.38
|
0.24-0.58
|
5
|
Tazovskiy, Tazovskiy district
|
67.469359
|
78.701905
|
0.37
|
0.37
|
0.17-0.51
|
4
|
Krasnoselkup, Krasnoselkupskiy district
|
65.707158
|
82.466035
|
0.42
|
0.42
|
0.3-0.54
|
4
|
Taymir Peninsula (Krasnoyarsk Krai)
|
Dudinka, Taymir Dolgano-Nenets Autonomous okrug
|
69.404172
|
86.190953
|
0.054
|
0.054
|
0.02-0.1
|
10
|
Kamchatka krai
|
Esso, Bystrinskiy district
|
55.928058
|
158.707517
|
0.25
|
0.25
|
0.22-0.27
|
4
|
Khailino, Olutorskiy district
|
60.958573
|
166.84867
|
0.66
|
0.66
|
0.46-0.85
|
2
|
Slautnoe, Penzhiskiy district
|
63.170231
|
167.973181
|
0.53
|
0.53
|
0.39-0.67
|
2
|
Achayvayam, Olutorskiy district
|
61.007986
|
170.507868
|
0.38
|
0.38
|
0.36-0.39
|
2
|
Chukotka Autonomous Okrug
|
Anadyr
|
64.735814
|
177.518904
|
1.1
|
1.1
|
0.93-1.5
|
10
|
Liver
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
0.12
|
0.12
|
0.052-0.23
|
49
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
0.26
|
0.26
|
0.022-0.52
|
105
|
Nenets autonomous okrug
|
Mgla, Zapolyarni district
|
66.498855
|
44.449269
|
0.20
|
0.20
|
|
1
|
Nes', Zapoliarni district
|
66.600876
|
44.678905
|
0.18
|
0.18
|
0.094-0.34
|
29
|
Oma, Zapolyarni district
|
66.641769
|
46.492496
|
0.27
|
0.27
|
0.13-0.47
|
8
|
Verhniaia Pesha, Zapolyarni district
|
66.609449
|
47.953301
|
0.25
|
0.25
|
0.21-0.28
|
5
|
Indiga, Zapolyarni district
|
67.655217
|
49.037136
|
0.22
|
0.22
|
0.15-0.32
|
16
|
Khongurey, Zapoliarni district
|
67.557642
|
51.955412
|
0.21
|
0.21
|
0.014-0.3
|
4
|
Naryan-Mar
|
67.63805
|
53.006926
|
0.21
|
0.21
|
0.076-0.33
|
12
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.18
|
0.18
|
0.11-0.29
|
13
|
Charyaginski, Zapolyarni district
|
67.214359
|
56.774622
|
0.16
|
0.16
|
0.074
|
17
|
Komi Republic
|
Verhnekolvinsk, Uninsk City district
|
66.668506
|
56.988744
|
0.15
|
0.15
|
0.089-0.2
|
10
|
Nenets autonomous okrug
|
Khorey-Ver, Zapoliarni district
|
67.42082
|
56.988744
|
0.20
|
0.20
|
0.1-0.36
|
29
|
Kharuta, Zapoliarni district
|
66.840223
|
59.526054
|
0.15
|
0.15
|
0.056-0.25
|
15
|
Komi Republic
|
Inta, Inta City district
|
66.03682
|
60.115367
|
0.18
|
0.18
|
0.12-0.22
|
3
|
Petrun', Inta City district
|
66.472032
|
60.742615
|
0.11
|
0.11
|
0.078-0.14
|
12
|
Abez', Inta City district
|
66.520928
|
61.756166
|
0.13
|
0.13
|
0.069-0.25
|
10
|
Vorkuta
|
67.4935
|
64.050113
|
0.11
|
0.11
|
0.065-0.2
|
7
|
Yamalo-Nenets Autonomous Okrug
|
Muzhi, Shurishkarskiy district
|
65.400443
|
64.70556
|
0.15
|
0.15
|
0.14-0.16
|
4
|
Gorki, Shuryshkarskiy district
|
65.055353
|
65.273825
|
0.23
|
0.23
|
0.12-0.41
|
4
|
Aksarka, Priuralskiy district
|
66.558885
|
67.806086
|
0.19
|
0.19
|
0.094-0.55
|
24
|
Beloyarsk, Priuralskiy district
|
66.868108
|
68.143053
|
0.14
|
0.14
|
0.088-0.18
|
8
|
Panaevsk, Yamalskiy district
|
66.744918
|
70.086244
|
0.12
|
0.12
|
0.08-0.17
|
12
|
Yar-Sale, Yamalskiy district
|
66.861201
|
70.839311
|
0.19
|
0.19
|
0.12-0.4
|
23
|
Se-Yakha, Yamalskiy district
|
70.167798
|
72.511058
|
0.10
|
0.10
|
0.055-0.17
|
10
|
Nyda, Nadymskiy district
|
66.629301
|
72.923663
|
0.19
|
0.19
|
0.14-0.24
|
8
|
Antipayuta, Tazovskiy district
|
69.101507
|
76.865075
|
0.11
|
0.11
|
0.073-0.17
|
8
|
Tarko-Sale, Purovskiy disctrict
|
64.911819
|
77.761055
|
0.39
|
0.39
|
0.22-0.52
|
5
|
Samburg, Purovskiy district
|
67.003022
|
78.223471
|
0.17
|
0.17
|
0.13-0.24
|
5
|
Tazovskiy, Tazovskiy district
|
67.469359
|
78.701905
|
0.15
|
0.15
|
0.091-0.18
|
4
|
Krasnoselkup, Krasnoselkupskiy district
|
65.707158
|
82.466035
|
0.14
|
0.14
|
0.11-0.19
|
4
|
Krasnoyarsk Krai
|
Dudinka, Taymir Dolgano-Nenets Autonomous okrug
|
69.404172
|
86.190953
|
0.051
|
0.057
|
0-0.2
|
8
|
Volochanka, Taymir Dolgano-Nenets Autonomous okrug
|
70.976083
|
94.541377
|
0.053
|
0.053
|
0.02-0.082
|
10
|
Tura, Evenki district
|
64.272252
|
100.206396
|
1.0
|
1.0
|
|
1
|
Kamchatka krai
|
Esso, Bystrinskiy district
|
55.928058
|
158.707517
|
0.067
|
0.067
|
0.054-0.072
|
4
|
Khailino, Olutorskiy district
|
60.958573
|
166.84867
|
0.12
|
0.12
|
0.093-0.15
|
2
|
Slautnoe, Penzhiskiy district
|
63.170231
|
167.973181
|
0.13
|
0.13
|
0.13-0.13
|
2
|
Achayvayam, Olutorskiy district
|
61.007986
|
170.507868
|
0.088
|
0.088
|
0.056-0.12
|
2
|
Vaegi, Anadyrskiy district
|
64.165339
|
171.040631
|
0.25
|
0.25
|
|
1
|
Khatyrka, Anadyr district
|
62.061584
|
175.288773
|
0.25
|
0.25
|
|
1
|
Chukotka Autonomous Okrug
|
Anadyr
|
64.735814
|
177.518904
|
0.089
|
0.089
|
0.059-0.12
|
10
|
Meat
|
Kola Peninsula (Murmansk oblast)
|
Lovozero, Lovozero district
|
68.00466
|
35.014147
|
0.0051
|
0.011
|
0-0.013
|
7
|
Krasnoschelie, Lovozero district
|
67.349847
|
37.053197
|
0.0071
|
0.011
|
0-0.013
|
8
|
Nenets autonomous okrug
|
Nelmin nos, Zapolyarni district
|
67.979742
|
52.956746
|
0.0
|
0.0
|
0-0.011
|
2
|
Iskateley, Zapoliarni district
|
67.677629
|
53.127704
|
0.0
|
0.0
|
|
4
|
Charyaginski, Zapolyarni district
|
67.214359
|
56.774622
|
0.0
|
0.0
|
|
1
|
Table 6. Mean cadmium and mercury concentrations in liver and kidneys depending on the region.
Region
|
Number of samples
|
Mean, pg WHO-TEQ/g of fat
|
Standard deviation
|
Concentration range in 95% confidence interval, pg WHO-TEQ/g of fat
|
Dioxins in liver, Lowerbound estimate
|
Kola Peninsula (Murmansk oblast)
|
125
|
31.7
|
14.3
|
26.6-31.2
|
Nenets autonomous okrug
|
131
|
31.0
|
13.9
|
25.9-30.5
|
Komi Republic
|
16
|
27.7
|
11.4
|
18.4-33.3
|
Yamalo-Nenets Autonomous Okrug
|
75
|
13.1
|
4.6
|
11.3-13.3
|
Taymir Peninsula (Krasnoyarsk Krai)
|
15
|
3.3
|
1.7
|
2.0-4.0
|
Kamchatka and Chukotka
|
21
|
1.4
|
1.4
|
---
|
Dioxins in liver, lowerbound
|
|
|
|
|
Cadmium in liver, Lowerbound estimate
|
Murmansk oblast (Kola Peninsula)
|
154
|
1.0
|
0.51
|
0.8 - 1
|
Nenets autonomous okrug
|
149
|
0.32
|
0.23
|
0.2-0.3
|
Komi Republic
|
42
|
0.52
|
0.28
|
0.4-0.5
|
Yamalo-Nenets Autonomous Okrug
|
119
|
0.65
|
0.39
|
0.5-0.6
|
Taymir Peninsula (Krasnoyarsk Krai)
|
19
|
0.5
|
0.38
|
0.3-0.5
|
Kamchatka and Chukotka
|
22
|
0.64
|
0.28
|
0.5-0.7
|
Cadmium in kidneys, Lowerbound estimate
|
Murmansk oblast (Kola Peninsula)
|
90
|
4.4
|
3.3
|
3.1-4
|
Nenets autonomous okrug
|
53
|
1.7
|
2.0
|
0.8-1.5
|
Komi Republic
|
42
|
3.4
|
3.8
|
1.7-2.9
|
Yamalo-Nenets Autonomous Okrug
|
100
|
3.8
|
3.1
|
2.3-3.2
|
Taymir Peninsula (Krasnoyarsk Krai)
|
10
|
0.74
|
0.49
|
0.3-1.1
|
Kamchatka and Chukotka
|
20
|
4
|
2.27
|
2.3-4.6
|
Mercury in liver, Lowerbound estimate
|
Murmansk oblast (Kola Peninsula)
|
154
|
0.21
|
0.11
|
0.2-0.2
|
Nenets autonomous okrug
|
149
|
0.19
|
0.07
|
0.2-0.2
|
Komi Republic
|
42
|
0.13
|
0.04
|
0.1-0.1
|
Yamalo-Nenets Autonomous Okrug
|
119
|
0.17
|
0.09
|
0.1-0.2
|
Taymir Peninsula (Krasnoyarsk Krai)
|
19
|
0.06
|
0.07
|
---
|
Kamchatka and Chukotka
|
22
|
0.11
|
0.05
|
0.1-0.1
|
Mercury in kidneys, Lowerbound estimate
|
Murmansk oblast (Kola Peninsula)
|
90
|
0.62
|
0.3
|
0.5-0.6
|
Nenets autonomous okrug
|
53
|
0.67
|
0.22
|
---
|
Komi Republic
|
42
|
0.43
|
0.15
|
0.4-0.5
|
Yamalo-Nenets Autonomous Okrug
|
100
|
0.52
|
0.18
|
0.5-0.5
|
Taymir Peninsula (Krasnoyarsk Krai)
|
10
|
0.05
|
0.02
|
0-0.1
|
Kamchatka and Chukotka
|
20
|
0.75
|
0.4
|
0.5-0.9
|
Cadmium concentrations were found to be generally much higher than mercury concentrations. The concentrations of metals in kidneys were much higher than in liver. In meat only low concentration of cadmium and mercury were found, mostly below the limit of detection. The highest concentrations of cadmium in liver (more than 1 mg/kg) were found in 3 sampling places from Murmansk oblast, Yamalo-Nenets Autonomous okrug and Taymir Peninsula. Highest cadmium concentrations in kidneys (more than 6 mg/kg) were found in Komi republic, Nenets and Yamalo-Nenets AO. Highest mercury concentration in liver (1 mg/kg) was found in one sample from Taymir Peninsula. Highest mercury concentrations (more than 1 mg/kg) in kidneys were found in Nenets AO and Chukotka.
Cadmium and mercury concentrations in kidneys and liver exceeded the National Maximum Levels from the Customs Union Technical Regulation TR TS 021/2011 (0.3 mg/kg – cadmium in offal, 0.1 mg/kg – mercury in offal) for almost all sampling places. No violations of Maximum Level (0.05 mg/kg – cadmium, 0.03 mg/kg - mercury) were found for meat.
Heatmap of cadmium and mercury concentrations in kidneys are presented in pictures 6 and 7, respectively. Unlike dioxins, no signs of concentration dependence on latitude may be seen from our data. Coefficients of correlation between heavy metals concentrations and latitude are presented in Supplementary Table 1.
Limited data on age and sex of animals did not allow to plot data by these parameters. However, these data was provided for samples from Yamalo-Nenets AO. Data on cadmium and mercury concentrations depending on sex are presented in Supplemental Table 2. For mercury and cadmium, the difference in concentrations between two sexes did not exceed 10% for both liver and kidneys. Data on metals concentrations, depending on age of the animals, is presented in Supplemental table 3. Coefficients of correlation between heavy metals concentrations and age groups are presented in Supplementary Table 1. The following age groups were considered: up to 0-0.5 years, 0.5–1.5 years, 1.5-3 years, 3-4.5 years, 4.5 + years. Statistically significant correlation was found only for cadmium in kidneys, and it was strong negative correlation (R is -0.9115, the P-value is 0.031444). This does not correspond with literature indicating that cadmium accumulates in kidneys with age and the correlation is positive [Hooser 2018; Gamberg et al. 2020], while mercury renal concentrations are highly dependent on sex [Gamberg et al. 2020]. Taking into account the confusion in data, geographical localization may be a better predictor of cadmium and mercury concentration in reindeer liver and kidneys, than age and sex of the animals.
Data on individual samples from Yamalo- Nenets AO with indication of age and sex of the animals is presented in Supplemental Table 4.
Mean cadmium concentrations in kidneys for each age groups and each sampling place were compared to each other. The range of cadmium concentrations in kidneys for age groups was 2.81–4.71 mg/kg (1.7-fold difference between the lowest and the highest concentrations), while the range of concentration between sampling places in Yamalo-Nenets AO was much wider: 1.30–7.30 mg/kg (5.6-fold difference). Along with relatively low difference in cadmium concentrations between male and female tissues (< 10%), this indicates, that cadmium concentrations in our data are dependent more on geographical localization, than age and sex. However, absence of data stratification by age group due to lack of information could be a source a bias.
Mining enterprises, including non-ferrous metals production, are believed to be important sources of mercury and cadmium pollution of the environment [AMAP 2004; Zengwei et al. 2019]. The most active local sources of mercury emission in Russian Far North are located in two places in Kola Peninsula - Monchegosrk and Zapolyarni district and one place in Taymir Peninsula (Krasnoyarsk krai) - Norilsk. These sources are combined smelters of «Norilsk Nickel» company – one of the world’s largest producers of non-ferrous metals: palladium, nickel, platinum, cobalt and copper and other ore-dressing and processing enterprises.
There were two sampling places in relatively close vicinity to the abovementioned enterprises – one in Lovozero: 60 km to Monchegorsk, the other in Dudinka: 60 km to Norilsk. As it may be seen from Tables 3 and 4, cadmium concentrations in these sampling places in liver and kidneys are not among the highest, and mercury concentrations are even among the lowest.
There were two sampling places in Kola Peninsula: Krasnoschelie and Lovozero. Krasnoschelie is located in approx. 100 km from Lovozero to the South East, being further from Monchegorsk than Lovozero. Average mercury concentrations in liver and kidneys from Krasnoschelie are approx twice as high as in Lovozero, and quite the same situation is with cadmium. These data indicate that local sources of pollution may not play a crucial role of cadmium and liver accumulation in reindeers, at least at the distance greater than 60 km.
The overall density of domesticated reindeer population leading to increased digestion of the soil particles may play less role for metals, than in case of dioxins. Dioxins, being lypophilic compounds, accumulate poorly in lichens and plants, while cadmium and mercury do it well [Hassan et al. 2012; WHO 2016; Bačkor et al. 2009], so additional swallowing of soil will have less effect of heavy metals accumulation in reindeer tissues, comparing to dioxins.
Lichen and plant contamination, originating from atmospheric deposition and soil pollution, coupled with individual and subpopulational biochemical variability, age, sex, month of sampling may be the factors, that are responsible for the differences in cadmium and mercury distribution between sampling places in the Russian Far North.
Reindeer liver as global indicator of dioxins, cadmium and mercury pollution
Here we present data on geographical distribution of reindeer liver and kidneys pollution by dioxins, cadmium and mercury and discuss possible factors that could affect it.
For environmental monitoring purposes, reindeer liver may serve as good additional indicator of dioxins, cadmium and mercury pollution of Nothern regions of the planet, along with air, soil, plants etc., for the following reasons:
- All reindeers in Europe and Asia belong to the same species Rangifer tarandus, which is the only representative of the genus Rangifer. There are several subspecies, e.g. Rangifer tarandus tarandus and Rangider tarandus sibiricus in Eurasia, and Rangifer tarandus caribou in America. Differences between reindeer (Eurasia) and caribou (America), for example caribou is larger than reindeer. However, data indicate typical similarity in terms of biochemistry, resistance to harmful agents and feeding habits for both species [Johnson 2012; Tryland et al. 2018].
- Both reindeer and caribou are likely to exhibit the longest terrestrial migrations among mammalians on the planet. The animals graze on vast areas, having seasonal migrations on distances up to hundreds kilometers in one side in North-South direction [Hansen et al. 2010, Nicholson et al. 2016]. Dioxins and heavy metals are unevenly spatially distributed in soil. Reindeer and caribou graze on the whole path of their migration, and have a higher, than other animals, likehood to cross the contaminated local areas. So, their tissues may be representative for dioxins and metals environmental concentrations for the whole grazing area, and thus may serve for effective comparison of pollution between the regions with different latitudes [EFSA 2011; Kachova 2015].
- Most reindeers are semi-domestic animals, feeding with natural feeds e.g. lichens, mosses, plants, mushrooms etc. Supplementary feeding is used only in certain conditions [Horstkotte et al. 2020], so the impact of artificial feeds on reindeer dioxin and heavy metals contamination is minimal. At the other hand, taking samples from reindeer may be easily made at slaughterhouses and presents less difficulties, than sampling of wild animals.