2.1 Soil sampling
Soil sampling was carried out in the last decade of April - the first 10 days of May, by the "envelope" method of five points, the depth of which was about 10 cm i.e. the upper fertile layer. During the sampling, the presence or absence of organic fertilizer use was registered. Spot samples taken at the same sampling site were combined, thereby achieving their mixing and homogenization. Sample preparation included: preliminary drying of the soil, removal of foreign matter. The dataset includes a total of 189 samples of soils of Tomsk oblast’.
For the investigation, the settlements of the Tomsk region located within the interfluve of the Ob River and its large tributaries are considered. There are 6 inter-stream areas in Tomsk oblast’ and 47 settlements are included in the research area.
In the following table the list of the districts included in the interfluves is given, information about the number of settlements in each administrative district is given in the annex (Table 1).
As can be seen from table 1, some interfluve areas include settlements included administratively in the same district, others overlap administrative districts. We exclude the double-counting of the same districts by using the concentration of Cr from different villages.
2.3 Meat sampling
The sampling was carried out by the researchers from the Division for Geology of Tomsk Polytechnic University. The total quantity of samples is 78 samples of organs and tissues of 2 animals. Organs and tissues of 2 domestic pigs Sus scrofa domesticus were taken from private farms in Tomsk region of Tomsk oblast’ (Russia).
The samples of organs and tissues of the domestic pig represent the whole organism of the animal and all parts that can be consumed as food. The food samples were taken on private farms, raising animals for sale to the native population in the local markets.
The representability of biomaterials of domestic pigs as a sufficient environmental indicator was already presented in a previous investigation by the research group of Tomsk Polytechnic University (Baranovskaya and Rikhvanov, 2011; Belyanovskaya et al., 2019). Results of the chemical analysis are presented in the corresponding table, under the ‘Annex’ section.
Sample preparation and analysis
Soil and pork samples were analyzed by Instrumental Neutron Activation Analysis (INAA). The INAA analysis has an advantage as a direct non-destructive analysis without chemical decomposition of samples. In the published papers, the accuracy of the analysis is proven (Arbuzov et al. 2016, 2019; Arbuzov 2017).
Sample preparation for the INAA takes place in several stages: a package of aluminum foil (size 3 cm x 3 cm), its pretreatment with an alcohol, a bag formation with tweezers, then weighing the foil bag (mg) on an electronic balance. A sample code is affixed to the bag, the sample is poured into bags on electronic scales to determine the weight of the sample (ideally 100 mg) and the total weight.
The analysis of the samples is carried out at the “IRT-T” research nuclear reactor in the nuclear geochemical laboratory of the Division for Geology of the National Research Tomsk Polytechnic University (accreditation certificate RA.RU.21AB27 of 04/08/2015). Analysis was carried out by A.F. Sudyko and L.F. Bogutskaya according to the instructions of NSAM VIMS No. 410-YAF.
The thermal neutron flux density in the irradiation channel is 2*1013 neutrons (cm2*s), the duration of sample irradiation is 20 hours. The measurements were carried out on a gamma spectrometer with a germanium-lithium detector DGDK-63A. The detection limit of Cr in soils by the INAA is 0.2 ppm.
Processing and generalization of the obtained analytical data was carried out on a personal computer using the office suite Microsoft Office (Excel, Word 2013) and the program “Statistica 7”. To build the graphic material, the software “Surfer 10” and “CorelDraw” were used. Samples were organized for Tomsk oblast’, using both the administrative approach of spatial recognition and by considering the divisions according to the interfluve areas to which they belong.
4.1 The statistical analysis
Statistical processing of data (with a reliability level of 95%) is carried out.
When calculating the average contents of elements from the total sample, “hurricane samples” were removed, but they are shown in the scatter of values. When some elements were present in concentrations below the detection limit of the analysis, half of the threshold value is used in the calculation (Mikhalchuk and IAzikov 2014). Regardless of the nature of the distribution of elements, we took the arithmetic mean values of the sample as average levels of content, which, with both normal and asymmetric distribution, gives the most consistent estimate of the concentration values (Tkachev and IUdovich 1975).
The significance of the differences in the sample sets is estimated using the Kolmogorov-Smirnov statistical non-parametric analysis method. The differences were considered significant at a p-level p <0.001.
4.2 Methodology for assessing the toxicity of elements
The basics of the USEtox model developed on the Microsoft Excel platform (Figure 1, Annex). USEtox is a model based on scientific consensus providing midpoint and endpoint characterization factors for human toxicological and freshwater ecotoxicological impacts of chemical emissions in life cycle assessment (Fantke et al. 2017).
According to the USEtox, Impact Score (IShum) is a LCIA impact score used for characterizing human toxicity that is expressed as a number of cancer or non-cancer disease cases at midpoint level and as a number of disability-adjusted life years [DALY] at endpoint level (Fantke et al., 2017).
Midpoint indicators focus on single environmental problems in the case-effect chain, endpoint indicators show the environmental impact on higher aggregation levels (Bare et al. 2000; Huijbregts et al. 2016b).
The IShum for potential impacts of chromium is calculated using a weighted summation of pollutants released from potential pollution sources and characterization factors for the damage (Figure 3, formula 2). The characterization factor needed for the impact score calculation was derived using the USEtox model dataset.
For the modification of the characterization factor and the Impact score, two types of local samples are used.
- Tomsk oblast’ soils. These are used for the characterization factors and the impact score calculation and modification (Figure 3, formulas I, II);
- Pork sampled in two settlements of Tomsk oblast’. This data is extrapolated into the exposure factor modification (Figure 3, formula III).
The total mass of the element in soils (MCr) is calculated according to the formula developed by (Bratec et al. 2019) (Figure 3, formula IV).
- Cx,i is the concentration of chromium in agricultural soils in each studied area. Cx,i is taken from the own analytical results;
- ps is the bulk density of soils, which is the table value taken from the USEtox documentation [kgsoil/m3soil];
- Vs is the volume of soils of each considered region [m3].
The characteristic toxicity factor (CF) is calculated by USEtox documentation. Characterization factor for the potential human health damages at the endpoint is expressed in DALY/kg emitted – disability adjusted years per kg emitted. The CF is derived as the multiplication of three factors:
Effect factor (EF) [kgintake/day] reflects the impact on human health due to the arrival of a chemical element substance in the living organism in various ways (through air, water, soil or food).
Fate factor (FF) [kgin compartment per kgemitted/day] represents the persistence of a chemical in the environment (e.g. in days) as well as the relative distribution.
Exposure factor (XF) [kgintake/day per kgin compartment] describes the effective human intake of a specific environmental medium– soil – through ingestion.
In the current investigation, we use the default values of effect and fate factors, but with the modification of exposure factor using the analytical data of the concentration of chromium in the pork meat (Belyanovskaya et al., 2019). This reflects the effective intake of elements via soil or air into the human body when eating meat products.
The exposure factor is calculated according to the formula given in the framework of the investigation (Figure 3, formula 5), where the bulk density (pi) of the soils and the individual consumption rate (IR) are tabular values and are taken from the model for calculation. The volume of soils (Vi [m3]) is calculated by the following formula:
Formula 1. The volume of medium i calculation
Where, hi [m] is the height of medium i (continental and global air, or soil), the table value presented in the model, and Si [m2] is the area of agricultural soils, depending on the geographical features of the studied region.
In order to take into account the environmental features of the region, the bio-transfer factor (BTF) is replaced by the ratio of the concentration of Cr (CCr) [mg/kgxp] in pork (according to the results of chemical analysis), and the concentration of chromium in soils of each studied region (Figure 3, formula 6) [mg/kg]. Where, the bio-transfer factor BTF [days/kgsubstrate] is the steady-state ratio between the concentration Csubstrate in meat or milk respectively and the intake i of a chemical (Cr) by the animal.
In previous investigations the concentration ratio was normalized to the percent abundance (Glazovsky clarke of Cr in biosphere (Glazovsky 1982)). In the current investigation the Cr concentration in soils is taken for the ratio.
Official data is used for the total square footage and population calculation of the administrative areas and interfluves (2020). The area between the biggest rivers of Tomsk oblast, forming the interfluves is used for the square footage calculation. The geographical information obtained is given in the annex section.