Determination of tungsten’s toxicity coefficient for potential ecological risk assessment

The potential ecological risk index (RI), proposed by the Swedish geochemist Hakanson, has been widely used for quantitatively evaluating the pollution degree caused by various pollutants. As an emerging contaminant, tungsten (W) poses ecological risks to the environment, and the quantitative assessment of the risk is of extraordinary significance. However, the lack of a determined W toxicity coefficient has limited the use of the RI in evaluating the W pollution degree. In this study, the toxicity coefficient of W (= 2.00) was calculated based on Hakanson’s theory, then verified via a case study conducted by 23 sediment samples in Taojiang River near a W mining area in southern Jiangxi. The risk factor (E w ) and geoaccumulation index (I geo ) of W, and RI and Nemerow comprehensive pollution index (NCPI) of eight heavy metals at each sampling site were calculated and compared, respectively. The results showed consistent correlations and trends of pollution levels for the investigated sites, which means the rationality of assigning a toxicity coefficient of 2.00 for W. These results can contribute to the use of the RI method for the scientific evaluation of W pollution levels.


Introduction
The potential ecological risk index (RI) proposed by the Swedish geochemist Hakanson [1] is a method to quantitatively evaluate the level of pollution caused by heavy metals in sediment [2][3][4]. Its application has been extended to other environmental media, such as the atmosphere [5], dust storms [6], and soil [7,8]. According to Hakanson's theory, the potential ecological risk factor (E r i ) of a single heavy metal can be calculated by equation (1). The RI is defined as the sum of the E r i of all related metals, as shown in equation (2). where C r i is the pollution coefficient of heavy metal, C m i is the measured concentration of heavy metal in surface sediments, C n i is the reference standard of heavy metal, and T r i is the toxicity coefficient which reflects both the toxic intensity of the heavy metal and the sensitivity to it of water. The toxicity coefficients of As, Cd, Cr, Cu, Hg, Pb, and Zn were reported by Hakanson [1]. Other authors have followed Hakanson's principle to calculate the coefficients of other metals, including B [9], Co [10], Ni [10], Sb [11], Tl [11], V [10], and rare earth elements [12]. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Tungsten (W) is a transition metal from Group VIB of the periodic table. Its properties were similar to Molybdenum (Mo). Owing to its advantages of hardness, high melting point, and chemical stability, W is widely used in many fields, including metallurgy, electronics, and military equipment [13][14][15][16][17]. China has a long history of W mining and possesses the largest reserves and highest outputs of W globally [18]. After nearly 200 years of exploitation and use, W and its compounds are widely distributed in various environmental media, including the soil [13,19], water [20,21], sediments [22], and atmosphere [23]. The W concentrations in surface water and shallow sediments of typical mining areas in southern Jiangxi have exceeded the corresponding standards, and most of this pollution derives from human activities such as mining, metallurgy, and poultry breeding [24][25][26][27]. Clausen and Korte [28] investigated the level of W pollution on a military base in Massachusetts, USA. The result showed that the W concentration in the surface soil reached 2080.00 mg kg −1 . These concentrations decreased rapidly with depth but were still higher than the background concentration (1.5 mg kg −1 , determined at locations believed unaffected by W) even at a depth of 150 cm. An air quality study in the USA showed that the W content in the atmosphere in industrial areas was 1-2 orders of magnitude higher than those observed in ambient air [23]. An air pollution survey in eight urban areas of Canada also showed that the concentration of W in the urban particulate matter was four times higher than in the ambient air [23].
The W was regarded as an element harmless to human health and the environment for a long period owing to its insolubility and other chemical stability properties [29]. However, concerns regarding its associated health and environmental risks have increased worldwide since a 1997 poisoning incident in Fallon, Nevada, USA [30]. It has been recognised as an emerging contaminant in the USA [22] and a highly hazardous water pollutant in Russia [31]. In China, the W smelting slag which is produced by alkali decomposition during the production of ammonium paratungstate (APT), was listed as a hazardous waste in 2021 [32]. The W is distributed in the soil and sediments mainly in the forms of tungstate or polytungstate, and the latter might be substantially more toxic than the former [33]. Furthermore, the W and its compounds in the environment accumulate in plants and then enter the human body via the food chain, potentially causing health risks to the ecosystem and populations [14]. A pronounced inhibitory effect was observed on the growth of pea and cotton seedlings upon the addition of W at a high concentration [34]. Similarly, an ultra-high concentration of W can directly lead to the death of rye [35]. An epidemiological investigation showed a notable correlation between elevated W concentrations in human urine and the occurrence of diseases, including stroke, diabetes, peripheral arterial disease, and hyperthyroidism [23]. In animal experiments, Lindsay et al [36] observed that W could be enriched by snails and was mainly stored in their pancreas. Kelly et al [37] reported that W would damage the DNA of mice's bones. Inouye et al [38] compared the effects of W and Pb on earthworms and observed that W was less toxic considering the survival effect but more toxic to the reproduction system, thus indicating that W is a reproductive toxicant. In summary, W and its compounds can cause pronounced health risks to the environment, ecology, and human beings. Therefore, the scientific evaluation of this risk is extremely important. However, there is a limitation in our knowledge about the ecological risk of W because of the lack of its toxicity coefficient.
Therefore, the aims of this study were to: (1) calculate the toxicity coefficient of W based on Hakanson's theory; (2) verify the calculated results via a case study. The calculation of the W toxicity coefficient will contribute to extending the range of applications of the RI method.

Calculation of the toxicity coefficient of W
According to Hakanson's theory, the toxicity coefficient of heavy metals follows the rules of 'abundance principle' and 'release effect'. The 'abundance principle' reflects the heavy metals' harm to humans, and the 'release effect' reflects the harm to the aquatic ecosystem. Therefore, the abundance of each heavy metal in different media is extremely important for the calculation of the toxicity coefficient. In this study, except for the W, Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Mercury (Hg), Nickel (Ni), Lead (Pb), and Zinc (Zn) were also included in the calculation procedure, the reasons are: (1) it is impossible to calculate the toxicity coefficient of a single heavy metal in Hakanson's theory; (2) their toxicity coefficients of these selected elements have already been reported before [10,39] so that we can verify our calculation result by comparing with them; (3) these elements usually coexisted with W in the soil of a W mining area.

2.1.1.
Step 1: the abundance principle Table 1 shows the abundance of these nine heavy metals in igneous rocks, soil, freshwater, land plants, and land animals. Considering the improvement of monitoring technologies, updated data was adopted for the abundance of heavy metals in soil [39]. Nevertheless, the abundance in other media continues to be cited from Bowen's study [40], which was referred to in Hakanson's study [1], because of the lack of available updated data.
First, the element with the highest abundance in these five media was given a value of 1.00, and the other elements were modified according to their relative proportions. For example, in soil, Zn had the highest abundance and was 756.00 and 2.96 times greater than the abundance of Cd and Pb, respectively. As a result, the relative abundance of Zn, Cd, and Pb in soil is 1.00, 756.00, and 2.96, respectively. This method was used for modifying the relative abundance of the metals in other media, and the results are shown in table 2. Second, to counterbalance the effect of extreme 'relative abundance' which might add inappropriate weight to the total abundance, the maximum value (marked with an * ) of each metal in different media was omitted. Then, the 'relative abundance' values of the remaining four environmental media were summed to convey the total abundance. Finally, the 'average abundance' (last column of table 2) was obtained by dividing the total abundance of each metal by 4.43 (the smallest total abundance, Zn). The average relative abundances of these heavy metals were in the following order: Zn < Cu < Ni < Pb < As < Cd < Cr < W < Hg.

2.1.2.
Step 2: sink effect According to Hakanson's theory, the toxicity coefficient of a metal element is related to but not equivalent to the average abundance. The calculated average abundance can describe the 'sink effect' and interpret the depositional trend of heavy metals in sediments.
In this study, the 'sink effect' indicates the 'fingerprints' left by different pollutants on sediments. Their depositional behaviour follows different tendencies depending on several aspects, such as metal form, interactions among pollutants, and pH of the water system. 'Release factor' was used to describe the 'sink effect' and was calculated following equation (3): ( ) Release factor metal content in freshwater metal content in preindustrial sediments 3 = The release factors of the nine metals were calculated and shown in table 3. Its value of W was the smallest, indicating that W is more easily deposited into sediments than other heavy metals. Conversely, the release factor of Hg was the largest, indicating that Hg is more easily distributed in the water phase. The intensity of the release factors was in the following order: W < Cr < As < Zn < Pb < Ni < Cu = Cd < Hg.
We multiplied the average relative abundance of each heavy metal by the release factor to obtain the corrected abundance number, which is the co-embodiment of the 'abundance principle' and 'sink effect'. That is, a higher content of heavy metal in the environmental medium leads to more significant toxicity. Correspondingly, a larger release factor of heavy metals in sediments leads to more significant toxicity. Therefore, the corrected abundance number was used to demonstrate the initial toxicity coefficient of the heavy metals, which are listed in the fifth column of table 3. Table 3 shows that the initial toxicity coefficient of the heavy metals ranged from 57.10 to 516,480.00, which does not match the dimension of the pollution scale for heavy metals. Therefore, to obtain toxicity coefficients on a reasonable scale for convenient use, we assumed that the existing ranking of the initial toxicity coefficients would remain unchanged, then further processed the data as follows: First, the initial toxicity coefficient of each heavy metal was divided by the minimum obtained coefficient (Zn = 57.14) with the following results: As The above calculation process shows that the toxicity coefficient is influenced by the mutual effect of heavy metals. To confirm the definitive value of the toxicity coefficients of these nine heavy metals, the calculated toxicity coefficient of various elements in this study were compared with those of other studies (table 4).

Step 3: dimension problem and rationality principle
The data in table 4 shows that the absolute toxicity coefficients of As, Cd, Cr, Cu, Hg, Pb, and Zn in the three studies were almost the same (the maximum dispersion coefficient was 0.18 for Cr). The sorting and multiple relationships of the toxicity coefficient of each element were completely consistent, which indicates that the values calculated in this study were accurate. Therefore, we concluded that the toxicity coefficient of W is approximately 2, 1, 0.5, 0.5, and 0.25 times that of Zn, Cr, Pb, Cu, and As, respectively. As a result, the toxicity coefficient of W was set to 2.00 because the toxicity coefficient of Zn, Cr, Pb, Cu, and As was 1.00, 2.00, 5.00, 5.00, and 8.00, respectively, according to Hakanson's study [1]. In addition, W and Cr are homogenous elements with similar physical and chemical properties. Thus, it is reasonable for their toxicity coefficient to be identical. The data were cited from Bowen's study [40] unless noted.  [24,27,43]. All sediment samples were air-dried, ground, and sieved (0.15 mm) before the digestion analysis. For the analysis of Cd, Cr, Cu, Pb, W, and Zn, method 3035B of USEPA using hydrogen peroxide and nitric acids was applied to extraction and inductively coupled plasma mass spectrometry (ICP-MS, Agilent-8800, SureCycler) was used for detection. Correspondingly, for As and Hg, aqua regia was used for extraction, and atomic fluorescence spectrometer (AFS-9700, Beijing Haiguang Instrument Co., China) was used for detection.

Contamination assessment
In this study, E , r i RI, the Nemerow comprehensive pollution index (NCPI), and the geoaccumulation index (I geo ) were used to describe the level of pollution at the sampling sites.

I geo and NCPI
The I geo and NCPI were calculated using equations (4) and (5), respectively.

Comparison between RI and NCPI
As shown in figure 2, the pollution degree of Cd and Hg were pronounced, as they exceeded the background value by nearly 29.90 and 28.70 times, respectively. We can see that sampling sites #8 and # 15 were respectively identified as the most slight and severe polluted site according to both the RI and NCPI values. Moreover, as shown in figure 2, the trends of RI and NCPI in all sampling sites were almost consistent. Thus, it can be concluded that setting the W toxicity coefficient as 2.00 was reasonable.

Conclusions
The RI method was widely used for evaluating the degree of pollution caused by heavy metals. However, the lack of toxicity coefficient has limited the application of RI in the calculation of W pollution degree. In this study, the toxicity coefficient of W was systematically calculated based on Hakanson's theory. Subsequently, we calculated the E , r i RI, I geo , and NCPI values of sediment samples from 23 sites in Taojiang River near a W mining area as a case study. Comparative analysis was conducted between the E r i and I geo values of W, and the NCPI and RI values of eight heavy metals, respectively. All results indicated the rationality of the toxicity coefficient of W as 2.00. That is, this study extended the RI method to the assessment of W pollution, and it provides a practical basis for future ecological risk assessment of W in various environmental media, including sediment, soil, and the atmosphere.