Distribution of metals in dustfall in copper mining area
The geometric mean (GM) concentrations of As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn was 47.9, 1.01, 13.4, 154.8, 1141.4, 32113, 385.1, 38.9, 99.7 and 526.2 mg/kg during the summer season. While in case of winter season the geometric mean concentrations were found to be 37.4, 0.80, 10.9, 140.4, 968.4, 20642, 355.0, 29.1, 83.6 and 495.5 mg/kg as shown in Table 3. The order of the metal concentration was found as Fe > Cu > Zn > Mn >Cr >Pb > As >Ni > Cd> Co during both the seasons. The metal concentrations were observed to be generally higher at the locations of Benasol and Ghatsila. Both the locations are in vicinity to existing or abandoned copper mining and mills area and also under the influence of heavy vehicular load.
Distribution of metals in dustfall in Iron mining area
The geometric mean concentrations of As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn was 53.4, 0.77, 4.1, 158.1, 240.2, 124923, 689.0, 25.3, 156.5 and 446.6 mg/kg during the summer season (Table 3). While in case of winter season the geometric mean concentrations was found to be 53.1, 0.55, 3.7, 116.0, 162.1, 79487, 557.1, 22.0, 118.9 and 383.2 mg/kg. The order of the metal concentration was found as Fe > Mn> Zn >Cu >Cr >Pb > As >Ni > Co >Cd during both the seasons. The concentrations of metals were observed to be generally higher at the locations of Hathigate and Barajamda which were under heavy vehicular load. Both the locations were situated in close vicinity to Iron and Manganese mining areas.
For almost all metals, metal concentrations in the dustfall for both study areas exceeded the average metal concentration in the shale (Turekian and Wedepohl 1961). The study areas are characterised by the presence of metal bearing formations influenced by extensive mining and industrial activities and thus high metal levels can be anticipated in atmospheric dust (Preston and Chester 1996). However, the increase in concentration was more noticeable for Cu, Pb and Zn for copper mining areas and for Fe, Pb and Zn for iron mining areas.
For both the study areas, the dustfall rate was higher in summer as compared to winter which may be attributed to the meteorological factors. The high wind strength at higher temperature range and low relative humidity in summer months is responsible for erosion of earth crust which results in increased levels of coarse crustal metals in the atmospheric dust as coarse particles tends to get settled down due to gravity (Singh and Mondal 2008; Mondal et al. 2010; Moja and Mnisi, 2013). The high humidity and low temperature during the winter result in stable condition which encourages the long-lasting life of atmospheric particles in the environment, entrapping them and preventing their free fall. The average dustfall rates in summer and winter for the copper mining areas were 20.5 and 15.9 g/m2/month, respectively, while for iron mining areas the dust fall rates were 37.2 and 34.5 g/m2/month, respectively.
The concentrations of metals in the dustfall were also higher in the summer season than the winter season that can be attributable to the meteorological conditions and anthropogenic activities. In the summer the relative humidity is lower which results in lower moisture content of the soil which facilitates the mobilization of the soil particles that is rich in metals (Tanushree et al. 2011). Moreover, the mining activities are higher during the summer as compared to the winter which may also be considered a reason for the high concentrations of the metals related to the mining during the summer (Vega et al. 1998).
Comparison of metals in dustfall of the study area with other studies
A comparison of metals in the atmospheric dust of the present study with other studies is provided in Table 4. The table suggest that for most of the considered metals, the concentrations in the east and west Singhbhum areas were higher than other areas of India and worldwide. This may be attributed to the high mineralisation of the study areas along with extensive mining and other industrial activities. However, differences in the metal concentration in the free fall dust of different areas are obvious due to differences in geographic settings, traffic arrangements, and the type of industries that run across the area.
Metal fluxes of atmospheric dustfall
Seasonal and spatial variations were observed for most of the metals in both the study areas considering the metal fluxes (Table 5). The metal fluxes were higher in summer than winter considering the seasons which is in accordance to other studies (Rout et al. 2014). This may be attributed to the high dustfall and high metals concentration in dustfall during the summer as compared to winters. Also, the flux was higher in the mining and industrial sites as compared to the control site for most of the considered metals. Considering both the mining areas, significant differences were observed for Cu, Fe, Mn and Cr with higher Cu flux being observed in copper mining areas and Fe, Mn and Cr observed to be higher in iron mining areas. The results are in accordance to the related mining activities in both the mining areas. The sequence of the metal flux was found as Fe>Cu>Zn>Mn>Cr>Pb>As>Ni>Cd>Co in copper mining area while in case of iron mining areas, the order was observed to be Fe>Mn>Zn>Cu>Cr >Pb>As>Ni>Co>Cd.
Assessment of contamination indices with respect to metals of atmospheric dustfall
Large variations were observed in the Igeo for the metals in both the study areas as metals widely varied from class 0 to class 6 indicating large spatial variations; representing the background status for some metals to extremely polluted status for others (Table 6). Largest variation was observed for Cu in the copper mining areas for which the Igeo values ranged from 1.66 to 6.90; thus falling under the Igeo class of 2–6, i.e., moderately polluted to extremely polluted status. As, Cd, Zn and Pb showed moderate to high contamination in the dustfalll of the area. In case of iron mining area, Cu, Fe, Pb and Zn depicted moderately to highly polluted status according to Igeo classification.
The analysis of the enrichment factor showed significant to extremely high Cu contamination in the atmospheric dustfall of the copper mining area for all the sites (Table 7). Moderate to high contamination was depicted for Pb, Zn, As and Cd as per calculated EF. For the iron mining areas, enrichment factor suggested lower contamination than copper mining areas. Significant contamination was observed for As, Cd and Pb at few samples while the other metals had no to moderate contamination as per EF classification.
The contamination factor (CF), revealed that Cu had the highest contamination in the dust samples considering the copper mining area while in case of iron mining area, the highest CF was calculated for Pb. The sequence of CF for the different metals were in the order of Cu < Pb < Ni < As < Cd < Zn< Cr < Fe < Co < Mn and Pb <Zn < Cu< As < Fe < Mn < Cd < Cr < Ni < Co for copper and iron mining areas, respectively (Table 7). PLI was determined to study the cumulative effect of the metals analyzed, ranged from 1.04 to 3.33 for the copper mining area advocating moderate to extremely heavy pollution for the area. The range of PLI for iron mining area was 0.94 to 2.63 suggesting no pollution to heavy pollution status of the locations. The average PLI values in the study areas were estimated to be 1.99 and 1.75, respectively for copper and iron mining areas.
Thus, the findings, based on EF, Igeo, CF, and PLI, confirm that metal contamination in the copper mining area ranges from moderate to severe, with Cu, Pb and Zn being the metals of greatest concern. The locations closest to Cu mining and processing operations have the highest levels of pollution. However, in iron mining area is moderately to extremely serious with Cd, Pb and Zn being the metals with most concern.
Statistical source apportionment
The Pearson’s correlation coefficients of the metals in the dustfall samples of the copper and iron mining area are depicted in Table 8. Considering the copper mining areas, there was a strong positive correlation (p < 0.01) for As with Cd, and Fe; Co with Cu and Ni; Cr with Ni, Pb and Zn; Cu with Ni; Fe with Mn and Pb with Zn. The positive correlations between Cu, Co and Ni indicated a possibility of a common source which may be derived from mining and processing of copper ores. For iron mining areas, significant positive association were seen (p < 0.01) for Cd with Co; Cr with Fe, Mn and Zn; Cu with Fe, Ni and Pb; Fe with Mn and Zn; Ni with Pb and Zn; Pb with Zn. Positive associations between Fe, Mn, and Cr may be a suggestive of a possible shared source originating from iron ore mining and processing (Chen et al. 2014).
Principal component analysis
Principal component analysis (PCA) was carried out on the heavy metal data of the atmospheric dust samples in order to obtain significant interrelationships and to reduce the dimensionality of the dataset, since a few of the new components could explain the major variance in the data. It also helps in assigning source identity to each one of the PCs (Miller and Miller 2000).
For metals data of dustfall of copper mining area PCA was performed and four principal components were extracted explaining 91.1% of total variance (Table 9). According to the loading factors, the first principal component (PC-1) was associated with Co, Cu and Ni explaining 30.9% of the total variance. The factor may be attributed seems to the extensive copper mining and processing industries since Ni and Co are associated with copper deposits (Ikenaka et al. 2010). The second component (PC-2) explained 25.9 % of total variance and have considerable factor loading for Cr, Pb and Zn. Vehicular and industrial emissions can be attributed to this factor. The increase in concentration of Pb in the environment is identified to be associated to human made activities such as industrial uses, waste incineration, coal burning, etc. (Cheng and Hu 2010). Zinc is used in a wide variety of materials including galvanizing on iron products, in alloys, in rubber, glazes, enamels, paper and glass (Belliles 1978). Environmental pollution with various forms of Cr results from its numerous uses in the chemical industry, production of dyes, wood preservation, leather tanning, chrome plating, manufacturing of various alloys and many other applications and products (Alimonti et al. 2000; ATSDR 2000). All the 3 metals; Cr, Zn and Pb are associated with vehicular sources also. The wearing down of vehicular brake linings and the use of catalytic converters represents vehicular source of chromium (Fishbein 1981). Lead is used for batteries, fuel tanks, solder, seals, bearings, and wheel weights (Sander et al. 2000; Lohse et al. 2001; USDI 2003). Lead also comes from the wear of tyres since Pb oxide is used as filler materials in some overseas makes of tyres (Sharheen 1975). As Zn is used as a vulcanization agent in vehicle tyres (Alloway 1990) and the higher wearing rate at the high temperature in the area may contribute to the high Zn content in the dust (Davis et al. 2001). Zn is used as minor additive to gasoline and various auto lubricants and released during combustion and spillage (Ipeaiyeda and Dawodu 2008). The third and fourth factors (PC-3 and PC-4) having high loadings for As, Cd, Fe and Mn explicated 34.3% of the variance in combination and the possible source appeared to be associated to the earth’s crust and geology of the study area.
The PCA performed on the metal data of the dustfall samples from iron mining areas resulted in extraction of three principal components were extracted explaining 75.0 % of total variance (Table 9). The first principal component (PC-1) was associated with Cu, Ni, Pb, and Zn, accounting for 29.7% of the total variance. It may be related to vehicular and industrial emissions in the study area. The second component (PC-2) explained 25.5 % of total variance, as seen by significant factor loading for Cr, Fe and Mn. This factor may be due to the iron ore mining and related activities. The third factor (PC-3), explained 19.8% of the variance with high loadings for As Cd and Co can be related to the geogenic origin.
Human health risk from metals exposure through atmospheric dustfall
Human health risk was estimated by calculating Hazard Quotients (HQ) and Hazard Index (HI) for the considered metals for both summer and winter season. If HQ and HI are greater than unity then considerable risk may be anticipated on the human health. The HQ and HI values considering the pathway of ingestion has been depicted in Supplementary Table 2 taking into account both the adult and child populations. The HQs for all the metals irrespective of the pathways were <1 for adult population, suggesting that the metals posed little hazard individually for adult for both the study areas. However, for the sensitive child population, the HQs of As through the ingestion pathway were higher than one in copper mining area, thus predicting risk for the child populace during both the season. Moreover, in the iron mining area HQs of As and Fe through the ingestion pathway were higher than unity thus predicting risk for the child group during both seasons. The uppermost contributors to non-cancer chronic risks via the ingestion route were As, Cr, Fe, Co and Cu in the copper mining area (Fig. 2) where as in case of iron mining area, the uppermost contributors of risks via the ingestion route were As, Fe, Cr, Pb and Mn (Fig. 3). Considering the cumulative risk of metals, HI through ingestion pathway (HIing) for child populace is evaluated to be 4.48 and 3.60 in the copper mining area and 6.00 and 4.79 in the iron mining area during summer and winter seasons, respectively suggesting substantial risk. The HIing for adults of West Singhbhum area is also impending 1 (0.939) during the summer season, suggesting a likelihood of non-carcinogenic risk in the near future. The overall HI for the study area, taking into account the ten metals and the three pathways were evaluated during the summer and winter seasons for the adult and child population, respectively (Supplementary Table 3). The HI of the other 2 routes i.e. dermal contact and inhalation risk are negligible as compared to the ingestion pathway. Accordingly, it can be implied that the oral intake of the dust was the primary exposure pathway.