Introduction

India ranks 177 out of 180 countries in the world with respect to environmental issues handling practices (Environmental Performance Index (EPI), 2018). According to World Air Quality Report 2018, out of the 10 highest polluted cities, 7 are present in India (Greenpeace South East Asia, 2018). Jharia Coalfield (JCF) present in Dhanbad, also known as “Coal Capital of India”, shares nearly 20% of the total coal production of the country (CIL n.d.) which falls under 43 critically polluted industrial clusters with the rank 13th due to its comprehensive environmental pollution index (CEPI) value 78.63 (Central Pollution Control Board). The occurrence of coal mine fire has a prolonged background of worldwide significance and has contributed to the loss of natural resources. It also has a strong detrimental effect on ecosystem as well as human health. Coal fires are now a problem worldwide; nevertheless, they are of significant concern in Asia, USA, China, South Africa, Australia, Indonesia, Turkey and Germany (Kuenzer et al. 2007; Kuenzer and Stracher 2012). JCF in India is comprised of 23 large underground and 9 large opencast mines. Mine fire became widespread in India after 1930, with the occurrence of several major fires in JCF and RCF (Raniganj coalfield) (BCCL 1991; Pandey et al. 2016). At present, more than 40 coal mines at 80 locations, covering an area of 10 km2, are experiencing active coal mine fire in JCF (NRSA 2006; CMPDIL, 2008). JCF fire is known to be one of the most challenging coal mine fire in the country which occurs as a result of spontaneous heating or endogenous coal fires, which rely on different mining, geological and environmental factors (Song et al. 2014). A number of physico-chemical processes are responsible for spontaneous combustion of coal seams and associated strata, such as temperature increase, mineral oxidation, smoke emission, changes in rock colour, formation and deposition of new materials on the surface and subsidence on the surface with multiple cracks (Guan and Van Genderen 1997; Zhang et al. 2004).

Mining activities are the leading cause of air pollution directly or indirectly in the coal mining areas (Baldauf 2001; Collins et al. 2001). Drilling, blasting, loading and unloading of coal, active and excessive coal mine fire hotspots, contribute significantly to air pollution (Ghose and Majee 2000a). Apart from these, mining and its associated activities like proximity to a railway siding, open burning of coal and heavy vehicular load are the major reasons for higher concentration of air pollutants around JCF (Dubey et al. 2012; Singh et al. 2014; Yadav et al. 2019). These sources ultimately lead to an increase in the concentration of particulate matter (Patra et al. 2016) and gaseous pollutants (SO2 and NOx) in the surrounding areas of coal mines (Tripathi and Gautam 2007) which adversely affect ambient air quality and thereby threaten the life of humans residing close to those areas (Gautam et al. 2016). Particulate matter has been considered group I contaminants by the International Agency for Research on Cancer (IARC 2013), and they are the conveyor of several trace elements such as As, Cd, Cr, Cu, Zn, Pb and Ni into the ambient air (Brunekreef and Holgate 2002).The trace elements are a small fraction of the total particulate matter (PM) mass, but they are sufficient to damage human health (Jena and Singh 2017). Trace elements concomitant as respiratory particles are found to increase heart and lung-related injuries in humans (Lee et al. 2005; Shaheen et al. 2005). Thus, trace elements are responsible for a wide variety of health issues. Previous studies have indicated that Pb and Cd could be probable carcinogens in human. In addition to carcinogenic outgrowth, Pb induces kidney failure, neuropathy and encephalopathy (ASTDR 1993; USEPA 1990), and Cd also interferes with proper kidney function (Park et al. 2004). Cr causes lung cancer (Mancuso 1975), skin ailments (Afridi et al. 2011; Pedersen 1982) and shows both teratogenic and human carcinogenic effects (Cr (VI)) (Danielsson et al. 1982; Iijima et al. 1983; Matsumoto et al. 1976). The toxicity of the elements and their obstinate existence makes it a primary concern for research (Hall 2002). Previous investigations carried out across the globe have revealed the composition of trace elements in atmospheric particulate matter (PM10) (Abulude et al. 2003; Banerjee 2003; Bhuyan et al. 2010; Feng et al. 2009; Karar et al. 2006; Leili et al. 2008; Limbeck et al. 2009; López et al. 2005; Senlin et al. 2007). Since trace elements share a correlation with various sources of anthropogenic origin, the trace elements have been used as a tracer to define the source of PM in various studies (Birmili et al. 2006; Weckwerth 2001). Trace elements have found application in various source apportionment studies (Basha et al. 2014; Roy et al. 2012; Gummeneni et al. 2011; Meena et al. 2016; Pathak et al. 2013; Shridhar et al. 2010). The JCF in Dhanbad has also been contaminated by several airborne heavy metals in the order of Fe > Cu > Zn > Mn > Cr > Cd > Pb > Ni due to its several mining activities, soil dust re-suspension, biomass burning and heavy transportation load (Dubey et al. 2012; Roy et al. 2012; Pandey et al. 2014). In Jharia coal mining areas of Dhanbad, several studies have been done which revealed that Dhanbad not only falls under critically polluted areas but also serves as cancer-prone area due to its chronic exposure to poor air quality caused by the active coal mine fire in the JCF (Roy et al., 2017). This study had been undertaken to estimate the ambient air quality concerning PM10, PM2.5, SO2, NOx and PM10-bound trace elements in the mine fire-affected and non-mine fire coal mining areas of Jharia Coalfield as well as to identify the possible sources of these atmospheric pollutants.

Materials and methods

Study area and its monitoring locations

JCF is located in the heart of the Damodar River Valley in the district of Dhanbad, Jharkhand, India. It is situated approximately 260 km northwest of Kolkata and 1150 km southwest of Delhi. JCF is limited between 23° 38′ 00″ N–23° 52′ 00″ N latitude and 86° 08′ 00″ E–86° 30′ 00″ E longitude. It stretches 38 km from east to west and 19 km from north to south, covering a geographical area of 450 m2 (380 km2 coal-bearing area).

A total of nine monitoring locations were selected based on coal mine fire and non-fire areas in JCF and depicted in Fig. 1 and discussed in Table 1 (as per sampling criteria IS: 5182 Part XIV). Monitoring at IIT (ISM) Dhanbad Campus was done as background site.

Fig. 1
figure 1

Map of the study area depicting monitoring locations

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Table 1 Studied sampling sites and their characteristics
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Monitoring frequency

The monitoring had been conducted on three consecutive seasons, i.e. summer, post-monsoon and winter. The monitoring for PM10, PM2.5, SO2 and NOx was done twice a week (for 24 h) at uniform intervals and for the trace elements (Pb, Zn, Cd, Cr, Mn, Cu, Fe and Ni) was done once in a month during the monitoring period. The details of the instruments and methods used for sampling and analysis are given in Table 2.

Table 2 Sampling instruments used during monitoring and the methods of analysis
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Results and discussion

Concentrations of particulate matter and gaseous pollutants

The ambient air concentrations of PM10, PM2.5, SO2 and NOx were monitored at nine sites of JCF and one reference site on three consecutive seasons, i.e. summer, post-monsoon and winter. The concentration levels of PM10, PM2.5, SO2 and NOx at ten selected monitoring locations during summer, post-monsoon and winter seasons are presented in Fig. 2. The results revealed a significant variation in pollutant concentrations (PM10, PM2.5, SO2 and NOx) in mining areas (mine fire and non-mine fire area) and institutional area in all the seasons.

Fig. 2
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Seasonal variation in concentration (μg/m3) of PM10 (a), PM2.5 (b), SO2 (c) and NOx (d) at ten monitoring sites

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The maximum PM10 concentration (547 μg/m3) was recorded at Lodhna Police Station (PS) (S3) during the winter followed by Tetulmari PS (S1) (532 μg/m3), Jogta 14 Pit (S7) (520 μg/m3), Bastacolla Colliery (S5) (513 μg/m3), Kujama Colliery (S9) (503 μg/m3), Katras (S8) (436 μg/m3), Kenduadih PS (S4), (424 μg/m3), Loyabad PS (S2) (413 μg/m3), Sijua Stadium (S6) (397 μg/m3) and IIT (ISM) Campus (S10) (82 μg/m3) (Fig. 2a). The concentration of PM10 in the ambient air of the ten selected sites varied between 0.71 and 547 μg/m3 being minimum and maximum at Lodhna PS and IIT (ISM) Dhanbad respectively.

The observed PM2.5 values of the studied sites were found in the range of 45 μg/m3 to 326 μg/m3 during winter (Fig. 2b). The ambient air of Lodhna PS and IIT (ISM) Dhanbad Campus exhibited the highest and lowest concentration of PM2.5 respectively during the period of monitoring. The concentrations of PM2.5 in the ambient air varied between 45 and 326 μg/m3 during winter, 37 and 275 μg/m3 during summer and 25 and 165 μg/m3 during post-monsoon. Lodhna PS (S3) is located at a distance of 2.2 km from Goluckdih opencast (OC) coal mine, experiencing highest concentration of particulate matter in all three seasons (445 ± 63 μg/m3 in summer, 375 ± 42 μg/m3 in post-monsoon and 547 ± 59 μg/m3 in winter respectively). Similarly, Tetulmari PS (S1), Bastacolla Colliery (S5), Jogta 14 Pit (S7) and Kujama Colliery (S9) experienced higher levels of particulate matter due to the active coal mine fire and other mining activities like crushing, grinding and abrasion of surfaces and also due to evaporation of sprays and re-suspension of dusts. Spontaneous combustion and unscientific exploitation of coal and other exogenous factors lead to the self-ignition of coal, which causes active coal mine fire in the coal mining areas and ultimately leads to the emission of particulate matter to a significant level. Average concentrations of PM10 were found maximum in the ambient air of Lodhna PS (S3) (455.67 μg/m3) during the whole period of monitoring, followed by Tetulmari PS (S1) (432.67 μg/m3), Bastacolla Colliery (S5) (425.33 μg/m3), Kujama Colliery (S9) (412.33 μg/m3), Jogta 14 Pit (S7) (408.67 μg/m3), Loyabad PS (S2) (343 μg/m3), Katras (S8) (338.67 μg/m3), Kenduadih PS (S4) (321.33 μg/m3), Sijua Stadium (S6) (313 μg/m3) and IIT (ISM) Dhanbad Campus (S10) (71 μg/m3). The ambient air of Lodhna PS (S3) also exhibited maximum average concentration of PM2.5 (255.33 μg/m3) during the monitoring period followed by Kujama Colliery (S9) (225 μg/m3), Tetulmari PS (S1) (210.67 μg/m3), Jogta 14 pit (S7) (206 μg/m3), Bastacolla Colliery (S5) (198 μg/m3), Loyabad PS (S2) (109 μg/m3), Katras (S8) (107 μg/m3), Sijua Stadium (S6) (104 μg/m3) and IIT (ISM) Campus (S10) (35.67 μg/m3). The concentration levels of particulate matter at Loyabad PS (S2), Kenduadih PS (S4), Sijua Stadium (S6) and Katras (S8) which are coal mining areas of JCF but not affected by mine fire were comparatively lower than the coal mining areas suffering from mine fire. The concentration of PM2.5 was found to be very concerning when compared with the permissible limits given by the National Ambient Air Quality Standards (NAAQS 2009) (Masih et al. 2019).

On an average, the concentration of particulate matter in post-monsoon as well as in summer and winter season remained almost the same (Fig. 2 a and b) because particulate matter once generated in summer or winter remains within the atmosphere for a long time following a non-linear process, and atmospheric precipitation in the monsoon does not seem to be effective for removing those particles from the atmosphere.

All the monitoring sites except the reference site (S10) had exceeded the value of NAAQS (2009) for particulate matter by a factor of 4.33 (S1), 3.43 (S2), 4.56 (S3), 3.21 (S4), 4.25 (S5), 3.13 (S6), 4.09 (S7), 3.39 (S8) and 4.12 (S9) respectively for PM10 and by a factor of 3.51 (S1), 1.82 (S2), 4.26 (S3), 1.89 (S4), 3.30 (S5), 1.73 (S6), 3.43 (S7), 1.78 (S8) and 3.53 (S9) respectively for PM 2.5.

According to the mechanism of pollutant dispersion, the topography and meteorological factors of the monitoring sites, the concentration level of particulate matter gets affected (Charron and Harrison 2005). So, the particulate matter (PM) during winter remained concentrated near the emitting source of the pollutants and did not dispersed at a greater distance due to lower temperatures and lower wind speed. On the other hand, higher wind speed and higher pollution dispersion were the major reason for comparatively lower atmospheric pollutants in summer. Particulate matter during the post-monsoon season got influenced by high relative humidity and washout by atmospheric precipitation, which reduced their concentration level during this season to some extent.

Apart from the particulate pollutants, a substantial variation in the spatial distribution of gaseous pollutants was also observed in the monitoring sites. There were significant variations in the concentration level of gaseous pollutants (SO2 and NOx) at the selected monitoring sites of Jharia Coalfield.

The ambient air SO2 concentrations were estimated in the range of 18.90 μg/m3 to141.67 μg/m3. Out of all the selected monitoring sites, the ambient air of Lodhna PS (S3) experienced the highest concentration of gaseous pollutants (SO2 and NOx) during the whole monitoring period (Fig. 2 c and d) (Supplementary Table A) because of the presence of surface and underground coal mines adjacent to the site which were highly affected by mine fire. Besides, four other sites like Tetulmari PS (S1), Bastacolla Colliery (S5), Jogta 14 pit (S7) and Kujama Colliery (S9) were present adjacent to coal mines affected by mine fire. Coal washeries and coke-oven plants were also present in the vicinity. These sites showed higher concentrations of gaseous pollutants (SO2 and NOx) which adversely contaminated the ambient air quality. In these coal mines, sulphur-rich coal releases sulphur dioxide into the atmosphere when it comes in contact with oxygen due to various mining activities or tectonic motions. At the same time, the coke-oven plants also release huge amounts of partially oxidized nitrogen by supplying oxygen to produce lesser by-products. These were the main reasons for the elevated level of gaseous pollutants in the monitoring sites like Lodhna (S3), Tetulmari PS (S1), Bastacolla Colliery (S5), Jogta 14 Pit (S7) and Kujama Colliery (S9). So, the emission of elevated levels of SO2 and NOx was an indicator of the higher level of pollution in the mining areas affected by mine fire. The concentration of gaseous pollutants was higher at all sites in winter in comparison with summer and post-monsoon seasons due to lower atmospheric dispersion of pollutants during winter.

Air quality of reference site IIT (ISM) Institutional Campus (S10) came under a satisfactory level (refer to Table 3) because it was devoid of any such mining or other industrial activities and is surrounded by Green Belt. Therefore, the concentration of pollutants was minimum in all three seasons monitored. All sites except the reference site (S10) showed a much higher concentration of gaseous pollutants than the NAAQS (2009) permissible limit.

Table 3 Air quality index of the studied monitoring sites
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Average concentration levels of SO2 were observed highest during the monitoring period at Lodhna PS (S3) (141.67 μg/m3), Tetulmari PS (S1) (128.63 μg/m3), Jogta 14 Pit (S7) (124 μg/m3), Bastacolla Colliery (S5) (122 μg/m3), Kujama Colliery (S9) (120.33 μg/m3), Kenduadih PS (S4) (85 μg/m3), Loyabad PS (S2) (81 μg/m3), Sijua Stadium (S6) (76.67 μg/m3), Katras (S8) (69.67 μg/m3) and IIT (ISM) Dhanbad Campus (S10) (18.90 μg/m3). The concentration levels of NOx in ambient air were seen highest at Lodhna PS (S3) (147.67 μg/m3) followed by Kujama Colliery (S9) (139 μg/m3), Tetulmari PS (S1) (136 μg/m3), Jogta 14 Pit (S7) (122.67 μg/m3), Bastacolla Colliery (S5) (121.67 μg/m3), Kenduadih PS (S4) (92.33 μg/m3), Loyabad PS (S2) (82.67 μg/m3), Sijua Stadium (S6) (75.83 μg/m3), Katras (S8) (69.63 μg/m3) and IIT (ISM) Campus (S10) (28.42 μg/m3).

Dhanbad has a tropical climatic pattern with lowest temperature (on an average 17 °C), lower sunlight and lower wind speed (on an average 2 km/h) during winter which causes poor dispersion of pollutants. So, the concentration of NOx was found highest in winter in comparison with summer and post-monsoon. Elevated levels of NOx in six mining sites may also be attributed due to the occurrence of active coal mine fire, vehicular transport of coal on heavy vehicles and other mining activities like drilling and blasting.

Overall, it has been recorded that at the monitoring sites of mine fire areas, i.e. Tetulmari PS (S1), Lodhna PS (S3), Bastacolla Colliery (S5), Jogta 14 Pit (S7) and Kujama Colliery (S9), higher values of particulate matter (PM10 and PM2.5) and gaseous pollutants (SO2 and NOx) were observed as compared with the monitoring sites of non-mine fire areas, i.e. Loyabad PS (S2), Kenduadih PS (S4), Sijua Stadium (S6) and Katras (S8). Emissions from mine fire-affected coal mines, coal washeries and coke-oven plants were the major reason for higher concentration of pollutants in the ambient air of those areas at JCF. Spatial distribution of the four major pollutants (PM10, PM2.5, SO2 and NOx) taking an average of all the three monitored seasons (summer, post-monsoon and winter) is depicted in Fig. 3.

Fig. 3
figure 3

Spatial distribution of PM10 (a), PM2.5 (b), SO2 (c) and NOx (d) at the selected monitoring sites

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Concentrations of trace elements

The seasonal variation in the concentration level of trace elements at ten selected monitoring sites is plotted in Fig. 4. The concentration of trace elements ranged from 2.88 to 8.35 μg/m3 (iron), 0.22 to 1.09 μg/m3 (zinc), 0.88 to 5.20 μg/m3 (copper), 0.17 to 2.87 μg/m3 (manganese), 0.02 to 0.04 μg/m3 (nickel), 0.02 to 0.07 μg/m3 (cadmium), 0.12 to 0.33 μg/m3 (chromium) and 0.04 to 0.34 μg/m3 (lead) (Supplementary Table B) at ten monitoring sites in the order of Fe > Cu > Mn > Zn > Pb > Cr > Cd > Ni (Supplementary Table B). The annual average concentration of trace elements was found highest in the coal mining areas of JCF, which were severely affected by coal mine fire like Lodhna (S3), Tetulmari PS (S1), Kenduadih PS (S5), Jogta 14 Pit (S7) and Kujama Colliery (S9). On an average, the concentrations of trace elements in PM10 were found higher in winter in comparison with summer and post-monsoon (Koukoulakis et al. 2019; Malandrino et al. 2013a, 2013b; Marcazzan et al. 2001; Prodi et al. 2009). This is due to the fact that winter in Dhanbad is characterized by low temperature, lower wind speed and thermal inversion in the stratosphere and ground-level fog. This caused poor dispersion of air pollutants and thus the particulate-borne trace elements accumulated at the source of their emission without being dispersed at a greater distance (Khare and Baruah 2010; Song et al., 2015; Padoan et al. 2016). This was the reason for the highest concentration of trace elements during winter in comparison with summer. Concentration of trace elements remained lowest in post-monsoon because the air pollutants were flushed out from the source of their emission by the atmospheric precipitation (rainfall) during post-monsoon. On the other hand, the values of Zn and Ni were found higher in summer and post-monsoon than winter which might be due to the influence of transportation and industrial activities at Dhanbad, which had lower strength during the winter season. Similar results were reported at Hisar in India and Bohai Rim in China as observed by Haritash and Kaushik (2007) and Zhang et al. (2014). Spatial distribution of the monitored trace elements (Fe, Zn, Cu, Mn, Ni, Cd, Cr, Pb) taking an average of all the three monitored seasons (summer, post-monsoon and winter) is depicted in Fig. 5.

Fig. 4
figure 4

Seasonal variations in concentration of trace elements like Fe (a), Zn (b), Cu (c), Mn (d), Ni (e), Cd (f), Cr (g) and Pb (h) at ten selected monitoring sites along with their standard deviation

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Fig. 5
figure 5

Spatial distribution of trace elements like Fe (a), Zn (b), copper (c), Mn (d) Ni (e), Cd (f), Cr (g) and Pb (h) at the monitoring sites

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Although leaded gasoline is not in use nowadays, re-suspension of lead (Pb)-rich dust due to heavy traffic load, coal mine fire and unscientific mining methods increases the concentration of Pb in the ambient air. As lead is one of the major elements present in Earth’s crust, mining activities lead to emission of higher levels of Pb in the ambient air (Cheng and Hu 2010). As the residence time and transport of lead (Pb) are co-related with atmospheric aerosols (U.S. ATSDR 2005), particulate matter (PM10) settles into the ambient air very quickly near the sources of their emission. This was the reason behind the higher level of emission of Pb in mining areas, and on the other hand, natural windblown dust and vehicular emission at the campus were the reason for a lower concentration of Pb at IIT (ISM) Dhanbad Campus.

Our results further specified that Fe, Cu, Mn and Zn were highest in concentration among all the trace elements in PM10. Higher concentration levels of iron (Fe) may be attributed to higher levels of Fe present in crustal abundance, which was present in loosely bound granular dust of coal mining areas (Mahowald et al. 2005). Also, as Fe and Zn are inter-related, the concentration of the trace metals in the ambient air was mainly related to the emission of fossil fuel combustion, incineration and also from natural origin (Manalis et al. 2005). As the institute campus was free of heavy vehicular transport and surrounded by lush green trees, the concentration of all the analysed trace elements was lowest there. The atmospheric trace elements found in the coal mining areas were primarily due to active mine fires, various coal mining activities and heavy vehicular transport across the mining region (Dubey et al. 2012).

Air quality index determination

A huge amount of data gets generated after regular monitoring at numerous sites cannot convey the air quality status to the various concerned people such as the scientific community, government officials, policymakers and most importantly to the general public in a simple manner, that is why determination of the ambient air quality of a specific region by estimation of air quality index (AQI) is considered to be an important tool.

AQI of the study area was calculated according to the National Air Quality Index guidelines given by Central Pollution Control Board (2014). This National AQI transforms complex air quality data of the pollutants into a single number (index value), nomenclature and colour to disseminate information on air quality and its associated health impacts in an easily understandable form for the common people. The pollutant concentration (Ip) values were calculated and the maximum Ip values were considered the AQI of an area according to the formula (Table 4).

$$ \mathrm{Ip}=\left[\left\{\left({I}_{\mathrm{HI}}\hbox{--} {I}_{\mathrm{LO}}\right)/\left({B}_{\mathrm{HI}}-{B}_{\mathrm{LO}}\right)\right\}\times \left(\mathrm{Cp}-{B}_{\mathrm{LO}}\right)\right]+{I}_{\mathrm{LO}} $$

where Ip is the sub-index, BHI is the breakpoint concentration greater than or equal to the concentration given, BLO is the breakpoint concentration less than or equal to the concentration given, IHI is the AQI value corresponding to BHI, ILO is the AQI value corresponding to BLO and Cp is the concentration of pollutants. Finally,

$$ \mathrm{AQI}=\max\ \left(\mathrm{Ip}\right), $$

where p = 1, 2, …, n denotes n pollutants.

Table 4 Rotated principal component loadings for particulate matter, gaseous pollutants and trace elements in the mine fire areas (a) and non-mine fire areas (b) of Jharia Coalfield
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The values of the AQI were calculated based on the method prescribed by CPCB (2014) of ten selected monitoring sites and are depicted in Fig. 6. The AQI values (as shown in Table 3) in the study area varied between a maximum of 407 and a minimum of 71. The values of AQI at Tetulmari PS (S1) and Lodhna PS (S3) were falling under severely polluted category due to their proximity to both underground and surface coal mining areas, rigorously affected by coal mine fire and heavy vehicular transportation of coal in the mines. The air quality of Bastacolla Colliery (S5), Jogta 14 Pit (S7) and Kujama Colliery (S9) were falling under very poor category due to the active mine fire and adjacent coal washeries as well as nearby coke-oven plants. The AQI values of Loyabad PS (S2), Kenduadih PS (S4), Sijua Stadium (S6) and Katras (S8) were falling under very poor category. The reason behind this is the burning of coal in the mining areas and heavy vehicular load in these regions. The air quality index of the mine fire-affected areas was nearly 1.5 times higher than the air quality index of non-mine fire areas of JCF. On the other hand, the air quality of IIT (ISM) Dhanbad (S10) falls under the category of satisfactory level because it is devoid of any such mining or industrial activities. From the AQI of all the studied sites, it was observed that the responsible air pollutants for the deterioration of ambient air quality were PM10 and PM2.5. The overall AQI of the study area reflects an image of a critically polluted area with considerable pollution load in Dhanbad.

Fig. 6
figure 6

Air quality index (AQI) of the ten monitoring sites

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Principal component analysis

Principal component analysis (PCA) with varimax rotation and Kaiser normalization had been performed in SPSS 16 to get a valid estimation of potential sources that contributed to the emission of atmospheric pollutants in the coal mining areas. In the coal mining areas affected by mine fire (Table 4a), three PCs with eigenvalues greater than 1.0 were extracted with 83.423% of the total variance in the entire data set. High loadings of PM10, PM2.5, SO2, NOx, Cu, Mn, Pb and Fe in PC1 indicated active coal mine fire, unscientific exploitation of coal, nearby coke-oven plants and allied mining activities as major sources. The maximum percent variance (50.187%) for this PC indicated that these sources were the main reasons for the emission of the atmospheric pollutants. SO2 was the indicator of active coal mine fire whereas NOx was the major pollutant emitted from mine fires as well as nearby coke-oven plants of the mining areas. In PC2, heavy vehicular loads in the mining areas were the significant sources of Cd and Cr as these two trace elements are emitted significantly from crude oil combustion and vehicular emissions (Tasdemir et al. 2006; Pandey et al. 2014). The PC3 with 15.419% of variance showed loadings of Zn and Ni which indicated that these two trace elements were emitted into the atmosphere mainly due to re-suspension of Earth’s crust or windblown dust (Quiterio et al. 2004). Three-dimensional factor loadings of the air pollutants (particulate matter, gaseous pollutants and trace elements) in mine fire areas of JCF are depicted in Fig. 7a.

Fig. 7
figure 7

Three-dimensional factor loadings of the studied air pollutants (particulate matter, gaseous pollutants and trace elements) in mine fire areas (a) and non-mine fire areas (b) of JCF

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Three PCs with eigenvalues greater than 1.0 were extracted with 79.579% of the overall variance of the analysed data of coal mining areas which were not affected by coal mine fire (Table 4b). High loadings of PM10, PM2.5, NOx, Cu and Mn, Pb and Fe in PC1 indicated point sources like the burning of coal in the mining areas as major sources. The maximum percent variance (46.659%) for this PC indicates that these sources are the major reasons for the emission of the atmospheric pollutants. In PC2, heavy vehicular load in the mining areas was the significant source of SO2, Cd and Cr as these three pollutants are emitted mainly from crude oil combustion and vehicular emissions (Äyräs and Kashulina 2000; Tasdemir et al., 2006; Pandey et al. 2014). SO2 was present in between cluster 2 and cluster 1 in the three-dimensional rotated space (Fig 7b), which indicated that SO2 had more than one significant source. The PC3 with 11.958% of variance showed loadings of Zn and Ni which indicated that these pollutants were emitted to the atmosphere mainly due to re-suspension of Earth’s crust or windblown dust (Quiterio et al. 2004).

Conclusions

The present study provided an idea of the current status of air pollutants like PM10, PM2.5, SO2, NOx and trace elements (Fe, Zn, Cu, Mn, Ni, Cd, Cr, Pb) in the coal mining areas of Jharia Coalfield. Significant seasonal and spatial variation of the air pollutants is depicted, which showed that the concentration level of the air pollutants was much higher in winter in the monitoring sites which were severely affected by active coal mine fire. The effect was due to the lower wind speed and lower atmospheric dispersion of pollutants during winter. PCA identified that active coal mine fire, nearby coke-oven plants and allied mining activities were the significant contributors of air pollutants in the coal mining areas affected by mine fire. SO2 was the indicator of active mine fire whereas NOx was the major pollutant emitted from mine fire as well as nearby coke-oven plants of the mining areas. Based on the AQI of the selected monitoring sites in Jharia Coalfield, it was observed that the AQI of mine fire areas was nearly 1.5 times higher than the AQI of non-mine fire areas. The overall AQI of the study area reflected an image of a critically polluted area with considerable pollution load. Advanced mining technology should be adopted to mitigate active mine fires and reduce the emission of toxic air pollutants. The outcome of this study lays down the framework for formulating a proper scheme for necessary preventive measures.