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Correlation and time-series analysis of black carbon in the coal mine regions of India: a case study

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Abstract

In recent times, black carbon (BC) has attracted the interest of the researchers due to its adverse effect on human health, climate, rainfall, and global heating causing the melting of ice in the poles due to carbon deposition on it. Coal industry is the backbone of Indian economy and India being the world’s third largest producer of coal. Various mining activities are leading to spontaneous emission of black carbon in the atmosphere, especially in the IGP (Indo-Gangetic plain) region. Long-term studies related to black carbon emission in the coal regions of India are very rare. In the present study, a long-term datum of 38 years (1980–2018) for the amount of black carbon emission among the three important coal mines of India, namely Bokaro, Jharia, and Raniganj, is studied using correlation analysis, and time-series analysis along with a few other mathematical parameters. The comparison and forecast obtained using this study will be beneficial in the upcoming years, so as to gather the interest of the government, NGOs, and researchers in this area, so that new policies and preventive measures could be taken to curtail the black carbon concentration from the coal mines.

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References

  • Abdel-Aziz A, Frey HC (2003) Development of hourly probabilistic utility NOx emission inventories using time series techniques: part I—univariate approach. Atmos Environ 37(38):5379–5389

    Google Scholar 

  • Atkinson RW, Cohen A, Mehta S, Anderson HR (2012) Systematic review and meta-analysis of epidemiological time-series studies on outdoor air pollution and health in Asia. Air Qual Atmos Health 5(4):383–391

    Google Scholar 

  • Attah DA, Bankole GM (2012) Time series analysis model for annual rainfall data in lower Kaduna catchment Kaduna, Nigeria. Int J Res Chem Environ 2(1):82–87

    Google Scholar 

  • Babu SS, Moorthy KK (2002) Aerosol black carbon over tropical coastal station in India. Geophys Res Lett 29(23):2098

    Google Scholar 

  • Balakrishnan K, Ganguli B, Ghosh S, Sambandam S, Roy SS, Chatterjee A (2013) A spatially disaggregated time-series analysis of the short-term effects of particulate matter exposure on mortality in Chennai, India. Air Qual Atmos Health 6(1):111–121

    Google Scholar 

  • Bond TC, Streets DG, Yarber KF, Nelson SM, Woo JH, Klimont Z (2004) A technology-based global inventory of black and organic carbon emissions from combustion. J Geophys Res 109:D14203. https://doi.org/10.1029/2003JD003697

    Article  Google Scholar 

  • Box GEP, Jenkins GM (1976) Time Series Analysis: Forecasting and Control. Wiley, New York, pp 1–712

    Google Scholar 

  • Chambers JM, Cleveland WS, Kleiner B, Tukey PA (1983) Graphical methods for data analysis. CRC Press, Taylor & Francis Group, Wadsworth

    Google Scholar 

  • Chaulya SK, Chakrabarty MK (1995) Perspective of new national mineral policy and environmental control for mineral sector. In: GS Khuntia (Ed) Proceeding of National Seminar on Status of Mineral Exploitation in India New Delhi India 174–123

  • Dimakopoulou K, Gryparis A, Katsouyanni K (2017) Using spatio-temporal land use regression models to address spatial variation in air pollution concentrations in time series studies. Air Qual Atmos Health 10(9):1139–1149

    Google Scholar 

  • Fang H, Wang X, Lou L, Zhou Z, Wu J (2010) Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques. Water Res 44(5):1562–1572

    Google Scholar 

  • Ganguly D, Jayaraman A, Rajesh TA, Gadhavi H (2006) Winter time aerosol properties during foggy and non-foggy days over urban center Delhi and their implications for shortwave radiative forcing. J Geophys Res 111:D15217

    Google Scholar 

  • Gautam S, Patra AK (2016) Occupational exposure to particulate matter in three Indian opencast mines. Air Qual Atmos Health 9(2):143–158

    Google Scholar 

  • Guttikunda SK, Kopakka RV (2014) Source emissions and health impacts of urban air pollution in Hyderabad, India. Air Qual Atmos Health 7(2):195–207

    Google Scholar 

  • Haque MI, Nahar K, Kabir MH, Salam A (2018) Bangladesh. Air Qual Atmos Health 11(8):925–935

    Google Scholar 

  • Highwood JE, Kinnersley RP (2006) When smoke gets in our eyes: the multiple impacts of atmospheric black carbon on climate, air quality and health. Environ Int 32(4):560–566

    Google Scholar 

  • Horvath H (1993) Atmospheric light absorption—a review. Atmos Environ Part A General Top 27(3):293–317

    Google Scholar 

  • Jacobson MZ (2010) Short term effects of controlling fossil fuel soot, biofuel soot and gases, and methane on climate, arctic ice, and air pollution health. J Geophys Res 115:D14209

    Google Scholar 

  • Jansen KL, Larson TV, Koenig JQ, Mar TF, Fields C, Stewart J, Lippmann M (2005) Associations between health effects and particulate matter and black carbon in subjects with respiratory disease. Environ Health Perspect 113:1741–1746

    Google Scholar 

  • Japar SM, Brachaczek WW, Gorse RA, Norbeck JM, Pierson WR (1986) The contribution of elemental carbon to the optical properties of rural atmospheric aerosols. Atmos Environ 20(6):1281–1289

    Google Scholar 

  • Kisi O, Parmar KS, Soni K, Demir V (2017) Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models. Air Qual Atmos Health 10(7):873–883

    Google Scholar 

  • Kumar M, Parmar KS, Kumar DB, Mhawisha A, Broday DM, Malla RK, Banerjeea T (2018) Long-term aerosol climatology over Indo-Gangetic Plain: Trend, prediction and potential source fields. Atmos Environ 180:37–50

    Google Scholar 

  • Latha KM, Badarinath KVS (2005) Seasonal variations of black carbon aerosols and total aerosol mass concentrations over urban environment in India. Atmos Environ 39(22):4129–4141

    Google Scholar 

  • Li M, Zhou M, Yang J, Yin P, Wang B, Liu Q (2019) Temperature, temperature extremes, and cause-specific respiratory mortality in China: a multi-city time series analysis. Air Qual Atmos Health 12(5):539–548

    Google Scholar 

  • Liousse C, Penner JE, Chuang C, Walton JJ, Eddleman H, Cachier H (1996) A global three-dimensional model study of carbonaceous aerosol. J Geophys Res 101(14):19411–19432

    Google Scholar 

  • Lu WX, Zhao Y, Chu HB, Yang LL (2014) The analysis of groundwater levels influenced by dual factors in western Jilin Province by using time series analysis method. Appl Water Sci 4(3):251–260

    Google Scholar 

  • Menon S, Hansen JE, Nazarenko L, Luo Y (2002) Climate effects of black carbon aerosols in China and India. Science 297(5590):2250–2253

    Google Scholar 

  • Parmar KS, Bhardwaj R (2013a) Water quality index and fractal dimension analysis of water parameters. Int J Environ Sci Technol 10(1):151–164

    Google Scholar 

  • Parmar KS, Bhardwaj R (2013b) Wavelet and statistical analysis of river water quality parameters. Appl Math Comput 219(20):10172–10182

    Google Scholar 

  • Parmar KS, Bhardwaj R (2014) Water quality management using statistical analysis and time-series prediction model. Appl Water Sci 4:425. https://doi.org/10.1007/s13201-014-0159-9

    Article  Google Scholar 

  • Parmar KS, Bhardwaj R (2015) Statistical, time series, and fractal analysis of full stretch of river Yamuna (India) for water quality management. Environ Sci Pollut Res 22(1):397–414

    Google Scholar 

  • Penner JE, Eddleman H, Novakov T (1993) Towards the development of a global inventory for black carbon emissions. Atmos Environ 27(8):1277–1295

    Google Scholar 

  • Prasad B, Kumari P, Bano S, Kumari S (2013) Ground water quality evaluation near mining area and development of heavy metal pollution index. Appl Water Sci 4:11–17

    Google Scholar 

  • Ramanathan V, Carmichael G (2008) Global and regional climate changes due to black carbon. Nat Geosci 1:221–227

    Google Scholar 

  • Ramanathan V, Chung C, Kim D, Bettge T, Buja L, Kiehl JT, Washington WM, Fu Q, Sikka DR, Wild M (2005) Atmospheric brown clouds: impacts on South Asian climate and hydrologic cycle. Proc Natl Acad Sci USA 102(15):5326–5333

    Google Scholar 

  • Rojano RE, Manzano CA, Toro RA, Morales RGE, Restrepo G, Leiva-Guzman MA (2018) Potential local and regional impacts of particulate matter emitted from one of the world’s largest open-pit coal mines. Air Qual Atmos Health 11(5):601–610

    Google Scholar 

  • Seth R, Singh P, Mohan M, Singh R, Aswal RS (2013) Urban pond water contamination in India. Appl Water Sci 3:717–720

    Google Scholar 

  • Sharma S, Lavoue D, Cachier H, Barrie LA, Gong SL (2004) Long-term trends of the black carbon concentrations in the Canadian Arctic. J Geophys Res 109:D15203. https://doi.org/10.1029/2003JD004331

    Article  Google Scholar 

  • Singh KP, Malik A, Mohan D, Sinha S (2004) Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Res. 38:3980–3992

    Google Scholar 

  • Sirois A (1997) Temporal variation of oxides of sulphur and nitrogen in ambient air in eastern Canada: 1979–1994. Tellus Ser B 49(3):270–291

    Google Scholar 

  • Soni K, Kapoor S, Parrmar KS (2014) Long-term aerosol characteristics over eastern, southeastern and south coalfield regions in India. Water Air Soil Pollut 225:1832

    Google Scholar 

  • Soni K, Parmar KS, Kapoor S (2015) Time series model prediction and trend variability of aerosol optical depth over coal mines in India. Environ Sci Pollut Res 22(5):3652–3671

    Google Scholar 

  • Stracher GB, Taylor TP (2004) Coal fires burning out of control around the world: thermodynamic recipe for environmental catastrophe. Int J Coal Geol 59(1):7–17

    Google Scholar 

  • Su S, Li D, Zhang Q, Xiao R, Huang F, Wu J (2011) Temporal trend and source apportionment of water pollution in different functional zones of Qiantang River, China. Water Res 45(4):1781–1795

    Google Scholar 

  • Tsakiri KG, Zurbenko IG (2011) Prediction of ozone concentrations using atmospheric variables. Air Qual Atmos Health 4(2):111–120

    Google Scholar 

  • Twomey SA, Piepgrass M, Wolfe TL (1984) An assessment of the impact of pollution on global cloud albedo. Tellus B 36(5):356–366

    Google Scholar 

  • Tzanis C, Varotsos CA (2008) Tropospheric aerosol forcing of climate: a case study for the greater area of Greece. Int J Remote Sens 29(9):2507–2517

    Google Scholar 

  • Varotsos CA, Chronopoulos GJ, Katsikis S, Sakellariou NK (1995) Further evidence of the role of air pollution on solar ultraviolet radiation reaching the ground. Int J Remote Sens 16(10):1883–1886

    Google Scholar 

  • Venkataraman C, Habib G, Eiguren-Fernandez A, Miguel AH, Friedlander SK (2005) Residential biofuels in South Asia, Carbonaceous aerosol emissions and climate impacts. Science 307(5714):1454–1456

    Google Scholar 

  • Wang C (2004) A modeling study on the climate impacts of black carbon aerosols. J Geophys Res 109(D3):DO3106

Download references

Acknowledgements

The authors are thankful to CSIR-National Physical Laboratory, New Delhi for providing the data for research. We also grateful to Lovely Professional University, Punjab, I. K. Gujral Punjab Technical University, Jalandhar for providing facilities for research work. Author would also like to thank NASA website (https://nasa.gov/) for processing of data.

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Authors and Affiliations

  1. Department of Mathematics, School of Chemical Engineering and Physical Sciences, Lovely Professional University, Phagwara, Punjab, 144411, India

    Sidhu Jitendra Singh Makkhan & Sachin Kaushal

  2. Department of Mathematics, I K Gujral Punjab Technical University, Jalandhar, Punjab, 144603, India

    Kulwinder Singh Parmar

  3. Department of Mathematics, Sri Guru Angad Dev College, Khadoor Sahib, Tarn Taran, Punjab, 143117, India

    Sidhu Jitendra Singh Makkhan

  4. CSIR-National Physical Laboratory, New Delhi, 110012, India

    Kirti Soni

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  1. Sidhu Jitendra Singh Makkhan
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  2. Kulwinder Singh Parmar
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  4. Kirti Soni
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Correspondence to Kulwinder Singh Parmar.

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Makkhan, S.J.S., Parmar, K.S., Kaushal, S. et al. Correlation and time-series analysis of black carbon in the coal mine regions of India: a case study. Model. Earth Syst. Environ. 6, 659–669 (2020). https://doi.org/10.1007/s40808-020-00719-8

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