Skip to main content
SpringerLink
Log in

Evaluating Dispersion Modeling of Inhalable Particulates (PM10) Emissions in Complex Terrain of Coal Mines

  • Published:
Environmental Modeling & Assessment Aims and scope Submit manuscript

Abstract

The dispersion of inhalable particulates (PM10) in opencast mines needs to be identified precisely for controlling its atmospheric concentration. To date, misrepresented terrains in dispersion models resulted in over/under-estimated predictions. The present study aimed to model the dispersion of PM10 in coal mines using AERMOD and assess outcomes rendered by disparate digital elevation models (DEM). CartoDEM (10 m) generated using the rational polynomial coefficient method and publically available DEMs, i.e., SRTM (90 m), ASTER (30 m), CartoDEM (30 m), and FLAT, were processed for simulating complex terrain of coal mines. Modeled concentration predicted using different terrain inputs was compared with field measured values for evaluating performance metrics. This comparison suggested that SRTM and FLAT topography met lesser performance criteria in comparison with other input DEMs. The model performance was evaluated using Willmott’s index of agreement (dr) being 0.39, 0.41, and 0.47 for SRTM, ASTER, and CartoDEM, respectively. However, CartoDEM (10 m) showed a slight improvement with dr of 0.57. The results revealed that model performance improved due to the recentness of DEM rather than its resolution. Overburden dump, haulage routes, and railway siding shared the majority PM10 concentration load invariably in all model runs where peak concentration varied from 454 to 680 µg/m3. Categorically, complex terrain simulations of coal mines influenced dispersion models by altering emission sources’ interaction with pre-processor calculations of meteorological data. The work will help improve the performance of models in complex terrain and the selection of topographic parameterization for risk-based decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

References

  1. Heal, M. R., & KumarHarrison, & R. M., P. (2012). Particles, air quality, policy and health. Chemical Society Reviews, 41, 6606–6630.

    Article  CAS  Google Scholar 

  2. Kumar, P., Morawska, L., Birmili, W., Paasonen, P., Hu, M., Kulmala, M., et al. (2014). Ultrafine particles in cities. Environment International, 66, 1–10.

    Article  CAS  Google Scholar 

  3. Lal, B., & Tripathy, S. S. (2012). Prediction of dust concentration in open cast coal mine using artificial neural network. Atmospheric Pollution Research, 3, 211–218.

    Article  CAS  Google Scholar 

  4. Pandey, B., Agrawal, M., & Singh, S. (2014). Assessment of air pollution around coal mining area: Emphasizing on spatial distributions, seasonal variations and heavy metals, using cluster and principal component analysis. Atmospheric Pollution Research, 5, 79–86. https://doi.org/10.5094/APR.2014.010

    Article  CAS  Google Scholar 

  5. Patra, A. K., Gautam, S., & Kumar, P. (2016). Emissions and human health impact of particulate matter from surface mining operation—A review. Environmental Technology & Innovation, 5, 233–249.

    Article  Google Scholar 

  6. Gautam, S., Prusty, B. K., & Patra, A. K. (2015). Dispersion of respirable particles from the workplace in opencast iron ore mines. Environmental Technology & Innovation, 4, 137–149.

    Article  Google Scholar 

  7. Sahu, S. P., Patra, A. K., & Kolluru, S. S. R. (2018). Spatial and temporal variation of respirable particles around a surface coal mine in India. Atmospheric Pollution Research. https://doi.org/10.1016/j.apr.2018.01.010

    Article  Google Scholar 

  8. USEPA (2009). Integrated science assessment for particulate matter. National Center for Environ- mental Assessment — RTP Division.

  9. WHO (2005). http://apps.who.int/iris/bitstream/10665/69477/1/WHO_SDE_PHE_OEH 06. 02_eng.pdf

  10. Roy, S., Adhikari, G. R., Renaldy, T. A., & Jha, A. K. (2011). Development of multiple regression and neural network models for assessment of blasting dust at a large surface coal mine. Journal of Environmental Science and Technology, 4, 284–301.

    Article  CAS  Google Scholar 

  11. USEPA (2012). User's Guide for the AMS/EPA Regulatory Model—AERMOD. EPA-454/B-03–001, September 2004 (Addendum).

  12. Haichao, W., Wenling, J., Lahdelma, R., Pinghua, Z., & Shuhui, Z. (2013). Atmospheric environmental impact assessment of a combined district heating system. Building and Environment, 64, 200–212.

    Article  Google Scholar 

  13. Huertas, J. I., Huertas, M. E., Izquierdo, S., & González, E. D. (2012). Air quality impact assessment of multiple open pit coal mines in northern Colombia. Journal of Environmental Management, 93, 121–129.

    Article  CAS  Google Scholar 

  14. Huertas, J. I., Camacho, D. A., & Huertas, M. E. (2012). Standardized emissions inventory methodology for open-pit mining areas. Environmental Science and Pollution Research, 19, 2784–2794.

    Article  CAS  Google Scholar 

  15. Ma, J., Yi, H., Tang, X., Zhang, Y., Xiang, Y., & Pu, L. (2013). Application of AERMOD on near future air quality simulation under the latest national emission control policy of China: a case study on an industrial city. Journal of Environmental Sciences, 25, 1608–1617.

    Article  CAS  Google Scholar 

  16. Bajwa, K. S., Arya, S. P., & Aneja, V. P. (2008). Modeling studies of ammonia dispersion and dry deposition at some hog farms in North Carolina. Journal of Air and Waste Management, 58, 1198–1207.

    Article  CAS  Google Scholar 

  17. Olafsdottir, S., Gardarsson, S. M., & Andradottir, H. O. (2014). Spatial distribution of hydrogen sulfide from two geothermal power plants in complex terrain. Atmospheric Environment, 82, 60–70.

    Article  CAS  Google Scholar 

  18. Baltsavias, E., Kocaman, S., & Wolff, K. (2007). Geometric and radiometric investigations of Cartosat-1 data. In: ISPRS Hannover Workshop 2007, High-Resolution Earth Imaging for Geospatial Information, Hannover, Germany, May 29–June 1

  19. Hanna, S. R., Egan, B. A., Purdum, J., & Wagler, J. (2001). Evaluation of the ADMS, AERMOD, and ISC3 dispersion models with the OPTEX, Duke Forest, Kincaid, Indianapolis and Lovett field datasets. International Journal of Environment and Pollution, 16, 301–314.

    Article  CAS  Google Scholar 

  20. Theobald, M. R., Løfstrøm, P., Walker, J., Andersen, H. V., Pedersen, P., Vallejo, A., & Sutton, M. A. (2012). An intercomparison of models used to simulate the short-range atmospheric dispersion of agricultural ammonia emissions. Environmental Modelling & Software, 37, 90–102.

    Article  Google Scholar 

  21. Tartakovsky, D., Broday, D. M., & Stern, E. (2013). Evaluation of AERMOD and CALPUFF for predicting ambient concentrations of total suspended particulate matter (TSP) emissions from a quarry in complex terrain. Environmental Pollution, 179, 138–145.

    Article  CAS  Google Scholar 

  22. Tartakovsky, D., Stern, E., & Broday, D. M. (2016). Dispersion of TSP and PM10 emissions from quarries in complex terrain. Science of the Total Environment, 542, 946–954.

    Article  CAS  Google Scholar 

  23. Larcheveque, L., Sagaut, P., Mary, I., Labbe, O., & Comte, P. (2003). Large-eddy simulation of a compressible flow past a deep cavity. Physics of Fluids, 15, 193–210.

    Article  CAS  Google Scholar 

  24. Patra, A. K., Gautam, S., Majumdar, S., & Kumar, P. (2016). Prediction of particulate matter concentration profile in an opencast copper mine in India using an artificial neural network model. Air Quality, Atmosphere & Health, 9, 697–711.

    Article  CAS  Google Scholar 

  25. Peng, X., & Lu, G. R. (1995). Physical modeling of natural wind and its guide in a large open pit mine. Journal of Wind Engineering & Industrial Aerodynamics., 54–55, 473–481.

    Article  Google Scholar 

  26. Perry, S. G., Cimorelli, A. J., Paine, R. J., Brode, R. W., Weil, J. C., Venkatram, A., et al. (2005). AERMOD: A dispersion model for industrial source applications. Part II: Model performance against 17 field study databases. Journal of Applied Meteorology and Climatology, 44, 694–708.

    Article  Google Scholar 

  27. Silvester, S. A., Lowndes, I. S., & Hargreaves, D. M. (2009). A computational study of particulate emissions from an open pit quarry under neutral atmospheric conditions. Atmospheric Environment, 43, 6415–6424.

    Article  CAS  Google Scholar 

  28. Joseph, G. M. D., Lowndes, I. S., & Hargreaves, D. M. (2018). A computational study of particulate emissions from Old Moor Quarry, UK. Journal of Wind Engineering & Industrial Aerodynamics, 172, 68–84.

    Article  Google Scholar 

  29. Hadlocon, L. S., Zhao, L. Y., Bohrer, G., Kenny, W., Garrity, S. R., Wang, J., et al. (2015). Modeling of particulate matter dispersion from a poultry facility using AERMOD. Journal of the Air & Waste Management Association, 65, 206–217.

    Article  CAS  Google Scholar 

  30. Lowndes, I. S., Silvester, S. A., Kingman, S. W., & Hargreaves, D. M. (2008). The application of an improved multi-scale computational modelling techniques to predict fugitive dust dispersion and deposition within and from surface mining operations. In Proceedings of 12th US/North American Mine Ventilation Symposium, Wallace (ed) (pp. 359–366).

  31. Seangkiatiyuth, K., Surapipith, V., Tantrakarnapa, K., & Lothongkum, A. W. (2011). Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex. Journal of Environmental Sciences, 23, 931–940.

    Article  CAS  Google Scholar 

  32. Krishnan, S., Sajikumar, N., & Sumam, K. S. (2016). DEM Generation Using Cartosat-I Stereo Data and its Comparison with Publically Available DEM. Procedia Technology, 24, 295–302.

    Article  Google Scholar 

  33. Muralikrishnan, S., Pillai, A., Narender, B., Reddy, S., Venkataraman, V. R., & Dadhwal, V. K. (2012). Validation of Indian National DEM from Cartosat-1 Data. Journal of the Indian Society of Remote Sensing, 41, 1–13. https://doi.org/10.1007/s12524-012-0212-9

    Article  Google Scholar 

  34. Chatterjee, R. S. (2006). Coal fire mapping from satellite thermal IR data–a case example in Jharia Coalfield, Jharkhand, India. ISPRS Journal of Photogrammetry and Remote Sensing, 60, 113–128.

    Article  Google Scholar 

  35. Kumar, A., Patil, R. S., Dikshit, A. K., & Kumar, R. (2017). Application of WRF model for air quality modelling and AERMOD–A survey. Aerosol and Air Quality Research, 7, 1925–1937.

    Article  Google Scholar 

  36. Krzyzanowski, J. (2011). Approaching cumulative effects through air pollution modelling. Water, Air, & Soil Pollution, 214, 253–273.

    Article  CAS  Google Scholar 

  37. USEPA (2018). AERMOD Model Formulation and Evaluation. EPA-454/R-18–003. US Environmental Protection Agency- RTP Division.

  38. Snyder, W. H., Thompson, R. S., Eskridge, R. E., Lawson, R. E., Castro, I. P., Lee, J. T., et al. (1985). The structure of the strongly stratified flow over hills: dividing streamline concept. Journal of Fluid Mechanics, 152, 249–288.

    Article  Google Scholar 

  39. Bhaskar, B. V., Rajasekhar, R. J., Muthusubramanian, P., & Kesarkar, A. P. (2008). Measurement and modeling of respirable particulate (PM 10) and lead pollution over Madurai, India. Air Quality, Atmosphere & Health, 1, 45–55.

    Article  Google Scholar 

  40. Krishna, B. G., Amitabh, T. P., Srinivasan, P., & Srivastava, K. (2008). Dem generation from high resolution multi-view data product. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 1099–1102.

    Google Scholar 

  41. Krishna Murthy, Y. V. N., Srinivasa Rao, S., Prakasa Rao, D. S., & Jayaraman, V. (2008). Analysis of DEM generated using Cartosat-1 stereo data over Mausanne les Alpilles-Cartosat scientific appraisal programme (CSAP TS-5). ISPRS., 37, 1343–1348.

    Google Scholar 

  42. Pandey, P., & Venkataraman, G. (2012). Generation and evaluation of Cartosat -1 DEM for Chhota Shigri Glacier, Himalaya. International Journal of Geomatics and Geosciences, 2, 704–711.

    Google Scholar 

  43. Ghose, M. K. (2004). Emission factors for the quantification of dust in India coal mines. Journal of Scientific and Industrial Research, 63, 763–768.

    Google Scholar 

  44. USEPA (2003). AERMOD: Latest Features and Evaluation Results. Report EPA-454/R-03–003. US Environmental Protection Agency. Available from: http://www.epa.gov/scram001/7thconf/ aermod_mep.pdf.

  45. NAAQS (2009). Guidelines for the measurement of Ambient Air Pollutants: Volume I. National Ambient Air Quality Series: NAAQMS/36/2012–13. Central Pollution Control Board- PR Division

  46. Chang, J. C., & Hanna, S. R. (2004). Air quality model performance evaluation. Meteorology and Atmospheric Physics, 87, 167–196.

    Article  Google Scholar 

  47. Hanna, S. R., & Chang, J. (2010). Setting acceptance criteria for air quality models. Proceedings of the International Technical Meeting on Air Pollution Modeling and its Application. Turin, Italy

  48. Willmott, C. J., Robeson, S. M., & Matsuura, K. (2012). A refined index of model performance. International Journal of Climatology, 32, 2088–2094.

    Article  Google Scholar 

  49. Sastry, V. R., Chandar, K. R., Nagesha, K. V., Muralidhar, E., & Mohiuddin, M. S. (2015). Prediction and analysis of dust dispersion from drilling operation in opencast coal mines. Procedia Earth and Planetary Science, 11, 303–311.

    Article  CAS  Google Scholar 

  50. Chaulya, S. K. (2006). Emission rate formulae for surface iron ore mining activities. Environmental Modeling & Assessment, 11, 361–370.

    Article  Google Scholar 

  51. Gautam, S., Patra, A. K., & Prusty, B. K. (2012). Opencast mines: a subject to major concern for human health. International Research Journal of Earth Sciences, 2, 25–31.

    Google Scholar 

  52. Uno, I., Eguchi, K., Yumimoto, K., Takemura, T., Shimizu, A., Uematsu, M., et al. (2009). Asian dust transported one full circuit around the globe. Nature Geoscience, 2, 557.

    Article  CAS  Google Scholar 

  53. Huertas, J. I., Huertas, M. E., & Solis, C. (2012). Characterization of airborne particles in an open pit mining region. Science of the Total Environment, 19, 2784–2794.

    CAS  Google Scholar 

  54. Huertas, J. I., Huertas, M. E., Cervantes, G., & Díaz, J. (2014). Assessment of the natural sources of particulate matter on the opencast mines air quality. Science of the Total Environment, 493, 1047–1055.

    Article  CAS  Google Scholar 

  55. Rangel, M. G. L., Henríquez, J. R., Costa, J. A., & de Lira Junior, J. C. (2018). An assessment of dispersing pollutants from the pre-harvest burning of sugarcane in rural areas in the northeast of Brazil. Atmospheric Environment, 178, 265–281.

    Article  CAS  Google Scholar 

  56. Roy, D., & Singh, G. (2014). Source apportionment of particulate matter (PM10) in an integrated coal mining complex of Jharia coalfield, Eastern India: A review. International Journal of Engineering Research and Applications, 4, 97–113.

    Google Scholar 

  57. Trivedi, R., Chakraborty, M. K., & Tewary, B. K. (2009). Dust dispersion modeling using fugitive dust model at an opencast coal project of Western Coalfields Limited, India. Journal of Scientific and Industrial Research, 68, 71–78.

    CAS  Google Scholar 

  58. Jena, S., & Singh, G. (2017). Human health risk assessment of airborne trace elements in Dhanbad, India. Atmospheric Pollution Research, 8, 490–502.

    Article  Google Scholar 

  59. Srimuruganandam, B., & Nagendra, S. M. S. (2010). Analysis and interpretation of particulate matter–PM10, PM2. 5 and PM1 emissions from the heterogeneous traffic near an urban roadway. Atmospheric Pollution Research, 1, 184–194.

    Article  Google Scholar 

  60. Tiwari, S., Bisht, D. S., Srivastava, A. K., Pipal, A. S., Taneja, A., Srivastava, M. K., & Attri, S. D. (2014). Variability in atmospheric particulates and meteorological effects on their mass concentrations over Delhi, India. Atmospheric Research, 145, 45–56.

    Article  Google Scholar 

  61. Theobald, M. R., Sanz-Cobena, A., Vallejo, A., & Sutton, M. A. (2015). Suitability and uncertainty of two models for the simulation of ammonia dispersion from a pig farm located in an area with frequent calm conditions. Atmospheric Environment, 102, 167–175.

    Article  CAS  Google Scholar 

  62. Botlaguduru, V.S.V. (2009). Comparison of AERMOD and ISCST3 Models for Particulate Emissions from Ground Level Sources (MSc thesis). Texas A&M University.

  63. Golder Associates Ltd. (2006). Air Quality Assessment of Nelson Quarry Company. Burlington, Ontario: Burlington Quarry Extension.

    Google Scholar 

  64. Ul Haq, A., Nadeem, Q., Farooq, A., Irfan, N., Ahmad, M., & Ali, M. R. (2019). Assessment of AERMOD modeling system for application in complex terrain in Pakistan. Atmospheric Pollution Research, 10, 1492–1497.

    Article  Google Scholar 

  65. Chakraborty, M. K., Ahmad, M., Singh, R. S., Pal, D., Bandopadhyay, C., & Chaulya, S. K. (2002). Determination of the emission rate from various opencast mining operations. Environmental Modelling and Software, 17, 467–480.

    Article  Google Scholar 

  66. Carbonell, L. M. T., Gacita, M. S., Oliva, J. D. J. R., Garea, L. C., Rivero, N. D., & Ruiz, E. M. (2010). Methodological guide for implementation of the AERMOD system with incomplete local data. Atmospheric Pollution Research, 1, 102–111.

    Article  CAS  Google Scholar 

  67. Chaulya, S. K. (2004). Assessment and management of air quality for an opencast coal mining area. Journal of Environmental Management, 70, 1–14.

    Article  CAS  Google Scholar 

  68. Sinha, S., & Banerjee, S. P. (1997). Characterization of haul road dust in an Indian opencast iron ore mine. Atmospheric Environment, 31, 2809–2814.

    Article  CAS  Google Scholar 

  69. Gautam, S., Patra, A. K., Sahu, S. P., & Hitch, M. (2018). Particulate matter pollution in opencast coal mining areas: a threat to human health and environment. International Journal of Mining Reclamation and Environment, 32, 75–92.

    Article  Google Scholar 

  70. Ghose, M. K., & Majee, S. R. (2000). Assessment of dust generation due to opencast coal mining–an Indian case study. Environmental Monitoring and Assessment, 61, 257–265.

    Article  Google Scholar 

  71. Mishra, A. K., Maiti, S. K., & Pal, A. K. (2013). Status of PM^ sub 10^ bound heavy metals in ambient air in certain parts of Jharia coal field, Jharkhand. India. International Journal of Environmental Sciences, 4, 141.

    Google Scholar 

  72. Chaulya, S. K. (2004). Spatial and temporal variations of SPM, RPM, SO 2 and NO x concentrations in an opencast coal mining area. Journal of Environmental Monitoring, 6, 134–142.

    Article  CAS  Google Scholar 

  73. Reddy, G. S., & Ruj, B. (2003). Ambient air quality status in Raniganj-Asansol area, India. Environmental Monitoring and Assessment, 89, 153–163.

    Article  CAS  Google Scholar 

  74. Sharma, P. K., & Singh, G. (1990). Assessment of ambient air quality in Tilaboni. Nakrakonda and Jhanjra Block of Raniganj Coalfields. International Journal of Environmental Protection, 10, 105–112.

    Google Scholar 

  75. Chinthala, S., & Khare, M. (2011). Particle Dispersion Within a Deep Opencast Coal Mine. Air Quality-Models and Applications. InTech., 81–98

  76. Cooper, C.D., & Alley, F.C. (2014). Chapter 3: particulate matter. Air pollution control—a design approach. Waveland Press Inc., Illinois, 4, 126

  77. Gautam, S., & Patra, A. K. (2015). Dispersion of particulate matter generated at higher depths in opencast mines. Environmental Technology & Innovation, 3, 11–27.

    Article  Google Scholar 

  78. Weil, J. C., Corio, L. A., & Brower, R. P. (1997). A PDF dispersion model for buoyant plumes in the convective boundary layer. Journal of Applied Meteorology and Climatology, 36, 982–1003.

    Article  Google Scholar 

  79. Rzeszutek, M. (2019). Parameterization and evaluation of the CALMET/CALPUFF model system in near-field and complex terrain-Terrain data, grid resolution and terrain adjustment method. Science of The Total Environment, 689, 31–46.

    Article  CAS  Google Scholar 

  80. Tartakovsky, D., Stern, E., & Broday, D. M. (2016). Indirect estimation of emission factors for phosphate surface mining using air dispersion modeling. Science of the Total Environment, 556, 179–188.

    Article  CAS  Google Scholar 

  81. Chaulya, S. K., Chakraborty, M. K., Ahmad, M., Singh, R. S., Bondyopadhay, C., Mondal, G. C., & Pal, D. (2002). Development of empirical formulae to determine emission rate from various opencast coal mining operations. Water, Air, & Soil Pollution, 140, 21–55.

    Article  CAS  Google Scholar 

  82. Milazzo, M. F., Ancione, G., & Lisi, R. (2017). Emissions of volatile organic compounds during the ship-loading of petroleum products: Dispersion modelling and environmental concerns. Journal of Environment Management, 204, 637–650.

    Article  CAS  Google Scholar 

  83. Kumar, P., Ketzel, M., Vardoulakis, S., Pirjola, L., & Britter, R. (2011). Dynamics and dispersion modelling of nanoparticles from road traffic in the urban atmospheric environment—a review. Journal of Aerosol Science., 42, 580–603.

    Article  CAS  Google Scholar 

  84. Shih, H. C., Crawford-Brown, D., & Ma, H. W. (2015). The influence of spatial resolution on human health risk co-benefit estimates for global climate policy assessments. Journal of Environmental Management, 151, 393–403.

    Article  Google Scholar 

  85. Perry, S. G. (1992). CTDMPLUS, a dispersion model for sources in complex topography. Part I: technical formulations. Journal of Applied Meteorology and Climatology, 31, 633–645.

    Article  Google Scholar 

  86. Kesarkar, A. P., Dalvi, M., Kaginalkar, A., & Ojha, A. (2007). Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune. India. Atmospheric Environment, 9, 1976–1988.

    Article  Google Scholar 

  87. Paine, R.J., J.A. Connors., & C.D. Szembek. (2010). AERMOD Low Wind Speed Evaluation Study: Results and Implementation. Paper 2010-A-631-AWMA, presented at the 103rd Annual Conference, Air & Waste Management Association, Calgary, Alberta, Canada.

  88. Cohan, A., Wu, J., & Dabdub, D. (2011). High–resolution pollutant transport in the San Pedro Bay of California. Atmospheric Pollution Research, 2, 237–246.

    Article  CAS  Google Scholar 

  89. Neshuku, M.N. (2012). Comparison of the Performance of Two Atmospheric Dispersion Models (AERMOD and ADMS) for Open Pit Mining Sources of Air Pollution (MSc thesis). University of Pretoria, SAR.

  90. USEPA (2006a). Revision of emission factors for AP-42. Chapter 13: miscellaneous source. Section 13.2.2: Unpaved Roads (Fugitive Dust Sources). http://www.epa.gov/ttn/chief/ap42/index.html. Accessed 16 May 2018

  91. Cowherd, C., Muleski, G. E., & Kinsey, J. S. (1988). Control of open fugitive dust sources. Final report (No. PB-89–103691/XAB). Midwest Research Inst., Kansas City, MO (USA).

  92. USEPA (2006b). Revision of emission factors for AP-42. Chapter 13: Miscellaneous Source. Section 13.2.4: Aggregate Handling and Storage Piles (Fugitive Dust Sources). http://www.epa.gov/ttn/chief/ap42/index.html. Accessed 2 June 2018

  93. USEPA (2008). Revision of emission factors for AP-42. Chapter 11: mineral products industry. Section 11.9: Western Surface Coal Mining. http://www.epa.gov/ttn/chief/ap42/index.html. Accessed 1 April 2018

  94. Missouri Department of Natural Resources (2009). EIQ form 2.8 storage pile worksheet instructions for form 780-1446. http://dnr.mo.gov/forms/. Accessed 21 October 2018

  95. SPCC (1983). Air Pollution from Coal Mining and Related Developments.

Download references

Acknowledgements

The authors acknowledge the support and guidance provided by the Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India and Bharat Coking Coal Limited, Dhanbad, for carrying out the research work. The authors express their courtesy to the National Data Centre of National Remote Sensing Centre, India, to provide satellite data. The authors also acknowledge Lakes Environmental for providing web-based resources for DEM. The authors sincerely express sincere thanks to the anonymous reviewers for their constructive critique to improve this manuscript's quality.

Author information

Authors and Affiliations

  1. Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India

    Amartanshu Srivastava, Ambasht Kumar & Suresh Pandian Elumalai

Authors
  1. Amartanshu Srivastava
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ambasht Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suresh Pandian Elumalai
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Amartanshu Srivastava: conceptualization, data curation, formal analysis, investigation, methodology, software, writing-original draft. Amabasht Kumar: investigation, validation, formal analysis, writing-review and editing. Suresh Pandian Elumalai: conceptualization, investigation, resources, supervision, writing-review and editing.

Corresponding author

Correspondence to Suresh Pandian Elumalai.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 4867 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srivastava, A., Kumar, A. & Elumalai, S. Evaluating Dispersion Modeling of Inhalable Particulates (PM10) Emissions in Complex Terrain of Coal Mines. Environ Model Assess 26, 385–403 (2021). https://doi.org/10.1007/s10666-021-09762-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10666-021-09762-w

Keywords

Search

Navigation