Development and assessment of multiple regression and neural network models for prediction of respirable PM in the vicinity of a surface coal mine in India
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Afzali A, Rashid M, Sabariah B, Ramli M (2014) PM10 pollution: its prediction and meteorological influence in PasirGudang, Johor. In IOP Conference Series: Earth and Environmental Science, vol 18. IOP Publishing, p 012100, (1)
Aneja VP, Isherwood A, Morgan P (2012) Characterization of particulate matter (PM10) related to surface coal mining operations in Appalachia. Atmos Environ 54:496–501
Baheer I (2000) Selection of methodology for modeling hysteresis behavior of soils using neural networks. J Comput Aided Civ Infrastruct Eng 5(6):445–463
Banks DE, Wang ML, Lapp NL (1998) Respiratory health effects of opencast coalmining: a cross sectional study of current workers. Occup Environ Med 55(4):287–288
Çelik MB, İbrahim KADI (2007) The relation between meteorological factors and pollutants concentrations in Karabük city. Gazi Univ J Sci 20(4):87–95
Chaloulakou A, Grivas G, Spyrellis N (2003a) Neural network and multiple regression models for PM10 prediction in Athens: a comparative assessment. J Air Waste Manage Assoc 53(10):1183–1190
Chaloulakou A, Kassomenos P, Spyrellis N, Demokritou P, Koutrakis P (2003b) Measurements of PM10 and PM2.5 particle concentrations in Athens, Greece. Atmos Environ 37(5):649–660
Deshmukh DK, Deb MK, Mkoma SL (2013) Size distribution and seasonal variation of size-segregated particulate matter in the ambient air of Raipur city, India. Air Qual Atmos Health 6(1):259–276
Enayatollahi I, Bazzazi AA, Asadi A (2014) Comparison between neural networks and multiple regression analysis to predict rock fragmentation in open-pit mines. Rock Mech Rock Eng 47(2):799–807
EPR (2000) http://cpcb.nic.in/Industry-Specific-Standards/Effluent/494-1.pdf (accessed on November 18, 2017)
Field A (2009) Discovering statistics using SPSS. Sage publications
Finkelman RB, Orem W, Castranova V, Tatu CA, Belkin HE, Zheng B, Bates AL (2002) Health impacts of coal and coal use: possible solutions. Int J Coal Geol 50(1):425–443
Gautam S, Patra AK (2015) Dispersion of particulate matter generated at higher depths in opencast mines. Environ Technol Innov 3:11–27
Gautam S, Patra AK, Prusty BK (2012) Opencast mines: a subject to major concern for human health. Int Res J Geol Min 2(2):25–31
George KV, Patil DD, Alappat BJ (2013) PM10 in the ambient air of Chandrapur coal mine and its comparison with other environments. Environ Monit Assess 185(2):1117–1128
Ghose MK, Majee SR (2001) Air pollution due to opencast coal mining and its control in Indian context. J Sci Ind Res 60:786–797
Grimm (2010) Operational manual of portable laser aerosol spectrometer and dust monitor (Model 1.108/1.109). GRIMM Aerosol Technik GmbH & Co. KG, Ainring
Gupta SK, Elumalai SP (2019) Dependence of urban air pollutants on morning/evening peak hours and seasons. Arch Environ Contam Toxicol:1–19
Gupta AK, Nag S, Mukhopadhyay UK (2006) Characterisation of PM10, PM2.5 and benzene soluble organic fraction of particulate matter in an urban area of Kolkata, India. Environ Monit Assess 115(1):205–222
Hecht-Nielsen R (1987) Kolmogorov’s mapping neural network existence theorem. In Proceedings of the IEEE International Conference on Neural Networks III. IEEE Press, p 11-13
Hendryx M (2009) Mortality from heart, respiratory, and kidney disease in coal mining areas of Appalachia. Int Arch Occup Environ Health 82(2):243–249
Hendryx M, Ahern MM (2008) Relations between health indicators and residential proximity to coal mining in West Virginia. Am J Public Health 98(4):669–671
Jena S, Singh G (2017) Human health risk assessment of airborne trace elements in Dhanbad, India. Atmos Pollut Res 8(3):490–502
Kakosimos KE, Assael MJ, Lioumbas JS, Spiridis AS (2011) Atmospheric dispersion modeling of the fugitive particulate matter from overburden dumps with numerical and integral models. Atmos Pollut Res 2(1):24–33
Kanellopoulos I, Wilkinson GG (1997) Strategies and best practice for neural network image classification. Int J Remote Sens 18(4):711–725
Karar K, Gupta AK (2006) Seasonal variations and chemical characterization of ambient PM 10 at residential and industrial sites of an urban region of Kolkata (Calcutta), India. Atmos Res 81(1):36–53
Kaur S, Nieuwenhuijsen MJ (2009) Determinants of personal exposure to PM2.5, ultrafine particle counts, and CO in a transport microenvironment. Environ Sci Technol 43(13):4737–4743
Kumar A, Goyal P (2013) Forecasting of air quality index in Delhi using neural network based on principal component analysis. Pure Appl Geophys 170(4):711–722
Kundu S, Pal AK (2015) The evaluation of airborne respirable particulates in opencast mining area of Jharia coal field using Grimm 1.109 real-time portable aerosol spectrometer. J Biodivers Environ Sci 6(4):276–287
Lal B, Tripathy SS (2012) Prediction of dust concentration in open cast coal mine using artificial neural network. Atmos Pollut Res 3(2):211–218
Li H, Zhang Z, Zhao Z (2019) Data-mining for processes in chemistry, materials, and engineering. Processes 7(3):151
Lu Z, Pu H, Wang F, Hu Z, Wang L (2017) The expressive power of neural networks: a view from the width. Adv Neural Inf Proces Syst:6231–6239
Maeda T (2018) Technical note: how to rationally compare the performances of different machine learning models? PeerJ Preprints No. 26714v1
Mandal K, Kumar A, Tripathi N, Singh RS, Chaulya SK, Mishra PK, Bandyopadhyay LK (2012) Characterization of different road dusts in opencast coal mining areas of India. Environ Monit Assess 184(6):3427–3441
Manju A, Kalaiselvi K, Dhananjayan V, Palanivel M, Banupriya GS, Vidhya MH, Panjakumar K, Ravichandran B (2018) Spatio-seasonal variation in ambient air pollutants and influence of meteorological factors in Coimbatore, southern India. Air Qual Atmos Health 11(10):1179–1189
Manoj K, Padhy PK (2014) Multivariate statistical techniques and water quality assessment: discourse and review on some analytical models. Int J Environ Sci 5(3):607
Maraziotis E, Sarotis L, Marazioti C, Marazioti P (2008) Statistical analysis of inhalable (PM10) and fine particles (PM2.5) concentrations in urban region of Patras, Greece. Glob Nest J 10(2):123–131
Montgomery DC, Peck EA, Vining GG (2012) Introduction to linear regression analysis, vol 821. Wiley
Nazif A, Mohammed NI, Malakahmad A, Abualqumboz MS (2016) Application of step wise regression analysis in predicting future particulate matter concentration episode. Water Air Soil Pollut 227(4):117
Nazif A, Mohammed NI, Malakahmad A, Abualqumboz MS (2018) Regression and multivariate models for predicting particulate matter concentration level. Environ Sci Pollut Res 25(1):283–289
Onder M, Yigit E (2009) Assessment of respirable dust exposures in an opencast coal mine. Environ Monit Assess 152(1):393–401
Pallant J (2004) SPSS survival manual. Open University Press, London
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. Atmos Pollut Res 5(1):79–86
Papanastasiou DK, Melas D, Kioutsioukis I (2007) Development and assessment of neural network and multiple regression models in order to predict PM10 levels in a medium sized Mediterranean city. Water Air Soil Pollut 182:325–334
Patra AK, 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 Qual Atmos Health 9(6):697–711
Pless-Mulloli T, Howel D, King A, Stone I, Merefield J, Bessell J, Darnell R (2000) Living near opencast coal mining sites and children’s respiratory health. Occup Environ Med 57(3):145–151
Rivas I, Kumar P, Hagen-Zanker A, de Fatima Andrade M, Slovic AD, Pritchard JP, Geurs KT (2017) Determinants of black carbon, particle mass and number concentrations in London transport microenvironments. Atmos Environ 161:247–262
Roy S, Adhikari GR, Singh TN (2010) Development of emission factors for quantification of blasting dust at surface coal mines. J Environ Prot 1(4):346–361
Roy S, Adhikari GR, Renaldy TA, Jha AK (2011) Development of multiple regression and neural network models for assessment of blasting dust at a large surface coal mine. J Environ Sci Technol 4(3):284–301
Sahu SP, Patra AK, Kolluru SSR (2018a) Spatial and temporal variation of respirable particles around a surface coal mine in India. Atmos Pollut Res 9(4):662–679
Sahu SP, Yadav M, Pradhan DS, Rani N, Das AJ (2018b) Spatio-temporal variations of respirable particles at residential areas located in the vicinity of opencast coal projects, India: a case study. Arab J Geosci 11(10):241
Samara C, Argyropoulos G, Grigoratos T, Kouras Α, Manoli Ε, Andreadou S, Pavloudakis F, Sahanidis C (2017) Chemical characterization and receptor modeling of PM10 in the surroundings of the opencast lignite mines of Western Macedonia, Greece. Environ Sci Pollut Res:1–16
Sastry VR, Chandar KR, Nagesha KV, Muralidhar E, Mohiuddin MS (2015) Prediction and analysis of dust dispersion from drilling operation in opencast coal mines. Procedia Earth Planet Sci 11:303–311
Singal SP, Prasad R (2005) Analytical study of some observed micrometeorological data. J Air Pollut Control Assoc 1:44–49
Singh G (2006) An index to measure depreciation in air quality in some coal mining areas of Korba industrial belt of Chhattisgarh, India. Environ Monit Assess 122(1):309–317
Spectrum (2010) Operational manual of watchdog 2000 series portable weather station. Spectrum Technologies, Inc., Aurora
Srimuruganandam B, Nagendra SMS (2010) Analysis and interpretation of particulate matter–PM10, PM2.5 and PM1 emissions from the heterogeneous traffic near an urban roadway. Atmos Pollut Res 1(3):184–194
Tecer LH, Süren P, Alagha O, Karaca F, Tuncel G (2008) Effect of meteorological parameters on fine and coarse particulate matter mass concentration in a coal-mining area in Zonguldak, Turkey. J Air Waste Manage Assoc 58(4):543–552
Tetko IV, Livingstone DJ, Luik AI (1995) Neural network studies. 1. Comparison of overfitting and overtraining. J Chem Inf Comput Sci 35(5):826–833
Tiwari S, Chate DM, Pragya P, Ali K, Bisht DS (2012a) Variations in mass of the PM10, PM2.5 and PM1 during the monsoon and the winter at New Delhi. Aerosol Air Qual Res 12(1):20–29
Tiwari S, Chate DM, Srivastava MK, Safai PD, Srivastava AK, Bisht DS, Padmanabhamurty B (2012b) Statistical evaluation of PM10 and distribution of PM1, PM2.5, and PM10 in ambient air due to extreme fireworks episodes (Deepawali festivals) in megacity Delhi. Nat Hazards 61(2):521–531
Tiwari S, Bisht DS, Srivastava AK, Pipal AS, Taneja A, Srivastava MK, Attri SD (2014) Variability in atmospheric particulates and meteorological effects on their mass concentrations over Delhi, India. Atmos Res 145:45–56
Tripathy DP, Dash TR, Badu A, Kanungo R (2015) Assessment and modeling of dust concentration in an opencast coal mine in India. Glob Nest J 17(4):825–834
Trivedi R, Chakraborty MK, Tewary BK (2009) Dust dispersion modeling using fugitive dust model at an opencast coal project of Western Coalfields Limited, India. J Sci Ind Res 68:71–78
Yadav SK, Jain MK (2019) Variation in concentrations of particulate matter with various sizes in different weather conditions in mining zone. Int J Environ Sci Technol:1–14
Yadav S, Praveen OD, Satsangi PG (2015) The effect of climate and meteorological changes on particulate matter in Pune, India. Environ Monit Assess 187(7):402