NDLI: Statistical Model to Study the Effect of Agriculture Crop Residue Burning on Healthy Subjects

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Statistical Model to Study the Effect of Agriculture Crop Residue Burning on Healthy Subjects

Content Provider	Springer Nature Link
Author	Agarwal, Ravinder Awasthi, Amit Mital, Susheel K. Singh, Nirankar Gupta, Prabhat K.
Copyright Year	2013
Abstract	Pulmonary function test (PFT) values of 50 healthy subjects and levels of pollutants like suspended particulate matter (SPM), PM$_{10}$, PM$_{2.5}$ in ambient air were continually investigated from February 2007 to January 2010 at Patiala, Punjab (India). Significant decrease in PFTs were observed with increase in concentration levels of pollutants during wheat and rice crop residue burning in the fields. In the present paper a new statistical model on field crop residue burning and PFT has been proposed. The model is based on multiple ordinary least square regression method. It can predict values of PFTs as a function of some parameters of air pollutants. Monthly average values of different variables are used for the purpose of designing four different models. These models were tested by parameters like randomness of residual, relationship of residual with independent variables, etc. The final accepted models could predict up to 88 % variation in the values of force vital capacity and force expiratory volume and up to 77 % variation in peak expiratory flow and force expiratory flow with the corresponding changes in the SPM, PM$_{10}$, PM$_{2.5}$ and temperature respectively. This model can be used as a tool for measurement of risk assessment due to air pollution in future.
Starting Page	57
Ending Page	65
Page Count	9
File Format	PDF
ISSN	09703950
Journal	MAPAN
Volume Number	29
Issue Number	1
e-ISSN	09749853
Language	English
Publisher	Springer India
Publisher Date	2013-09-24
Publisher Institution	Metrology Society of India
Publisher Place	India
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Field crop residue burning pulmonary function test Multiple linear regressions Ordinary least squares Statistical model and particulate matter Measurement Science and Instrumentation Theoretical, Mathematical and Computational Physics Mathematical Methods in Physics Numerical and Computational Physics
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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