Abstract
India Stands at the third position, as the producer of wheat and rice all over the globe, presently. On the other hand, even with this achievement, India also stands first amongst the world for polluting air due to burning of agricultural residuals. Haryana and Punjab alone contribute to 48 percent of total agriculture residual burning which leads to air being polluted with toxic gases like Carbon monoxide (CO), Organic Carbon (OC), Ammonia (NH3), Sulphur dioxide (SO2), Particulate matter (PM2.5), Organic Compounds (VOCs) and Carbon dioxide (CO2). Burning of crop residuals not only pollutes the air quality but also degrades the soil parameters, which are very essential for crops. Stats revealed that 8.5 children out of 10,000 dies due to the bad air quality in India before the age of five per year. It observed over time that air quality degrades every successive year in northern India. One of the Major reasons for climate change is crop residual burning. This increasing trend of residual burning practice is somewhere related to farmers profit and environmental parameters of Haryana and Punjab. This paper contributes in the study which relate parameters like rainfall, temperature, and crop production with crop residual burning pattern. Data from the last twenty years has been used from various resources and analysed with latest machine learning algorithms and statistical tools.
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Crop Residue Burning,Air Pollution,Rainfall,Temperature,Climate Change,ADOMNet,ANN,Pattern Recognition.Non Linear Regression,Agriculture Residual
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