Advanced Mathematical Applications in Data Science

A State-Wise Assessment of Greenhouse Gases Emission in India by Applying K-mean Clustering Technique

Author(s): Nitin Jaglal Untwal * .

Pp: 162-176 (15)

DOI: 10.2174/9789815124842123010014

* (Excluding Mailing and Handling)

Abstract

 India is a vast country with variations in geography as well as in population density. The pollution in India is increasing day by day. The Greenhouse gas emission is on the rise due to various activities like agriculture, industry, power generation, transportation, etc. Carbon dioxide (CO2 ), Carbon Monoxide (CO), and Methane (CH4 ) are the major elements in greenhouse gases. The emission of greenhouse gases causes various threats to the environment and health. The states in India have been under development since independence. Various activities are on the rise. The states are not having balanced growth as far as the industrial and agriculture sectors are concerned. The powerhouse of industrial growth is the state of Maharashtra and Gujarat. The population density is also scattered in India. The states contribute differently to greenhouse gases emission and it is difficult for the government to make policy category-wise for the control of greenhouse gases emissions. The classification of states into different categories will help in the strategic formulation of policy and strategy for different states depending on their greenhouse gases emission and per capita analysis of these emissions. The per capita greenhouse gas emission is calculated by dividing the total emissions by the total population. After analyzing the above problem, the researchers have decided to conduct the study titled A state-wise Assessment of greenhouse gas emission in India by applying the K-mean Clustering Technique using Python Programming. Research is carried out in Five steps -Feature extraction and engineering, Data extraction, Standardizing and Scaling, Identification of Clusters, Cluster formation. The study period is 2020. The data selected for analysis is yearly data state-wise of different Indian states. Data taken for the study is from the Kaggle database. Findings - The k- mean algorithm (cluster analysis using Python Programming) classifies the states of India into three clusters. Cluster one includes 16 states of India viz. Arunachal, Assam, Bihar, Himachal Pradesh, Jammu & Kashmir, Jharkhand, Madhya Pradesh, Manipur, Meghalaya, Mizoram, Odisha, Rajasthan, Sikkim, Tripura, Uttar Pradesh, Uttarakhand. Cluster two includes 8 states of the India. Viz Andhra Pradesh, Goa, Gujarat, Karnataka, Kerala, Maharashtra, Tamilnadu, West Bengal. Cluster three includes 4 states of India Viz Haryana, Nagaland, Punjab, Chhattisgarh. The major contributors to greenhouse gase emission are in cluster three.The medium-range emission for greenhouse gases emission are grouped in cluster two and Minimum Range greenhouse gase emission states are included in cluster one.


Keywords: Carbon emission, Data extraction, Feature extraction and engineering, K-mean clustering, Python programming, Standardizing and scaling.

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