Carbon Emission Assessment by Applying Clustering Technique to World’s Emission Datasets

The greenhouse gas emissions mostly include carbon-dioxide as the major component. The CO2 level is increasing day-by-day which is a great cause of worry for the future world’s environment. The reason why greenhouse gases’ level increases in the environment is to be assessed and controlled. The greenhouse gases have heattrapping capacity. A rise in numerous activities, including transportation, power production, agriculture, business, and residential, which are the main drivers of the increase in GHG levels in the atmosphere, is to blame for the rise in GHG emissions. Nitrous oxide, Methane, and Carbon Dioxide are all part of the GHG portfolio. Deforestation, traffic, and soil degradation all contribute to an increase in CO2 . As a result of burning biomass and urban trash, methane levels are also rising. The chlorofloro carbons are also rising due to refrigeration and industrial operations; so keeping the above concern in mind, the researcher had decided to conduct the study title. Carbon Emission Assessment by Applying Clustering Technique to World Emission Datasets using Python Programming. The study considers a period of 169 years (1750-2019). The study is carried out in five steps data fetching in python programming, feature engineering, standardization, clustering. The study generates 6 clusters. Cluster one contains 220 countries, cluster two includes Russia, France, Germany, China, Europe (others). America (others), Asia Pacific. Cluster three includes the United Kingdom. Cluster four includes the United States. Cluster five includes EU-28. Cluster six includes Malawi.