STIMULATING THE INHERENT MOTIVATORS FOR PLASTIC WASTE DISPOSAL TO MINIMIZE THE CARBON FOOTPRINTS IN GUWAHATI CITY, ASSAM

. Plastic waste handling & management skills, and controlling of carbon footprints in the environment are major challenges for a sustainable environment. In handling these challenges, awareness levels among the people in waste handling techniques and their pro-environmental behaviors must be identified. The likelihood to successfully engage people in participation of safe disposal of plastic waste process is explored, if people are intrinsically motivated or not, to enjoy their participation in these activities, is examined, in addition to enhancing the city’s plastic waste management activities. Guwahati, one of the most important cities in Northeast India, but it is suffering and generating more and more plastic waste every day. The wish to generate valuable energy from plastic waste is a distant dream as of now. This study aims to identify the factors responsible for the reduction of carbon footprints in the environment from plastic waste management activities through factor analysis of underlying variables of a sample survey questionnaire collected from 663 responses. The reliability of the dataset is confirmed using Cronbach’s alpha. The data adequacy and factorability along with the multi-collinearity of the dataset are checked using KMO, Bartlett’s test of sphericity, and determinant score and found in order. Principal component analysis (PCA), Exploratory factor analysis (EFA), and varimax orthogonal rotation method are used to extract high-loaded factors by reducing the number of variables. The results have depicted two highly loaded components representing the awareness level of waste management techniques (AWMT) and prevalent mode of plastic waste management techniques (PWMT) with their internal consistency of 0.84 and 0.780. the factor AWMT explains 27.53% of the total variance while the other factor PWMT explains 24.34% with their eigenvalues of 3.35 and 2.88 respectively. The regression model ensures that these two factors and the dependent variable, greenhouse reduction (GHGR) are statistically significant and there is a strong relationship between them to reduce the emission of greenhouse gases that have been established from the regression equation where two factors are positively correlated. This study proposes that AWMT and PWMT towards minimization of carbon footprints in the environment are the key factors for reducing plastic waste. This study would provide valuable input to the concerned authority for controlling waste generation and thereby achieve a pollution-free environment by focusing on a few limited controllable factors rather than more variables.