- ISSN: 2333-2581
- Modern Environmental Science and Engineering
Influencing Factors for Household Level Carbon Emissions and Spatial Differences
Wathsala Gunathilake, and C. M. K. N. K. Chandrasekara
Department of Geography, University of Colombo, Sri Lanka
Abstract: Higher admission of carbon to the atmosphere is currently a burning global issue. It becomes more vulnerable in the 21st century with the increase of population and the anthropogenic related emissions. According to the IPCC reports, Sri Lanka is also identified as one of the countries in the border line of high emissions of carbon from anthropogenic activities. The present study was carried out to identify the relationship between carbon emission and household size, occupation, settlement type and education level in Balangoda Divisional Secretariat Division (DSD) in Sri Lanka. The study was carried out in 251 households in six selected Grama Niladhari (GN) administrative divisions. Population density, population distribution, fuel and electricity consumption, land surface temperature and vegetation index were considered in identifying the current emission pattern of the area. Emission patterns were classified as high, medium and low magnitudes for the detailed analysis and selection of the GNs for the study was performed based on this patterns. A questionnaire survey was carried out in 121 urban households, 76 semi urban and 49 rural households. Arc GIS 10.5 and SPSS analysis tool pack were used for the analysis. The six GNDs represented high; Balangoda and Pettigala, medium Jahinkanda and Ellepola, low; Pallekanda and Massenna magnitudes in the distribution of carbon encouraging potentials. The study identified five major components of carbon emission from principal component analysis and the first three components highlighted the influence of secondary expenses based on primary necessities as the major drivers of carbon emission. Although the study identified high carbon emissions in Balangoda GND (108.01 MTCO2e) which is an urban area, the combined map highlighting the carbon clusters associated with five major drivers of carbon emission indicated more carbon clusters in Pettigala GND which is an estate area with more line settlements. High rates of electricity and LPG consumptions were also identified in this GND. The study indicated that the settlement type, population density and life styles of the people have a high impact on area’s total carbon emission. The findings of the study will be important for future carbon emission related predictions and for global scale measures for climate change. They will help planners and decision makers in climatic changes sector to easily recognize the areas with high, medium and low concentrations of carbon emission. Therefore the results can further be used for awareness and education purposes and to empower the future carbon emission reduction campaigns.