Konutlar için CBS tabanlı bir karbon ayak izi hesaplama metodolojisi geliştirlmesi: Bursa'da Nilüfer ilçesi örneği

With the recent adoption of Paris Agreement, countries agreed to combat climate change and its impacts by making efforts to keep the global average temperature rise well below 2 °C and by striving for 1.5 °C by the end of this century. In line with this purpose, greenhouse gas emission reduction actions are integrated into environmental policies all over the world. Urban carbon footprint emerges as one of the key concepts of current global climate policies since urban areas are the major contributors to global GHG emissions today. To develop reliable urban emission reduction policies and mitigate the associated adverse effects, one first has to calculate the emission level as accurate as possible. The main purpose of this study was to develop a GIS-based carbon footprint accounting methodology based on actual electricity and natural gas consumption figures of residential buildings in a pilot area to minimize the limitations caused by deficiencies in CF-related data generation and access; and to contribute to local policy-making by providing useful tools and results to decision-makers. Within this scope, three types of residential heating systems that predominate in Turkey were focused on, namely: (i) individual heating systems, (ii) central heating systems and (iii) district heating systems. Residential carbon footprint of six selected neighborhoods in Nilüfer District of Bursa Province was calculated by utilizing the GIS database of the pilot area. Although convenience of using a GIS software in carbon footprint accounting was observed to a certain extent, some corrections and modifications were required to obtain a complete GIS database that would serve the purpose of this study. Calculations were done based on actual natural gas and electricity consumption values of sample buildings and for each year between 2014-2017. According to the results, residential carbon footprint in the pilot area ranged from 93.14 to 119.52 ktCO2 and the per capita residential carbon footprint ranged from 0.99 to 1.27 tCO2 between 2014-2017. A more in-depth analysis of the results was then made by using spatial analysis tools to better discuss the outcomes; and consequently, useful conclusions for local policy-makers and future studies were drawn.M.S. - Master of Scienc