Enhancing individual's carbon footprint estimation via spatial data

The aim of the study is to determine the impact of spatial data within individual's carbon footprint calculation process and to test various shortest path measurement methodologies within these calculations. For this purpose, several individual carbon footprint calculators were examined and compared. The spatial data, especially distance between activities plays an important role within estimations. However, the distance utilized within the calculators is Euclidean distance - crow flight-. This information could provide rough estimations about the distances traveled, especially if the trip distance is long. Better techniques such as Dijkstra's algorithm are available for calculating the shortest paths. For testing the impact of applying more sophisticated techniques for path calculation, the individual carbon footprint of Istanbul Technical University students were calculated using different shortest path algorithms and results were compared. A survey was designed for capturing the activities, social preferences and commuting behaviors of students, where 430 students have responded positively. When network-based distance calculations was applied using the same online calculator, the monthly average of students' carbon footprint has increased 28%. The spatial approach outlined in this study revealed more realistic results that could aid to develop better strategies for mitigation and achieving the goals.