Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel

Traffic-related carbon dioxide (CO₂) emissions have become a major problem in cities. Especially, the CO₂ emissions induced by taxis account for a high proportion in total CO₂ emissions. The availability of taxi trajectory data presents new opportunities for addressing CO₂ emissions induced by taxis. Few previous studies have analyzed the impact of human trips on CO₂ emissions. This paper investigates trip-related CO₂ emission patterns based on individuals' travel behavior using taxi trajectory data. First, we propose a trip purpose inference method that takes into account the spatiotemporal attractiveness of POIs to divide human trips into different types. Further, we reveal the spatiotemporal patterns of CO₂ emissions from various types of trips, including temporal regularity and periodicity as well as spatial distribution of “black areas”. Finally, comparative analysis of CO₂ emissions for different kinds of trips based on trip behavior is conducted using three variables, namely trip distance, trip duration and trip speed. This study is helpful for us to understand how to make travel and cities more sustainable through modifying people's trip behaviors or taxi trips.