A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou

Commuting carbon emissions are an essential component of urban emissions, and determining how to reduce them is area great debate among researchers. The current research lacks a tool instrument that can extensively account for residents’ commuting. Traditional methods mainly based on questionnaire surveys, which have low accuracy at spatial temporal aspects. High emission accounting effectively assist planning achieve precise reductions. This study applies taxi commuting method divided into two main steps. Firstly, the trajectories calculated using trajectory data calculation developed VSP. Secondly, POI used filter commuter with help two-step moving search method. In this way, were obtained. Then, distribution characteristics residential analysed by autocorrelation tools, could facilitate zoning management. A typical working day in Hangzhou was selected as object study. results show (1) morning peak reached 2065.14 kg per hour, 13.73% all travel emissions; evening 732.2 4% (2) At grid level, shows single central decays directions; (3) resident community scale public transport facilities influence emissions. areas such urban-rural border, high levels aggregation, area, aggregation. not only provides new investigation but also offers constructive suggestions future reduction under Hangzhou’s planning.