Zhang, X; Cheng, T; Yang, Z; (2026) Spatiotemporal dynamics of local transport greenhouse gases using mobile phone data: A framework for emissions estimation, allocation, and determinants identification. Journal of Transport Geography , 130 , Article 104492. 10.1016/j.jtrangeo.2025.104492. (In press).

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Abstract

Estimating and allocating greenhouse gases (GHGs) emissions from transport at the urban scale is essential for guiding local decarbonisation strategies and enabling effective carbon governance. However, conventional top-down methods often obscure the spatial, temporal, and behavioural complexity of urban mobility, limiting the design of targeted interventions. This study presents a novel bottom-up framework that leverages individual-level mobile phone data to estimate, allocate, and analyse transport-related GHG emissions at high spatial and temporal resolution. The framework supports multiple accounting perspectives, including territorial and residence-based principles, while enabling contributor tracing by traveller types and the identification of localised emission determinants. Applied to Greater London, the framework reveals significant shifts in emission patterns between pre- and post-pandemic periods, highlighting increased emissions from residents and trip-attracted individuals, alongside persistent dominance by pass-through travellers. It also captures how behavioural changes, such as remote work, have reshaped emissions determinants. The proposed approach provides a scalable and policy-relevant tool to support localised climate action and lays a foundation for evidence-based transport carbon trading systems.

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