Smartphone-Based CO2e Emission Estimation Using Transportation Mode Classification

As a first step towards decreasing greenhouse gas emissions originating from transportation, it is critical that we create efficient systems for monitoring individual travel patterns and the associated carbon footprints. To this end, this paper presents a CO(2)e emission estimator that combines transportation mode classification with mode-specific emissions data. In addition to assessing the accuracy of the final emission estimation, we also categorize error sources and discuss their relative importance. Finally, we provide recommendations for designers of future carbon footprint estimators. Experimental results support the notion that transportation mode classifiers used for carbon footprint estimation should be evaluated based on their ability to identify carbon emitting transportation modes, while giving lower priority to recognition of various stationary activities and low-emission transportation modes. Additionally, it is demonstrated that errors in the estimated traveled distance have a low impact on the overall emissions error compared to errors in the transportation mode classification or in the assumed emissions per traveled distance for a specific mode.

Automated summary

In order to reduce transportation-related greenhouse gas emissions, it is important to establish efficient systems for monitoring individuals' travel patterns and carbon footprints. This paper introduces a CO(2)e emission estimator that combines transportation mode classification with mode-specific emissions data. It not only evaluates the accuracy of the emission estimation, but also identifies and discusses the sources of errors and their relative importance. The study provides recommendations for future carbon footprint estimators and highlights the importance of evaluating transportation mode classifiers based on their ability to identify carbon emitting transportation modes.