TEPs and Satellite
TEPs and pollution backcasting
TEPs and Satellite
This study enhances spatio-temporal interpolation models for Annual Average Daily Traffic (AADT) estimation across urban roads by incorporating vehicle detection from aerial images, achieving a high predictive accuracy of 90% R-squared for daily traffic counts, but highlighting the importance of longer-term data for accurate AADT predictions.
TEPs and structure
TEPs and pollution backcasting
TEPs and Satellite
The paper introduces a novel structure of TEPS, acknowledging spatio-temporal relationships and recognizing patterns, to predict periodic and annual volumes as well as greenhouse gas emissions at the individual roadway level across a large urban road network, addressing limitations in traditional emission inventories based on househ
The paper introduces a novel structure of TEPS, acknowledging spatio-temporal relationships and recognizing patterns, to predict periodic and annual volumes as well as greenhouse gas emissions at the individual roadway level across a large urban road network, addressing limitations in traditional emission inventories based on household travel data and providing a universal approach validated with City of Toronto traffic count program data
TEPs and pollution backcasting
TEPs and pollution backcasting
TEPs and pollution backcasting
This study proposes a method for backcasting traffic-related air pollution surfaces, incorporating temporal variability in traffic and emissions using TEPs as well as trends in concentrations measured at reference stations, revealing spatially heterogeneous improvements in nitrogen dioxide (NO2) concentrations in the City of Toronto
This study proposes a method for backcasting traffic-related air pollution surfaces, incorporating temporal variability in traffic and emissions using TEPs as well as trends in concentrations measured at reference stations, revealing spatially heterogeneous improvements in nitrogen dioxide (NO2) concentrations in the City of Toronto from 2006 to 2020, with average decreases of 20.46% and notable variations along major roads and highways.