Pollution Emission Patterns of Transportation in Porto, Portugal Through Network Analysis

PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT I(2023)

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摘要
Over the past few decades, road transportation emissions have increased. Vehicles are among the most significant sources of pollutants in urban areas. As such, several studies and public policies emerged to address the issue. Estimating greenhouse emissions and air quality over space and time is crucial for human health and mitigating climate change. In this study, we demonstrate that it is feasible to utilize raw GPS data to measure regional pollution levels. By applying feature engineering techniques and using a microscopic emissions model to calculate vehicle-specific power (VSP) and various specific pollutants, we identify areas with higher emission levels attributable to a fleet of taxis in Porto, Portugal. Additionally, we conduct network analysis to uncover correlations between emission levels and the structural characteristics of the transportation network. These findings can potentially identify emission clusters based on the network's connectivity and contribute to developing an emission inventory for an urban city like Porto.
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关键词
Road emissions,Microscopic emissions model,Vehicle-specific power,Transportation,Climate change,Greenhouse gas,Air pollution,Network analysis,Mobility patterns
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