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Estimating Instantaneous Vehicle Emissions

Published: 07 June 2023 Publication History

Abstract

Road transportation emissions have increased in the last few decades and have been the primary source of pollutants in urban areas with ever-growing populations. In this context, it is important to have effective measures to monitor road emissions in regions. Creating an emissions inventory over a region that can map road emissions based on vehicle trips can be helpful. In this work, we show that it is possible to use raw GPS data to estimate vehicle-related levels of pollution in a region. By transforming the data using feature engineering and calculating the vehicle-specific power (VSP) as well as various specific pollutants by using a microscopic emissions model, we show the areas with higher emissions levels made by a fleet of taxis in Porto, Portugal.

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European Environment Agency. 2021. Greenhouse gas emissions from transport in Europe. (2021). https://www.eea.europa.eu/ims/greenhouse-gas-emissions-from-transport
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CM González, CD Gómez, NY Rojas, H Acevedo, and BH Aristizábal. 2017. Relative impact of on-road vehicular and point-source industrial emissions of air pollutants in a medium-sized Andean city. Atmospheric environment 152 (2017), 279--289.
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Luis Moreira-Matias, Joao Gama, Michel Ferreira, Joao Mendes-Moreira, and Luis Damas. 2013. Predicting taxi-passenger demand using streaming data. IEEE Transactions on Intelligent Transportation Systems 14, 3 (2013), 1393--1402.
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Marguerite Nyhan, Stanislav Sobolevsky, Chaogui Kang, Prudence Robinson, Andrea Corti, Michael Szell, David Streets, Zifeng Lu, Rex Britter, Steven RH Barrett, et al. 2016. Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model. Atmospheric environment 140 (2016), 352--363.
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Luc Int Panis, Steven Broekx, and Ronghui Liu. 2006. Modelling instantaneous traffic emission and the influence of traffic speed limits. Science of the total environment 371, 1--3 (2006), 270--285.
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Cited By

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  • (2024)Next Location Prediction with Time-Evolving Markov Models over Data StreamsProgress in Artificial Intelligence10.1007/978-3-031-73503-5_10(115-126)Online publication date: 16-Nov-2024
  • (2023)Pollution Emission Patterns of Transportation in Porto, Portugal Through Network AnalysisProgress in Artificial Intelligence10.1007/978-3-031-49008-8_17(215-226)Online publication date: 15-Dec-2023

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cover image ACM Conferences
SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
March 2023
1932 pages
ISBN:9781450395175
DOI:10.1145/3555776
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Publication History

Published: 07 June 2023

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Author Tags

  1. road emissions
  2. microscopic emissions model
  3. vehicle-specific power
  4. climate change
  5. air pollution

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  • Fundação para a Ciência e a Tecnologia

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2024)Next Location Prediction with Time-Evolving Markov Models over Data StreamsProgress in Artificial Intelligence10.1007/978-3-031-73503-5_10(115-126)Online publication date: 16-Nov-2024
  • (2023)Pollution Emission Patterns of Transportation in Porto, Portugal Through Network AnalysisProgress in Artificial Intelligence10.1007/978-3-031-49008-8_17(215-226)Online publication date: 15-Dec-2023

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