2022
Journal article  Open Access

Gross polluters and vehicle emissions reduction

Bohm M., Nanni M., Pappalardo L.

Traffic emissions  Fuel consumption  Urban  Congestion  Patterns  Travel 

Vehicle emissions produce an important share of a city's air pollution, with a substantial impact on the environment and human health. Traditional emission estimation methods use remote sensing stations, missing the full driving cycle of vehicles, or focus on a few vehicles. We have used GPS traces and a microscopic model to analyse the emissions of four air pollutants from thousands of private vehicles in three European cities. We found that the emissions across the vehicles and roads are well approximated by heavy-tailed distributions and thus discovered the existence of gross polluters, vehicles responsible for the greatest quantity of emissions, and grossly polluted roads, which suffer the greatest amount of emissions. Our simulations show that emissions reduction policies targeting gross polluters are far more effective than those limiting circulation based on an uninformed choice of vehicles. Our study contributes to shaping the discussion on how to measure emissions with digital data.

Source: Nature sustainability (2022). doi:10.1038/s41893-022-00903-x

Publisher: Macmillan Publishers part of Springer Nature


Metrics



Back to previous page
BibTeX entry
@article{oai:it.cnr:prodotti:468812,
	title = {Gross polluters and vehicle emissions reduction},
	author = {Bohm M. and Nanni M. and Pappalardo L.},
	publisher = {Macmillan Publishers part of Springer Nature},
	doi = {10.1038/s41893-022-00903-x},
	journal = {Nature sustainability},
	year = {2022}
}

Track and Know
Big Data for Mobility Tracking Knowledge Extraction in Urban Areas

HumanE-AI-Net
HumanE AI Network

SoBigData-PlusPlus
SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics


OpenAIRE