Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model

Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model

Air pollution related to traffic emissions pose an especially significant problem in cities; this is due to its adverse impact on human health and well-being. Previous studies which have aimed to quantify emissions from the transportation sector have been limited by either simulated or coarsely reso...

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Bibliographic Details
Main Authors: Sobolevsky, Stanislav (Author), Kang, Chaogui (Author), Corti, Andrea (Author), Szell, Michael (Author), Streets, David (Author), Lu, Zifeng (Author), Barrett, Steven R.H (Author), Nyhan, Marguerite (Contributor), Robinson, Prudence (Contributor), Britter, Rex E (Contributor), Ratti, Carlo (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning (Contributor), Massachusetts Institute of Technology. SENSEable City Laboratory (Contributor)
Format: Article
Language:English
Published: Elsevier BV, 2018-10-11T20:10:33Z.
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