Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.

Hou J, Wang J, Guo X

DOI: 10.1371/journal.pone.0350301
Published: 2026
Container: PloS one
Publisher: Not recorded
Open access: yes

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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0350301,
  title = {Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.},
  author = {Hou J and Wang J and Guo X},
  year = {2026},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0350301},
  url = {https://doi.org/10.1371/journal.pone.0350301}
}

RIS

TY  - JOUR
TI  - Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.
AU  - Hou J
AU  - Wang J
AU  - Guo X
PY  - 2026
JO  - PloS one
DO  - 10.1371/journal.pone.0350301
UR  - https://doi.org/10.1371/journal.pone.0350301
ER  -

APA

J, H., J, W., & X, G. (2026). Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.. PloS one. https://doi.org/10.1371/journal.pone.0350301

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pubmed · retrieved 2026-09-25T20:52:29.917Z