Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions.

Qiu M, Zigler C, Selin NE

DOI: 10.5194/acp-22-10551-2022
Published: 2022
Container: Atmospheric chemistry and physics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.5194/acp-22-10551-2022,
  title = {Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions.},
  author = {Qiu M and Zigler C and Selin NE},
  year = {2022},
  journal = {Atmospheric chemistry and physics},
  doi = {10.5194/acp-22-10551-2022},
  url = {https://doi.org/10.5194/acp-22-10551-2022}
}

RIS

TY  - JOUR
TI  - Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions.
AU  - Qiu M
AU  - Zigler C
AU  - Selin NE
PY  - 2022
JO  - Atmospheric chemistry and physics
DO  - 10.5194/acp-22-10551-2022
UR  - https://doi.org/10.5194/acp-22-10551-2022
ER  -

APA

M, Q., C, Z., & NE, S. (2022). Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions.. Atmospheric chemistry and physics. https://doi.org/10.5194/acp-22-10551-2022

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pubmed · retrieved 2026-09-26T11:09:38.623Z