Editorial: Machine learning in studies of atmospheric environment and climate change

Ying Chen; Wanyun Xu; Jianjun He; Yu Wang

doi:10.3389/fenvs.2023.1280733

Editorial: Machine learning in studies of atmospheric environment and climate change

Ying Chen^*, Wanyun Xu, Jianjun He, Yu Wang

^*Corresponding author for this work

Geography, Earth and Environmental Sciences

Research output: Contribution to journal › Editorial › peer-review

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Original language	English
Article number	1280733
Number of pages	2
Journal	Frontiers in Environmental Science
Volume	11
DOIs	https://doi.org/10.3389/fenvs.2023.1280733
Publication status	Published - 13 Sept 2023

Keywords

air pollution
climate change
atmospheric science
data science
machine learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3389/fenvs.2023.1280733Licence: Creative Commons: Attribution (CC BY)

ChenY2023EditorialFinal published version, 515 KBLicence: Creative Commons: Attribution (CC BY)

Cite this

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title = "Editorial: Machine learning in studies of atmospheric environment and climate change",

keywords = "air pollution, climate change, atmospheric science, data science, machine learning",

author = "Ying Chen and Wanyun Xu and Jianjun He and Yu Wang",

year = "2023",

month = sep,

day = "13",

doi = "10.3389/fenvs.2023.1280733",

language = "English",

volume = "11",

journal = "Frontiers in Environmental Science",

issn = "2296-665X",

publisher = "Frontiers Research Foundation",

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AU - Chen, Ying

AU - Xu, Wanyun

AU - He, Jianjun

AU - Wang, Yu

PY - 2023/9/13

Y1 - 2023/9/13

KW - air pollution

KW - climate change

KW - atmospheric science

KW - data science

KW - machine learning

U2 - 10.3389/fenvs.2023.1280733

DO - 10.3389/fenvs.2023.1280733

M3 - Editorial

SN - 2296-665X

VL - 11

JO - Frontiers in Environmental Science

JF - Frontiers in Environmental Science

M1 - 1280733

ER -