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What Drives Air Pollution in China? Evidence from Interpretable Machine Learning and Spatial Analysis of PM2.5
https://agi.repo.nii.ac.jp/records/2000265
https://agi.repo.nii.ac.jp/records/2000265ed1556f5-e090-425c-a956-e0fa180f3d4e
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
report2025-05.pdf (4.9 MB)
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| アイテムタイプ | 調査報告書/Research Reports(1) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2026-03-31 | |||||||||||
| タイトル | ||||||||||||
| タイトル | What Drives Air Pollution in China? Evidence from Interpretable Machine Learning and Spatial Analysis of PM2.5 | |||||||||||
| 言語 | en | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| キーワード | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | China | |||||||||||
| キーワード | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | PM2.5 | |||||||||||
| キーワード | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Machine Learning | |||||||||||
| キーワード | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Spatial analysis | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_18ws | |||||||||||
| 資源タイプ | research report | |||||||||||
| 研究代表者 |
ドミンゲス, アルバロ
× ドミンゲス, アルバロ
WEKO
327
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| 報告年度 | ||||||||||||
| 日付 | 2026-03 | |||||||||||
| 日付タイプ | Issued | |||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | This paper investigates the determinants of fine particulate matter (PM2.5) across 31 Chinese provinces during 2004–2020, a period of rapid economic transformation accompanied by rising environmental pressures. Using a provincial panel dataset and a flexible empirical framework, we identify the economic, demographic, and energy-related factors most closely associated with regional variation in air quality. Population pressure and the composition of the regional energy mix emerge as the most influential predictors, while higher levels of solar and wind power capacity are associated with lower predicted pollution. The analysis also reveals substantial geographic heterogeneity, indicating that the drivers of air quality differ markedly across regions. These findings underscore the importance of geographically targeted environmental policies that simultaneously expand renewable energy capacity and address urban emission sources, particularly in densely populated provinces. | |||||||||||
| 言語 | en | |||||||||||
| 著者版フラグ | ||||||||||||
| 出版タイプ | NA | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_be7fb7dd8ff6fe43 | |||||||||||
