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Process-informed machine learning for interpretable air-quality prediction in tropical coastal cities of Sulawesi, Indonesia

delete2026-07-07
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PRE
AI
A
Asif Awaludin *
N
Nani Cholianawati
L
Listi Restu Triani
A
Asri Indrawati
G
Ginaldi Ari Nugroho
P
Prawira Yudha Kombara
S
Sany Indra Putra
A
Aufa Zalfarani Saprudin
T
Tiin Sinatra
E
Eka Dian Pusfitasari
I
Ibnu Fathrio
N
null Halimurrahman
A
Aisya Nafiisyanti
D
Dyah Aries Tanti
D
Dipo Yudhatama
R
Rizky Tazkia
DOI：10.1016/j.atmosenv.2026.122207delete
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Abstract

Abstract

En 中文
• Process-informed ML improved pollutant prediction, with R2 reaching 0.85. • Robust CCM links were found for rainfall–PM2.5 and rainfall–PM10. • SHAP revealed city-specific reliance on particulate, gaseous, and meteorological predictors.

Journal

Atmospheric Environment cover
Atmospheric Environment
IF:
3.7
Papers:
1.3K
Citations:
5.6W

Organization

B
brin
Scholars:
356
Papers: 115
Citations: 1
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