Dataset for: Deep Learning Attribution Reveals Global Climate-Amplified Smoke Penalty on Particulate Mitigation

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

Read full text
Authors: Tao Chenliang, Zhang Yuqiang, Drew T. Shindell, Zhang Hongliang
DOI: 10.5281/zenodo.18585348
Cited by: 0

Abstract

This dataset provides the projected annual mean concentrations of PM2.5 induced by fires under future climate change scenarios. The data was generated using a multi-model, multi-ensemble deep learning framework designed to capture the complex non-linear interactions between climate variables and fire emissions. Temporal Coverage: 2000-2010, 2040-2050, and 2090-2100 Spatial Resolution: 1˚×1˚ Unit: Micrograms per cubic meter (μg/m3) Variable: Fire-induced PM2.5 annual mean concentration

Fields of Study & Subjects

Fire effects on ecosystems Atmospheric chemistry and aerosols Air Quality and Health Impacts

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 February 2026
Language
EN
Document type
Dataset