Author Page for Caleb Kelly

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Refining Lung Cancer Risk Assessment from Pm2.5-Bound Pahs: Integrating Component-Based Potency Factors and Machine Learning in Ningbo, China

Number of pages: 73 Posted: 20 Aug 2024

Lord Famiyeh, Honghui Xu, Fiseha Berhanu Tesema, Caleb Kelly, Dongsheng Ji, Hang Xiao, Lei Tong, Ke Chen and Jun He

University of Nottingham, Ningbo - University of Nottingham Ningbo China, Zhejiang Institute of Meteorological Sciences, University of Nottingham, Ningbo - University of Nottingham Ningbo China, University of Nottingham, Ningbo - University of Nottingham Ningbo China, Chinese Academy of Sciences (CAS), Chinese Academy of Sciences (CAS), affiliation not provided to SSRN, University of Nottingham Ningbo China and University of Nottingham, Ningbo - Department of Chemical and Environmental Engineering

Downloads 31 (1,304,549)

Abstract:

Refining Source-Specific Lung Cancer Risk Assessment from Pm2.5-Bound Pahs: Integrating Component-Based Potency Factors and Machine Learning in Ningbo, China

Number of pages: 35 Posted: 19 Nov 2024

Lord Famiyeh, Ke Chen, Fiseha Berhanu Tesema, Caleb Kelly, Dongsheng Ji, Hang Xiao, Lei Tong, Zongshuang Wang and Jun He

University of Nottingham, Ningbo - University of Nottingham Ningbo China, University of Nottingham Ningbo China, University of Nottingham, Ningbo - University of Nottingham Ningbo China, University of Nottingham, Ningbo - University of Nottingham Ningbo China, Chinese Academy of Sciences (CAS), Chinese Academy of Sciences (CAS), affiliation not provided to SSRN, Chinese Research Academy of Environmental Sciences and University of Nottingham, Ningbo - Department of Chemical and Environmental Engineering

Downloads 25 (1,385,945)

Caleb Kelly

University of Nottingham, Ningbo - University of Nottingham Ningbo China

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Scholarly Papers (2)

Refining Lung Cancer Risk Assessment from Pm2.5-Bound Pahs: Integrating Component-Based Potency Factors and Machine Learning in Ningbo, China

Abstract:

Refining Source-Specific Lung Cancer Risk Assessment from Pm2.5-Bound Pahs: Integrating Component-Based Potency Factors and Machine Learning in Ningbo, China

Abstract: