Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models

This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data increment strategies and multiple machine learning m...

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Bibliographic Details
Published in:	The Science of the total environment Vol. 949; p. 175246
Main Authors:	Wu, Juncheng, Dai, Qili, Song, Shaojie
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.11.2024
Subjects:	air pollutants Air pollution atmospheric pressure BenMap cardiovascular diseases China decision support systems dewpoint environment health effects assessments Health impact assessment Machine learning Meteorological factors mortality prediction Prediction accuracy relative humidity respiratory tract diseases China Prediction accuracy Air pollution Health impact assessment BenMap Meteorological factors Machine learning
ISSN:	0048-9697, 1879-1026, 1879-1026
Online Access:	Get full text
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