A stochastic exposure model integrating random forest and agent-based approaches: Evaluation for PM2.5 in Jiangsu, China-Reference-Cited by-同舟云学术

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A stochastic exposure model integrating random forest and agent-based approaches: Evaluation for PM2.5 in Jiangsu, China

Published:2022-06 Issue: Volume:431 Page:128639
ISSN:0304-3894
Container-title:Journal of Hazardous Materials
language:en
Short-container-title:Journal of Hazardous Materials

Author:

Zhou Qi,Wang Xin,Shu Ye,Sun Li,Jin Zhou,Ma Zongwei,Liu Miaomiao,Bi Jun,Kinney Patrick L.

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

China Scholarship Council

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference40 articles.

1. A spatio-temporally weighted hybrid model to improve estimates of personal PM2.5 exposure: Incorporating big data from multiple data sources;Ben;Environ. Pollut.,2019

2. Seasonal characteristics of indoor and outdoor fine particles and their metallic compositions in Nanjing, China;Bi;Build. Environ.,2018

3. Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina;Breen;Environ. Sci. Technol.,2015

4. A population exposure model for particulate matter: case study results for PM2.5 in Philadelphia, PA;Burke;J. Expo. Anal. Environ. Epidemiol.,2001

5. Estimation of personal exposure to fine particles (PM2.5) of ambient origin for healthy adults in Hong Kong;Chen;Sci. Total Environ.,2019

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