Assessing the Spatiotemporal Characteristics, Factor Importance, and Health Impacts of Air Pollution in Seoul by Integrating Machine Learning into Land-Use Regression Modeling at High Spatiotemporal Resolutions-Reference-Cited by-同舟云学术

Assessing the Spatiotemporal Characteristics, Factor Importance, and Health Impacts of Air Pollution in Seoul by Integrating Machine Learning into Land-Use Regression Modeling at High Spatiotemporal Resolutions

Published:2023-01-11 Issue:3 Volume:57 Page:1225-1236
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Li Yue¹²,Hong Tageui³,Gu Yefu¹,Li Zhiyuan²,Huang Tao¹,Lee Harry Fung¹,Heo Yeonsook³,Yim Steve H. L.⁴⁵⁶^ORCID

Affiliation:

1. Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin 999077, Hong Kong, China

2. Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin 999077, Hong Kong, China

3. School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea

4. Asian School of the Environment, Nanyang Technological University, Singapore 639798, Singapore

5. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798, Singapore

6. Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798, Singapore

Funder

Dr. Stanley Ho Medicine Development Foundation

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.2c03027

Reference86 articles.

1. Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan

2. Effect of Urbanization on Ozone and Resultant Health Effects in the Pearl River Delta Region of China

3. Advancing environmental exposure assessment science to benefit society

4. Development of the Global to Mesoscale Air Quality Forecast and Analysis System (GMAF) and Its Application to PM2.5 Forecast in Korea

5. Land-use regression with long-term satellite-based greenness index and culture-specific sources to model PM2.5 spatial-temporal variability

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