气候变化领域集成服务门户(CCPortal): Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan

CCPortal

DOI	10.5194/acp-21-5063-2021
	Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan
	Li Z.; Ho K.-F.; Chuang H.-C.; Hung Lam Yim S.
发表日期	2021
ISSN	1680-7316
起始页码	5063
结束页码	5078
卷号	21 期号:6
英文摘要	To provide long-term air pollutant exposure estimates for epidemiological studies, it is essential to test the feasibility of developing land-use regression (LUR) models using only routine air quality measurement data and to evaluate the transferability of LUR models between nearby cities. In this study, we developed and evaluated the intercity transferability of annual-average LUR models for ambient respirable suspended particulates (PM10), fine suspended particulates (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in the Taipei-Keelung metropolitan area of northern Taiwan in 2019. Ambient PM10, PM2.5, NO2and O3measurements at 30 fixed-site stations were used as the dependent variables, and a total of 156 potential predictor variables in six categories (i.e., population density, road network, land-use type, normalized difference vegetation index, meteorology and elevation) were extracted using buffer spatial analysis. The LUR models were developed using the supervised forward linear regression approach. The LUR models for ambient PM10, PM2.5, NO2and O3achieved relatively high prediction performance, with R2 values of >0.72 and leaveone- out cross-validation (LOOCV) R2 values of >0.53. The intercity transferability of LUR models varied among the air pollutants, with transfer-predictive R2 values of >0.62 for NO2and <0.56 for the other three pollutants. The LUR-model-based 500m500m spatial-distribution maps of these air pollutants illustrated pollution hot spots and the heterogeneity of population exposure, which provide valuable information for policymakers in designing effective air pollution control strategies. The LUR-model-based air pollution exposure estimates captured the spatial variability in exposure for participants in a cohort study. This study highlights that LUR models can be reasonably established upon a routine monitoring network, but there exist uncertainties when transferring LUR models between nearby cities. To the best of our knowledge, this study is the first to evaluate the intercity transferability of LUR models in Asia. © 2021 Copernicus GmbH. All rights reserved.
语种	英语
scopus关键词	atmospheric pollution; concentration (composition); epidemiology; land use; nitrogen dioxide; numerical model; ozone; particulate matter; pollution control; pollution exposure; prediction; regression analysis; Keelung; Taipei; Taiwan
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/247008
作者单位	Institute of Environment Energy and Sustainability, Chinese University of Hong Kong, Shatin, Hong Kong; Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Shatin, Hong Kong; School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Geography and Resource Management, Chinese University of Hong Kong, Shatin, Hong Kong; Stanley Ho Big Data Decision Analytics Research Centre, Chinese University of Hong Kong, Shatin, Hong Kong
推荐引用方式 GB/T 7714	Li Z.,Ho K.-F.,Chuang H.-C.,et al. Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan[J],2021,21(6).
APA	Li Z.,Ho K.-F.,Chuang H.-C.,&Hung Lam Yim S..(2021).Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan.ATMOSPHERIC CHEMISTRY AND PHYSICS,21(6).
MLA	Li Z.,et al."Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan".ATMOSPHERIC CHEMISTRY AND PHYSICS 21.6(2021).