globalchange  > 气候变化事实与影响
DOI: 10.1016/j.atmosenv.2014.12.004
Scopus ID: 2-s2.0-84918526736
The application of semicircular-buffer-based land use regression models incorporating wind direction in predicting quarterly NO2 and PM10 concentrations
Author: Li X; , Liu W; , Chen Z; , Zeng G; , Hu C; M; , León T; , Liang J; , Huang G; , Gao Z; , Li Z; , Yan W; , He X; , Lai M; , He Y
Source Publication: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
Publishing Year: 2015
Volume: 103
pages begin: 18
pages end: 24
Language: 英语
Keyword: Land use regression (LUR) ; Nitrogen dioxide (NO2) ; Particulate matter (PM10) ; Semicircular buffer ; Wind direction
Scopus Keyword: Geographic information systems ; Nitrogen ; Nitrogen oxides ; Regression analysis ; Land use regression ; Nitrogen dioxides ; Particulate Matter ; Semicircular buffer ; Wind directions ; Land use ; buffer ; nitrogen dioxide ; buffer zone ; concentration (composition) ; GIS ; land use change ; location-allocation model ; nitrogen dioxide ; particulate matter ; regression analysis ; spatial distribution ; urban area ; wind direction ; air monitoring ; Article ; China ; concentration (parameters) ; geographic information system ; land use ; particulate matter ; predictor variable ; urban area ; wind ; Changsha ; China ; Hunan
Subject of Scopus: Environmental Science: Water Science and Technology ; Earth and Planetary Sciences: Earth-Surface Processes ; Environmental Science: Environmental Chemistry
English Abstract: Land use regression (LUR) models have proven to be a robust technique for predicting spatial distribution of pollutants with high resolution. Wind direction is an important factor affecting atmospheric environment quality. However, conventional LUR models have difficulties taking wind direction into consideration. This study put forward a semicircular-buffer-based (SCBB) LUR model to overcome this challenge. To assess the impact of wind direction on model performance, we set up two different LUR models for nitrogen dioxide (NO2) and particulate matter (PM10) in the urban area of Changsha, China. A location-allocation approach was used to identify sampling sites. Integrated 14-day mean concentrations of NO2 and PM10 were measured at 80 sites and 40 sites, respectively. Measured mean concentrations ranged from 17.0 to 75.7 for NO2 and 34.7 to 118.7μg/m3 for PM10. Random samples of 75% of monitoring sites were used to the develop model and the remaining 25% of sites were retained for evaluation. Predictor variables were created in a geographic information system (GIS) and LUR models were developed with the most significant variables. The results showed SCBB LUR models had significantly higher R2 values than traditional LUR models, supporting the feasibility of this new approach incorporating wind direction in the LUR model. © 2014 Elsevier Ltd.
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Document Type: 期刊论文
Appears in Collections:气候变化事实与影响

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Affiliation: College of Environmental Science and Engineering, Hunan University, Changsha, China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, China; College of Information Science and Technology, Hunan University, Changsha, Hunan, China; School of Public Health, University of California, Berkeley, CA, United States; Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada

Recommended Citation:
Li X,, Liu W,, Chen Z,et al. The application of semicircular-buffer-based land use regression models incorporating wind direction in predicting quarterly NO2 and PM10 concentrations[J]. Atmospheric Environment,2015-01-01,103
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