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Open AccessArticle

Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration

1
National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli 35053, Taiwan
2
Department of Forestry and Natural Resources, National Chiayi University, Chiayi 60004, Taiwan
3
Institute of Environmental and Occupational Health Sciences, National Yang-Ming University, Taipei 11221, Taiwan
4
Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
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Department of Atmospheric Sciences, National Taiwan University, Taipei 10617, Taiwan
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Institute of Environmental Health, School of Public Health, National Taiwan University, Taipei 10055, Taiwan
7
Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taipei 10055, Taiwan
8
Department of Geomatics, National Cheng Kung University, Tainan 70101, Taiwan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(7), 1300; https://doi.org/10.3390/ijerph16071300
Received: 27 February 2019 / Revised: 25 March 2019 / Accepted: 4 April 2019 / Published: 11 April 2019
(This article belongs to the Special Issue Spatio-Temporal Environmental Monitoring and Social Sensing)
This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency’s (EPA) data of O3 concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R2 of 0.74 and a 10-fold cross-validated R2 of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O3 concentration variation in Asian areas. View Full-Text
Keywords: land use regression (LUR); ozone; Asian culturally specific source; temple; spatial-temporal variability land use regression (LUR); ozone; Asian culturally specific source; temple; spatial-temporal variability
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Hsu, C.-Y.; Wu, J.-Y.; Chen, Y.-C.; Chen, N.-T.; Chen, M.-J.; Pan, W.-C.; Lung, S.-C.C.; Guo, Y.L.; Wu, C.-D. Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration. Int. J. Environ. Res. Public Health 2019, 16, 1300.

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