國家衛生研究院 NHRI:Item 3990099045/12478
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    題名: A hybrid kriging/land-use regression model with Asian culture-specific sources to assess NO2 spatial-temporal variations
    作者: Chen, TH;Hsu, YC;Zeng, YT;Candice Lung, SC;Su, HJ;Chao, HJ;Wu, CD
    貢獻者: National Institute of Environmental Health Sciences
    摘要: Kriging interpolation and land use regression (LUR) have characterized the spatial variability of long-term nitrogen dioxide (NO2), but there has been little research on combining these two methods to capture small-scale spatial variation. Furthermore, studies predicting NO2 exposure are almost exclusively based on traffic-related variables, which may not be transferable to Taiwan, a typical Asian country with diverse local emission sources, where densely distributed temples and restaurants may be important for NO2 levels. To advance the exposure estimates in Taiwan, a hybrid kriging/LUR model incorporates culture-specific sources as potential predictors. Based on 14-year NO2 observations from 73 monitoring stations across Taiwan, a set of interpolated NO2 values were generated through a leave-one-out ordinary kriging algorithm, and this was included as an explanatory variable in the stepwise LUR procedures. Kriging interpolated NO2 and culture-specific predictors were entered in the final models, which captured 90% and 87% of NO2 variation in annual and monthly resolution, respectively. Results from 10-fold cross-validation and external data verification demonstrate robust performance of the developed models. This study demonstrates the value of incorporating the kriging-interpolated estimates and culture-specific emission sources into the traditional LUR model structure for predicting NO2, which can be particularly useful for Asian countries.
    日期: 2020-04
    關聯: Environmental Pollution. 2020 Apr;259:Article number 113875.
    Link to: http://dx.doi.org/10.1016/j.envpol.2019.113875
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0269-7491&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000528534600038
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85077325785
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