A hybrid kriging/land-use regression model with Asian culture-specific sources to assess NO2 spatial-temporal variations. (April 2020)

• Record Type: Journal Article
• Authors: Chen, Tsun-Hsuan; Hsu, Yen-Ching; Zeng, Yu-Ting; Candice Lung, Shih-Chun; Su, Huey-Jen; Chao, Hsing Jasmine; Wu, Chih-Da
• Is Part Of: Environmental pollution. Volume 259(2020)
• Publication Date: 2020-04
• Subjects: Nitrogen dioxide (NO2) -- Hybrid kriging/LUR model -- Culture-specific sources -- Spatial-temporal variations; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2019.113875
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: 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. Graphical abstract: Image 1 Highlights: A hybrid Kriging/LUR model was applied to assess NO2 variability. High prediction power (R 2 = 0.90) was obtained regardless the model resolutions. A 3–15% increase of R 2 was obtained from the proposed hybrid methodology. Kriging-based NO2 estimates played the most important role in the monthly model. Abstract : The proposed hybrid kriging/LUR model incorporated culture-specific sources provide accurate estimations of NO2 variations of Asia.