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

• Published in: Environmental pollution (1987) 2020-04, Vol.259, p.113875, Article 113875
• Main Authors: Chen, Tsun-Hsuan, Hsu, Yen-Ching, Zeng, Yu-Ting, Candice Lung, Shih-Chun, Su, Huey-Jen, Chao, Hsing Jasmine, Wu, Chih-Da
• Format: Article
• Language: English
• Subjects: Culture-specific sources; Hybrid kriging/LUR model; Nitrogen dioxide (NO2); Spatial-temporal variations
• ISSN: 0269-7491; 1873-6424
• DOI: 10.1016/j.envpol.2019.113875

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. [Display omitted] •A hybrid Kriging/LUR model was applied to assess NO2 variability.•High prediction power (R2 = 0.90) was obtained regardless the model resolutions.•A 3–15% increase of R2 was obtained from the proposed hybrid methodology.•Kriging-based NO2 estimates played the most important role in the monthly model. The proposed hybrid kriging/LUR model incorporated culture-specific sources provide accurate estimations of NO2 variations of Asia.