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

Tsun Hsuan Chen, Yen Ching Hsu, Yu Ting Zeng, Shih Chun Candice Lung, Huey Jen Su, Hsing Jasmine Chao, Chih Da Wu

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)


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.

Original languageEnglish
Article number113875
JournalEnvironmental Pollution
Publication statusPublished - 2020 Apr

All Science Journal Classification (ASJC) codes

  • Toxicology
  • Pollution
  • Health, Toxicology and Mutagenesis


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