Kraiwuth Kallawicha1, Shih-Chun Candice Lung2, Ying-Chih Chuang1, Chih-Da Wu3, Tsun-Hsuan Chen4, Ying-Jie Tsai1, Hsing Jasmine Chao 1

  • 1 School of Public Health, Taipei Medical University, Taipei 110, Taiwan
  • 2 Research Center for Environmental Changes, Academia Sinica, Taipei 115, Taiwan
  • 3 Department of Forestry and Natural Resources, National Chiayi University, Chiayi 60004, Taiwan
  • 4 Environmental and Occupational Health Science program, University of Texas Health Science Center at Houston, P.O. Box 20186 Houston, TX 77225, USA

Received: January 20, 2015
Revised: April 13, 2015
Accepted: April 13, 2015
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Cite this article:
Kallawicha, K., Lung, S.C.C., Chuang, Y.C., Wu, C.D., Chen, T.H., Tsai, Y.J. and Chao, H.J. (2015). Spatiotemporal Distributions and Land-Use Regression Models of Ambient Bacteria and Endotoxins in the Greater Taipei Area. Aerosol Air Qual. Res. 15: 1448-1459.


  • Spatiotemporal distributions of ambient bacteria and endotoxin were evaluated.
  • Land-use regression models for ambient bacteria and endotoxin were developed. 
  • The major predictors were meteorological factors and particulates.
  • Schools and gas stations were associated with ambient bacteria and endotoxins.



Ambient bacteria and endotoxins are components of bioaerosols, which are abundant in ambient air. Exposure to ambient bacteria and endotoxins has been associated with respiratory symptoms. We monitored the spatiotemporal distributions of ambient bioaerosols in the Greater Taipei area by using multisite sampling and developed regression models for ambient bacterial and endotoxin concentrations. Forty-four representative sampling sites were selected from the Greater Taipei area. Samples were collected in 4 seasons throughout a 1-y study period. Ambient bacteria were quantified using acridine orange staining, and endotoxins were analyzed using Limulus amebocyte lysate assays. Land-use types and major determinants of the bioaerosols were used to develop regression models. Ambient bacteria ranged from < limit of detection (LOD) to 1.68 × 105 cells/m3, whereas endotoxins ranged from < LOD to 20.62 EU/m3. Significant seasonal variations were observed for both bioaerosols, with the highest concentrations observed in spring. Regression analyses revealed temperature, relative humidity, and particulate matter as the major predictors of ambient bacteria and endotoxins. No land-use type was correlated with any of the bioaerosols. The number of schools and gas stations was positively associated with both bioaerosols. The leave-one-out cross-validation R2 of the final models for ambient bacteria and endotoxins were 0.11 and 0.31, respectively. The results of this study revealed high spatiotemporal variations in the distributions of ambient bacteria and endotoxins in the Greater Taipei area. Additional potential predictors should be included in future studies to develop better predictive models for ambient bacteria and endotoxins.

Keywords: Bioaerosols; Ambient bacteria; Ambient endotoxins; Land-use regression (LUR)

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