Display options
Cite
Cordioli M, Pironi C, De Munari E, et al. Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO. Sci Total Environ. 2016;574:1075-1084doi: 10.1016/j.scitotenv.2016.09.089.
Cordioli, M., Pironi, C., De Munari, E., Marmiroli, N., Lauriola, P., & Ranzi, A. (2017). Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO. The Science of the total environment, 5741075-1084. https://doi.org/10.1016/j.scitotenv.2016.09.089
Cordioli, M, et al. "Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO." The Science of the total environment vol. 574 (2017): 1075-1084. doi: https://doi.org/10.1016/j.scitotenv.2016.09.089
Cordioli M, Pironi C, De Munari E, Marmiroli N, Lauriola P, Ranzi A. Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO. Sci Total Environ. 2017 Jan 01;574:1075-1084. doi: 10.1016/j.scitotenv.2016.09.089. Epub 2016 Oct 14. PMID: 27672737.
Copy Download .nbib Format: NLM
Share it on

Sci Total Environ. 2017 Jan 01;574:1075-1084. doi: 10.1016/j.scitotenv.2016.09.089. Epub 2016 Oct 14.

Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO.

The Science of the total environment

M Cordioli, C Pironi, E De Munari, N Marmiroli, P Lauriola, A Ranzi

Affiliations

  1. National Interuniversity Consortium for Environmental Sciences (CINSA), Dorsoduro 2137, 30123, Venice, Italy; Environmental Health Reference Centre, Regional Agency for Environmental Protection and Energy of the Emilia-Romagna Region, Via Begarelli 13, Modena, Italy. Electronic address: [email protected].
  2. Regional Agency for Environmental Protection and Energy of the Emilia-Romagna Region, Local district of Parma, Viale Bottego, 9, 43121 Parma, Italy.
  3. National Interuniversity Consortium for Environmental Sciences (CINSA), Dorsoduro 2137, 30123, Venice, Italy.
  4. Environmental Health Reference Centre, Regional Agency for Environmental Protection and Energy of the Emilia-Romagna Region, Via Begarelli 13, Modena, Italy.

PMID: 27672737 DOI: 10.1016/j.scitotenv.2016.09.089

Abstract

The epidemiological research benefits from an accurate characterization of both spatial and temporal variability of exposure to air pollution. This work aims at proposing a method to combine the high spatial resolution of Land Use Regression (LUR) models with the high temporal resolution of fixed site monitoring data, to model spatiotemporal variability of NO

Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords: Air pollution; Exposure assessment; GIS; Land use regression model; Spatiotemporal model

Publication Types