Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-6717-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
02 Oct 2025
Methods for assessment of models |
| 02 Oct 2025
| 02 Oct 2025
A close look at using national ground stations for the statistical modeling of NO2
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Cited articles
Algaba, E., Fragnelli, V., and Sánchez-Soriano, J.: Handbook of the Shapley value, CRC Press, https://doi.org/10.1201/9781351241410, 2019. a
Araki, S., Shima, M., and Yamamoto, K.: Spatiotemporal land use random forest model for estimating metropolitan NO2 exposure in Japan, Sci. Total Environ., 634, 1269–1277, 2018. a
Beelen, R., Hoek, G., Vienneau, D., Eeftens, M., Dimakopoulou, K., Pedeli, X., Tsai, M.-Y., Künzli, N., Schikowski, T., Marcon, A., Nawrot, T., Nador, G., Heinrich, J., de Hoogh, K., de Nazelle, A., Neubauer, G., Schindler, C., Schram-Bijkerk, D., Sugiri, D., Gryparis, A., Katsouyanni, K., and Brunekreef, B.: Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project, Atmos. Environ., 72, 10–23, https://doi.org/10.1016/j.atmosenv.2013.02.037, 2013. a, b, c, d
Boersma, F.: A close look at using national ground stations for the statistical mapping of NO2, GitHub [code], https://github.com/FoekeBoersma/A-close-look-at-using-national-ground-stations-for-the-statistical-mapping-of-NO2 (last access: 23 April 2025), 2025a. a, b, c, d
