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9 results on '"Eeftens, M.R."'

1. Spatial contrasts in air pollution and the effects on lung function in children

Author

Eeftens, M.R., Brunekreef, B., Hoek, G., Beelen, R.M.J., and University Utrecht

Subjects
Air pollution, Particulate matter, complex mixtures, Modelling, Lung function, Street canyon
Abstract

Within the framework of the ESCAPE project (European Study of Cohorts for Air Pollution Effects), we aimed to characterize and explain spatial contrasts in ambient air pollution within and between European study areas. Following a standard protocol, project partners selected “street” and “background” measurement sites in 36 study areas, and measured using identical equipment. NO2 and NOX measurements were available from 40 different sites in each area (80 in The Netherlands/Belgium and Catalunya). PM2.5 (particles

Published
2015

3. Systematic evaluation of land use regression models for NO₂

Author

Wang, M., Beelen, R.M.J., Eeftens, M.R., Meliefste, C., Hoek, G., Brunekreef, B., Risk Assessment of Toxic and Immunomodulatory Agents, and Dep IRAS

Abstract

Land use regression (LUR) models have become popular to explain the spatial variation of air pollution concentrations. Independent evaluation is important. We developed LUR models for nitrogen dioxide (NO(2)) using measurements conducted at 144 sampling sites in The Netherlands. Sites were randomly divided into training data sets with a size of 24, 36, 48, 72, 96, 108, and 120 sites. LUR models were evaluated using (1) internal "leave-one-out-cross-validation (LOOCV)" within the training data sets and (2) external "hold-out" validation (HV) against independent test data sets. In addition, we calculated Mean Square Error based validation R(2)s. The mean adjusted model and LOOCV R(2) slightly decreased from 0.87 to 0.82 and 0.83 to 0.79, respectively, with an increasing number of training sites. In contrast, the mean HV R(2) was lowest (0.60) with the smallest training sets and increased to 0.74 with the largest training sets. Predicted concentrations were more accurate in sites with out of range values for prediction variables after changing these values to the minimum or maximum of the range observed in the corresponding training data set. LUR models for NO(2) perform less well, when evaluated against independent measurements, when they are based on relatively small training sets. In our specific application, models based on as few as 24 training sites, however, achieved acceptable hold out validation R(2)s of, on average, 0.60.

Published
2012

5. Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2 – Results of the ESCAPE project

Author

Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Eeftens, M.R., Tsai, M-Y., Ampe, C., Anwander, B., Beelen, R.M.J., Bellander, T., Cesaroni, G., Cirach, M., Cyrys, J., de Hoogh, K., de Nazelle, A., de Vocht, F., Declercq, C., Dėdelė, A., Eriksen, K., Galassi, C., Gražulevičienė, R., Grivas, G., Heinrich, J., Hoffmann, B., Iakovides, M., Ineichen, A., Katsouyanni, K., Korek, M., Krämer, U., Kuhlbusch, T., Lanki, T., Madsen, C., Meliefste, K., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Oldenwening, M., Pennanen, A., Probst-Hensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Stephanou, E., Sugiri, D., Udvardy, O., Vaskövi, É., Weinmayr, G., Brunekreef, B., Hoek, G., Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Eeftens, M.R., Tsai, M-Y., Ampe, C., Anwander, B., Beelen, R.M.J., Bellander, T., Cesaroni, G., Cirach, M., Cyrys, J., de Hoogh, K., de Nazelle, A., de Vocht, F., Declercq, C., Dėdelė, A., Eriksen, K., Galassi, C., Gražulevičienė, R., Grivas, G., Heinrich, J., Hoffmann, B., Iakovides, M., Ineichen, A., Katsouyanni, K., Korek, M., Krämer, U., Kuhlbusch, T., Lanki, T., Madsen, C., Meliefste, K., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Oldenwening, M., Pennanen, A., Probst-Hensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Stephanou, E., Sugiri, D., Udvardy, O., Vaskövi, É., Weinmayr, G., Brunekreef, B., and Hoek, G.

Published
2012

6. Systematic evaluation of land use regression models for NO₂

Author

Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Wang, M., Beelen, R.M.J., Eeftens, M.R., Meliefste, C., Hoek, G., Brunekreef, B., Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Wang, M., Beelen, R.M.J., Eeftens, M.R., Meliefste, C., Hoek, G., and Brunekreef, B.

Published
2012

7. Development of Land Use Regression Models for PM(2.5), PM(2.5) Absorbance, PM(10) and PM(coarse) in 20 European Study Areas; Results of the ESCAPE Project.

Author

Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Eeftens, M.R., Beelen, R.M.J., de Hoogh, K., Bellander, T., Cesaroni, G., Cirach, M., Declercq, C., Dedele, A., Dons, E., de Nazelle, A., Dimakopoulou, K., Eriksen, K., Falq, G., Fischer, P., Galassi, C., Grazuleviciene, R., Heinrich, J., Hoffmann, B., Jerrett, M., Keidel, D., Korek, M., Lanki, T., Lindley, S., Madsen, C., Molter, A., Nador, G., Nieuwenhuijsen, M., Nonnemacher, M., Pedeli, X., Raaschou-Nielsen, O., Patelarou, E., Quass, U., Ranzi, A., Schindler, C., Stempfelet, M., Stephanou, E., Sugiri, D., Tsai, M.Y., Yli-Tuomi, T., Varro, M.J., Vienneau, D., von Klot, S., van der Wolf, K., Brunekreef, B., Hoek, G., Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Eeftens, M.R., Beelen, R.M.J., de Hoogh, K., Bellander, T., Cesaroni, G., Cirach, M., Declercq, C., Dedele, A., Dons, E., de Nazelle, A., Dimakopoulou, K., Eriksen, K., Falq, G., Fischer, P., Galassi, C., Grazuleviciene, R., Heinrich, J., Hoffmann, B., Jerrett, M., Keidel, D., Korek, M., Lanki, T., Lindley, S., Madsen, C., Molter, A., Nador, G., Nieuwenhuijsen, M., Nonnemacher, M., Pedeli, X., Raaschou-Nielsen, O., Patelarou, E., Quass, U., Ranzi, A., Schindler, C., Stempfelet, M., Stephanou, E., Sugiri, D., Tsai, M.Y., Yli-Tuomi, T., Varro, M.J., Vienneau, D., von Klot, S., van der Wolf, K., Brunekreef, B., and Hoek, G.

Published
2012

8. Variation of NO2 and NOx concentrations between and within 36 European study areas: Results from the ESCAPE study

Author

Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Cyrys, J., Eeftens, M.R., Heinrich, J., Ampe, C., Armengaud, A., Beelen, R., Bellander, T., Beregszaszi, T., Birk, M., Cesaroni, G., Cirach, M., de Hoogh, K., de Nazelle, A., de Vocht, F., Declercq, C., Dėdelė, A., Dimakopoulou, K., Eriksen, K., Galassi, C., Grąulevičienė, R., Grivas, G., Gruzieva, O., Gustafsson, A.H., Hoffmann, B., Iakovides, M., Ineichen, A., Krämer, U., Lanki, T., Lozano, P., Madsen, C., Meliefste, K., Modig, L., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Nonnemacher, M., Oldenwening, M., Peters, A., Pontet, S., Probst-Hensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Sugiri, D., Stephanou, E.G., Taimisto, P., Tsai, M-Y., Vaskövi, É., Villani, S., Wang, M., Brunekreef, B., Hoek, G., Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS, Cyrys, J., Eeftens, M.R., Heinrich, J., Ampe, C., Armengaud, A., Beelen, R., Bellander, T., Beregszaszi, T., Birk, M., Cesaroni, G., Cirach, M., de Hoogh, K., de Nazelle, A., de Vocht, F., Declercq, C., Dėdelė, A., Dimakopoulou, K., Eriksen, K., Galassi, C., Grąulevičienė, R., Grivas, G., Gruzieva, O., Gustafsson, A.H., Hoffmann, B., Iakovides, M., Ineichen, A., Krämer, U., Lanki, T., Lozano, P., Madsen, C., Meliefste, K., Modig, L., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Nonnemacher, M., Oldenwening, M., Peters, A., Pontet, S., Probst-Hensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Sugiri, D., Stephanou, E.G., Taimisto, P., Tsai, M-Y., Vaskövi, É., Villani, S., Wang, M., Brunekreef, B., and Hoek, G.

Published
2012

9. Developments and future prospects of land-use regression modelling

Author

Eeftens, M.R., Hoek, G. (Thesis Advisor), Eeftens, M.R., and Hoek, G. (Thesis Advisor)

Abstract

In recent years, land-use regression (LUR) modelling has become a popular method to assess the spatial variation of outdoor air pollution for large geographical areas. The technique is often used to estimate exposure estimates for individual study subjects in large epidemiological studies. Land-use regression studies combine measurements from an air pollution monitoring network in the study area with predictor variables, obtained through geographic information systems (GIS). Stochastic modelling is used to determine which of these variables best predict the pollution concentrations measured at each location of the network, after which the resulting model can be applied to estimate individual exposure levels for non-network locations. Current approaches for modelling intra-urban contrasts in pollution commonly use population density, land use, physical geography and various traffic-related variables to predict pollution concentrations. The objective of this thesis is to present an overview of several promising expansions to regular LUR models and assess the requirements and possibilities for their application in exposure assessment modelling for epidemiological studies. We also discuss some current problems in the application of LUR models to predict accurate concentrations, and suggest ways to overcome these problems by integrating different new elements into LUR modelling. Recent developments have been able to increase explained spatial variability of LUR models further by incorporating predictor variables like winter woodsmoke in residential areas, which make up a significant part of particulate matter pollution in several colder parts of the developed world. Street configuration (e.g. street canyons) has been dealt with by incorporating freely available remote sensing data. Furthermore, several papers present an increased temporal resolution, while “hybrid” models attempt to use emission data in combination with meteorological changes, as has been done earlier in

Published
2009

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