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- de Hoogh, Kees, et al.
(författare)
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Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data
- 2016
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Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 151, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR(2): 0.33-0.38). For NO2 CTM improved prediction modestly (adjR(2): 0.58) compared to models without SAT and CTM (adjR(2): 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies.
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| 2. |
- Guxens, Monica, et al.
(författare)
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Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies : the ESCAPE project
- 2016
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Ingår i: Environmental Health Perspectives. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 0091-6765 .- 1552-9924.
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts— CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10‑μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.
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