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Orsolya Udvardy

Researcher at National Institutes of Health

Publications -  18
Citations -  1295

Orsolya Udvardy is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Pollen & Ragweed. The author has an hindex of 9, co-authored 16 publications receiving 1065 citations.

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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

TL;DR: The ESCAPE study as discussed by the authors investigated the relationship between long-term exposure to outdoor air pollution and health using cohort studies across Europe, and found substantial variability in spatial patterns of PM2.5, PM10 and PMcoarse.
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Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

TL;DR: In this article, the authors compare the contribution of SAT and chemical transport model (CTM) data to the performance of LUR PM2.5 and NO2 models for Europe.
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Evaluation of land use regression models for NO2 and particulate matter in 20 European study areas: the ESCAPE project.

TL;DR: The results confirm that the predictive ability of LUR models based on relatively small training sets is overestimated by the LOOCV R(2)s, Nevertheless, in most areas Lur models still explained a substantial fraction of the variation of concentrations measured at independent sites.
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Indoor air pollution, physical and comfort parameters related to schoolchildren's health: Data from the European SINPHONIE study.

Ramen Munir Baloch, +137 more
TL;DR: In this paper, the authors examined the association between exposures and the health outcomes using logistic regression models on individual indoor air pollutants (IAPs); a VOC (volatile organic compound) score defined as the sum of the number of pollutants to which the children were highly exposed (concentration N median of the distribution) in classroom was also introduced to evaluate the multiexposure outcome association, while adjusting for several confounding factors.