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10 results on '"Tewis, Marjan"'

3. Impact of COVID-19 containment measures on perceived health and health-protective behavior: a longitudinal study

Author

IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, IRAS – One Health Microbial, van Kersen, Warner, de Rooij, Myrna M T, Portengen, Lützen, Diez, Nekane Sandoval, Pieterson, Inka, Tewis, Marjan, Boer, Jolanda M A, Koppelman, Gerard, Vonk, Judith M, Vermeulen, Roel, Gehring, Ulrike, Huss, Anke, Smit, Lidwien A M, IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, IRAS – One Health Microbial, van Kersen, Warner, de Rooij, Myrna M T, Portengen, Lützen, Diez, Nekane Sandoval, Pieterson, Inka, Tewis, Marjan, Boer, Jolanda M A, Koppelman, Gerard, Vonk, Judith M, Vermeulen, Roel, Gehring, Ulrike, Huss, Anke, and Smit, Lidwien A M

Published
2024

4. Effect of residential relocation on environmental exposures in European cohorts: An exposome-wide approach

Author

IRAS OH Epidemiology Chemical Agents, Saucy, Apolline, Gehring, Ulrike, Olmos, Sergio, Delpierre, Cyrille, de Bont, Jeroen, Gruzieva, Olena, de Hoogh, Kees, Huss, Anke, Ljungman, Petter, Melén, Erik, Persson, Åsa, Pieterson, Inka, Tewis, Marjan, Yu, Zhebin, Vermeulen, Roel, Vlaanderen, Jelle, Tonne, Cathryn, IRAS OH Epidemiology Chemical Agents, Saucy, Apolline, Gehring, Ulrike, Olmos, Sergio, Delpierre, Cyrille, de Bont, Jeroen, Gruzieva, Olena, de Hoogh, Kees, Huss, Anke, Ljungman, Petter, Melén, Erik, Persson, Åsa, Pieterson, Inka, Tewis, Marjan, Yu, Zhebin, Vermeulen, Roel, Vlaanderen, Jelle, and Tonne, Cathryn

Published
2023

8. Spatial variation of PM elemental composition between and within 20 European study areas - Results of the ESCAPE project

Author

Tsai, Ming-Yi, Hoek, Gerard, Eeftens, Marloes, de Hoogh, Kees, Beelen, Rob, Beregszászi, Timea, Cesaroni, Giulia, Cirach, Marta, Cyrys, Josef, De Nazelle, Audrey, de Vocht, Frank, Ducret-Stich, Regina, Eriksen, Kirsten, Galassi, Claudia, Gražuleviciene, Regina, Gražulevicius, Tomas, Grivas, Georgios, Gryparis, Alexandros, Heinrich, Joachim, Hoffmann, Barbara, Iakovides, Minas, Keuken, Menno, Krämer, Ursula, Künzli, Nino, Lanki, Timo, Madsen, Christian, Meliefste, Kees, Merritt, Anne-Sophie, Mölter, Anna, Mosler, Gioia, Nieuwenhuijsen, Mark J, Pershagen, Göran, Phuleria, Harish, Quass, Ulrich, Ranzi, Andrea, Schaffner, Emmanuel, Sokhi, Ranjeet, Stempfelet, Morgane, Stephanou, Euripides, Sugiri, Dorothea, Taimisto, Pekka, Tewis, Marjan, Udvardy, Orsolya, Wang, Meng, Brunekreef, Bert, LS IRAS EEPI ME (Milieu epidemiologie), Dep IRAS, Risk Assessment of Toxic and Immunomodulatory Agents, IRAS RATIA2, LS IRAS EEPI ME (Milieu epidemiologie), Dep IRAS, Risk Assessment of Toxic and Immunomodulatory Agents, and IRAS RATIA2

Subjects
Urban Mobility & Environment, Air-Pollution, Air pollution, Chemical-Composition, Urbanisation, PM2.5, Environment, medicine.disease_cause, Spatial distribution, Absorbance, PM10, Spatial contrasts, medicine, Humans, Cities, Energy-dispersive x-ray fluorescence (ED-XRF), lcsh:Environmental sciences, General Environmental Science, lcsh:GE1-350, Pollutant, Air Pollutants, Analysis of Variance, Trace elements, Chemistry, Cause Mortality, Environmental engineering, Spectrometry, X-Ray Emission, Particulates, PM composition, Oil Fly-Ash, Soot, Europe, Particles, Health, Environmental chemistry, UES - Urban Environment & Safety, Constituents, Exposure assessment, Particulate Matter, Composition (visual arts), Spatial variability, ELSS - Earth, Life and Social Sciences, Long-Term Exposure, Environment & Sustainability, Ambient Particulate Matter, Cohorts, Environmental Monitoring
Abstract

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10.Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM. © 2015 Elsevier Ltd. Chemicals/CAS: copper, 15158-11-9, 7440-50-8; iron, 14093-02-8, 53858-86-9, 7439-89-6; nickel, 7440-02-0; nitrogen oxide, 11104-93-1; potassium, 7440-09-7; silicon, 7440-21-3; sulfur, 13981-57-2, 7704-34-9; vanadium, 7440-62-2; zinc, 7440-66-6, 14378-32-6

Published
2015

9. Spatial variation of PM elemental composition between and within 20 European study areas - Results of the ESCAPE project

Author

LS IRAS EEPI ME (Milieu epidemiologie), Dep IRAS, Risk Assessment of Toxic and Immunomodulatory Agents, IRAS RATIA2, Tsai, Ming-Yi, Hoek, Gerard, Eeftens, Marloes, de Hoogh, Kees, Beelen, Rob, Beregszászi, Timea, Cesaroni, Giulia, Cirach, Marta, Cyrys, Josef, De Nazelle, Audrey, de Vocht, Frank, Ducret-Stich, Regina, Eriksen, Kirsten, Galassi, Claudia, Gražuleviciene, Regina, Gražulevicius, Tomas, Grivas, Georgios, Gryparis, Alexandros, Heinrich, Joachim, Hoffmann, Barbara, Iakovides, Minas, Keuken, Menno, Krämer, Ursula, Künzli, Nino, Lanki, Timo, Madsen, Christian, Meliefste, Kees, Merritt, Anne-Sophie, Mölter, Anna, Mosler, Gioia, Nieuwenhuijsen, Mark J, Pershagen, Göran, Phuleria, Harish, Quass, Ulrich, Ranzi, Andrea, Schaffner, Emmanuel, Sokhi, Ranjeet, Stempfelet, Morgane, Stephanou, Euripides, Sugiri, Dorothea, Taimisto, Pekka, Tewis, Marjan, Udvardy, Orsolya, Wang, Meng, Brunekreef, Bert, LS IRAS EEPI ME (Milieu epidemiologie), Dep IRAS, Risk Assessment of Toxic and Immunomodulatory Agents, IRAS RATIA2, Tsai, Ming-Yi, Hoek, Gerard, Eeftens, Marloes, de Hoogh, Kees, Beelen, Rob, Beregszászi, Timea, Cesaroni, Giulia, Cirach, Marta, Cyrys, Josef, De Nazelle, Audrey, de Vocht, Frank, Ducret-Stich, Regina, Eriksen, Kirsten, Galassi, Claudia, Gražuleviciene, Regina, Gražulevicius, Tomas, Grivas, Georgios, Gryparis, Alexandros, Heinrich, Joachim, Hoffmann, Barbara, Iakovides, Minas, Keuken, Menno, Krämer, Ursula, Künzli, Nino, Lanki, Timo, Madsen, Christian, Meliefste, Kees, Merritt, Anne-Sophie, Mölter, Anna, Mosler, Gioia, Nieuwenhuijsen, Mark J, Pershagen, Göran, Phuleria, Harish, Quass, Ulrich, Ranzi, Andrea, Schaffner, Emmanuel, Sokhi, Ranjeet, Stempfelet, Morgane, Stephanou, Euripides, Sugiri, Dorothea, Taimisto, Pekka, Tewis, Marjan, Udvardy, Orsolya, Wang, Meng, and Brunekreef, Bert

Published
2015

10. Spatial variation of PM elemental composition between and within 20 European study areas--Results of the ESCAPE project.

Author

Tsai MY, Hoek G, Eeftens M, de Hoogh K, Beelen R, Beregszászi T, Cesaroni G, Cirach M, Cyrys J, De Nazelle A, de Vocht F, Ducret-Stich R, Eriksen K, Galassi C, Gražuleviciene R, Gražulevicius T, Grivas G, Gryparis A, Heinrich J, Hoffmann B, Iakovides M, Keuken M, Krämer U, Künzli N, Lanki T, Madsen C, Meliefste K, Merritt AS, Mölter A, Mosler G, Nieuwenhuijsen MJ, Pershagen G, Phuleria H, Quass U, Ranzi A, Schaffner E, Sokhi R, Stempfelet M, Stephanou E, Sugiri D, Taimisto P, Tewis M, Udvardy O, Wang M, and Brunekreef B

Subjects
Analysis of Variance, Cities, Environmental Monitoring methods, Europe, Humans, Spectrometry, X-Ray Emission, Air Pollutants analysis, Air Pollution analysis, Particulate Matter analysis
Abstract

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Published
2015
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