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Differenzierung der Feinstaubexposition in Deutschland nach sozioökonomischem Status : Sachverständigengutachten im Auftrag des Umweltbundesamts
Publikationstyp
Research Report
Date Issued
2021
Sprache
German
Author(s)
Gaffron, Philine
Herausgeber*innen
Institut
First published in
Number in series
03/2021
Citation
Umwelt & Gesundheit 3: (2021)
Publisher
Umweltbundesamt
Peer Reviewed
false
Abstract: Differentiating exposure to particulate matter in Germany by socioeconomic status. Air pollution is a significant risk factor for human health. This study investigated the possibility for differentiating the population exposure to particulate matter by socio-economic status in Germany. A nationwide dataset on PM2.5 background concentrations at a resolution of 2 x 2 km² was used to quantify exposure. PM2.5 datasets for the cities of Hamburg (total concentrations at 100 x 100 m²) and Berlin (background concentrations at 500 x 500 m²) were used for additional local analyses. The annual net household income (at 1 x 1 km²) as well as housing rent and pur-chase price indices (at block level) were used as indicators for socio-economic status (SES). Data pre-processing included validation of housing block data, population weighting, spatial aggrega-tion and SES-standardization at municipal level. The relevant variables for the three study areas
were overlaid and their statistical relationships examined using spatial regression and Analysis of Variance (ANOVA) models. Some correlations between particulate matter concentrations and SES variables were significant but weak in magnitude, without clear trends and not fully con-sistent across the study areas. Overall, the data thus did not allow for a reliable differentiation of PM2.5 exposure as the variables with country-wide coverage offered only limited information on the population’s SES. The household income variable was considered to be a meaningful indica-tor for SES but its spatial resolution was too coarse to depict fine-scale variations. Residential
rent and purchase price indices on the other hand had an appropriate spatial resolution but represented SES only in approximation. In order to differentiate exposure to particulate matter by SES in Germany, future studies would require nationwide datasets with finer spatial resolutions.
were overlaid and their statistical relationships examined using spatial regression and Analysis of Variance (ANOVA) models. Some correlations between particulate matter concentrations and SES variables were significant but weak in magnitude, without clear trends and not fully con-sistent across the study areas. Overall, the data thus did not allow for a reliable differentiation of PM2.5 exposure as the variables with country-wide coverage offered only limited information on the population’s SES. The household income variable was considered to be a meaningful indica-tor for SES but its spatial resolution was too coarse to depict fine-scale variations. Residential
rent and purchase price indices on the other hand had an appropriate spatial resolution but represented SES only in approximation. In order to differentiate exposure to particulate matter by SES in Germany, future studies would require nationwide datasets with finer spatial resolutions.
Subjects
Umweltgerechtigkeit
Feinstaubexposition
PM 2.5
GIS
Deutschland
Hamburg
Berlin
DDC Class
300: Sozialwissenschaften, Soziologie
330: Wirtschaft
500: Naturwissenschaften