PuSH - Publikationsserver des Helmholtz Zentrums München: Assessment of German population exposure levels to PM10 based on multiple spatial-temporal data.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

EVA: Veröffentlichen

Neuer EVA Antrag

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Liu, X. ; Huang, H. ; Jiang, Y. ; Wang, T.* ; Xu, Y.* ; Abbaszade, G. ; Schnelle-Kreis, J. ; Zimmermann, R.

Assessment of German population exposure levels to PM10 based on multiple spatial-temporal data.

Environ. Sci. Pollut. Res. 27, 6637-6648 (2020)

DOI

PMC

Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

Abstract
Metriken
Zusatzinfos

Particulate matter is the key to increasing urban air pollution, and research into pollution exposure assessment is an important part of environmental health. In order to classify PM10 air pollution and to investigate the population exposure to the distribution of PM10, daily and monthly PM10 concentrations of 379 air pollution monitoring stations were obtained for a period from 01/01/2017 to 31/12/2017. Firstly, PM10 concentrations were classified using the head/tail break clustering algorithm to identify locations with elevated PM10 levels. Subsequently, population exposure levels were calculated using population-weighted PM10 concentrations. Finally, the power-law distribution was used to test the distribution of PM10 polluted areas. Our results indicate that the head/tail break algorithm, with an appropriate segmentation threshold, can effectively identify areas with high PM10 concentrations. The distribution of the population according to exposure level shows that the majority of people is living in polluted areas. The distribution of heavily PM10 polluted areas in Germany follows the power-law distribution well, but their boundaries differ from the boundaries of administrative cities; some even cross several administrative cities. These classification results can guide policymakers in dividing the country into several areas for pollution control.

Impact Factor

Scopus SNIP

Scopus
Cited By

Altmetric

3.056

1.032