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Liu, X. ; Hadiatullah, H.* ; Tai, P.* ; Xu, Y.* ; Zhang, X.* ; Schnelle-Kreis, J. ; Schloter-Hai, B. ; Zimmermann, R.

Air pollution in Germany: Spatio-temporal variations and their driving factors based on continuous data from 2008 to 2018.

Environ. Pollut. 276:116732 (2021)
Postprint DOI PMC
Open Access Green
This study analyzed long-term observational data of particulate matter (PM2.5, PM10) variability, gaseous pollutants (CO, NO2, NOX, SO2, and O3), and meteorological factors in 412 fixed monitoring stations from January 2008 to December 2018 in Germany. Based on Hurst index analysis, the trend of atmospheric pollutants in Germany was stable during the research period. The relative correlations of gaseous pollutants and meteorological factors on PM2.5 and PM10 concentrations were analyzed by Back Propagation Neural Network model, showing that CO and temperature had the greater correlations with PM2.5 and PM10. Following that, PM2.5 and PM10 show a strong positive correlation (R2 = 0.96, p < 0.01), suggesting that the reduction of PM2.5 is essential for reducing PM pollution and enhancing air quality in Germany. Based on typical PM10/CO ratios obtained under ideal weather conditions, it is conducive to roughly estimate the contribution of natural sources. In winter, the earth's crust contributed about 20.1% to PM10. Taken together, exploring the prediction methods and analyzing the characteristic variation of pollutants will contribute an essential implication for air quality control in Germany.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Air Pollution ; Gaseous Pollutants ; Meteorological Factors ; Natural Source Contribution ; Spatio-temporal Variation
ISSN (print) / ISBN 0269-7491
e-ISSN 1873-6424
Journal Environmental Pollution
Quellenangaben Volume: 276, Issue: , Pages: , Article Number: 116732 Supplement: ,
Publisher Elsevier
Publishing Place The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1gb, Oxon, England
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Cooperation Group Comprehensive Molecular Analytics (CMA)
Research Unit Comparative Microbiome Analysis (COMI)
Grants Support Project of High-Level Teachers in Beijing Municipal Universities in the Period of 13th Five-Year Plan
China Scholarship Council under the State Scholarship Fund