Spatiotemporal Characteristics and Driving Factors of Black Carbon in Augsburg, Germany: Combination of Mobile Monitoring and Street View Images

• Published in: Environmental science & technology Vol. 55; no. 1; pp. 160 - 168
• Main Authors: Liu, Xiansheng, Zhang, Xun, Schnelle-Kreis, Jürgen, Jakobi, Gert, Cao, Xin, Cyrys, Josef, Yang, Lanyan, Schloter-Hai, Brigitte, Abbaszade, Gülcin, Orasche, Jürgen, Khedr, Mohamed, Kowalski, Michal, Hank, Marcus, Zimmermann, Ralf
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 05.01.2021
• Subjects: Air Pollutants - analysis; Black carbon; Carbon; Diurnal variations; Driving; Driving ability; Environmental Monitoring; Equivalence; Germany; Heterogeneity; Meteorological data; Meteorological parameters; Microenvironments; Particulate emissions; Particulate matter; Particulate Matter - analysis; Relative humidity; Soot - analysis; Spatial discrimination; Spatial heterogeneity; Spatial resolution; Traffic; Traffic volume; Trolleys; Vehicle Emissions - analysis; Wind speed; Germany
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/acs.est.0c04776

The study investigates the spatial pattern of black carbon (BC) at a high spatial resolution in Augsburg, Germany. Sixty two walks were performed to assess the concentrations of equivalent black carbon (eBC), ultraviolet particulate matter (UVPM), and equivalent brown carbon (eBrC) in different seasons and at different times of the day with a mobile platform (i.e., trolley). Along with BC measurements, images of street microenvironments were recorded. Meteorological parameters, including temperature, relative humidity, and wind speed, were monitored. The BC concentrations showed significant spatial heterogeneity and diurnal variations peaking in the morning and at night. The highest BC concentrations were observed near dense traffic. The correlations between BC and street views (buildings, roads, cars, and vegetation) were weak but highly significant. Moreover, meteorological factors also influenced the BC concentration. A model based on street view images and meteorological data was developed to examine the driving factors of the spatial variability of BC concentrations at a higher spatial resolution as different microenvironments based on traffic density. The best results were obtained for UVPM and eBC (71 and 70% explained variability). eBrC (53%), to which other sources besides road traffic can also make significant contributions, is modeled less well.