Levels and drivers of urban black carbon and health risk assessment during pre- and COVID19 lockdown in Augsburg, Germany

Xiansheng Liu; Hadiatullah Hadiatullah; Jürgen Schnelle-Kreis; Yanning Xu; Mingqi Yue; Xun Zhang; Xavier Querol; Xin Cao; Jan Bendl; Josef Cyrys; Gert Jakobi; Andreas Philipp; Christoph Münkel; Ralf Zimmermann; Thomas Adam

doi:10.1016/j.envpol.2022.120529

Levels and drivers of urban black carbon and health risk assessment during pre- and COVID19 lockdown in Augsburg, Germany

Environ Pollut. 2023 Jan 1;316(Pt 1):120529. doi: 10.1016/j.envpol.2022.120529. Epub 2022 Oct 28.

Authors

Xiansheng Liu¹, Hadiatullah Hadiatullah², Jürgen Schnelle-Kreis³, Yanning Xu⁴, Mingqi Yue⁵, Xun Zhang⁶, Xavier Querol⁷, Xin Cao⁸, Jan Bendl⁹, Josef Cyrys¹⁰, Gert Jakobi⁵, Andreas Philipp¹¹, Christoph Münkel¹², Ralf Zimmermann¹³, Thomas Adam¹⁴

Affiliations

¹ Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China; University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemical and Environmental Engineering, 85577, Neubiberg, Germany; Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain.
² School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, 300072, China.
³ Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
⁴ School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, 266525, China.
⁵ Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
⁶ Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China; Hotan Normal College. Hotan 848000, Xinjiang, China. Electronic address: zhangxun@btbu.edu.cn.
⁷ Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain.
⁸ School of Sport Science, Beijing Sport University, Beijing, 100084, China.
⁹ University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemical and Environmental Engineering, 85577, Neubiberg, Germany.
¹⁰ Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
¹¹ Institute of Geography, University of Augsburg, Alter Postweg 118, D - 86159, Augsburg, Germany.
¹² Vaisala GmbH, Notkestr. 11, D-22607, Hamburg, Germany.
¹³ Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany; Joint Mass Spectrometry Center, Chair of Analytical Chemistry, University of Rostock, 18059, Rostock, Germany.
¹⁴ University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemical and Environmental Engineering, 85577, Neubiberg, Germany; Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.

PMID: 36341825
DOI: 10.1016/j.envpol.2022.120529

Abstract

This study aimed to evaluate the levels and phenomenology of equivalent black carbon (eBC) at the city center of Augsburg, Germany (01/2018 to 12/2020). Furthermore, the potential health risk of eBC based on equivalent numbers of passively smoked cigarettes (PSC) was also evaluated, with special emphasis on the impact caused by the COVID19 lockdown restriction measures. As it could be expected, peak concentrations of eBC were commonly recorded in morning (06:00-8:00 LT) and night (19:00-22:00 LT) in all seasons, coinciding with traffic rush hours and atmospheric stagnation. The variability of eBC was highly influenced by diurnal variations in traffic and meteorology (air temperature (T), mixing-layer height (MLH), wind speed (WS)) across days and seasons. Furthermore, a marked "weekend effect" was evidenced, with an average eBC decrease of ∼35% due to lower traffic flow. During the COVID19 lockdown period, an average ∼60% reduction of the traffic flow resulted in ∼30% eBC decrease, as the health risks of eBC exposure was markedly reduced during this period. The implementation of a multilinear regression analysis allowed to explain for 53% of the variability in measured eBC, indicating that the several factors (e.g., traffic and meteorology) may contribute simultaneously to this proportion. Overall, this study will provide valuable input to the policy makers to mitigate eBC pollutant and its adverse effect on environment and human health.

Keywords: Black carbon; Health risk; Lockdown effect; Urban pollution.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
COVID-19*
Carbon / analysis
Communicable Disease Control
Environmental Monitoring / methods
Humans
Particulate Matter / analysis
Risk Assessment
Soot / analysis

Substances

Air Pollutants
Soot
Carbon
Particulate Matter