Your browser doesn't support javascript.
Observed coupling between air mass history, secondary growth of nucleation mode particles and aerosol pollution levels in Beijing.
Hakala, S; Vakkari, V; Bianchi, F; Dada, L; Deng, C; Dällenbach, K R; Fu, Y; Jiang, J; Kangasluoma, J; Kujansuu, J; Liu, Y; Petäjä, T; Wang, L; Yan, C; Kulmala, M; Paasonen, P.
  • Hakala S; Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology Beijing China.
  • Vakkari V; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki Helsinki Finland simo.hakala@helsinki.fi.
  • Bianchi F; Finnish Meteorological Institute Erik Palmenin Aukio 1 Helsinki Finland.
  • Dada L; Atmospheric Chemistry Research Group, Chemical Resource Beneficiation, North-West University Potchefstroom South Africa.
  • Deng C; Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology Beijing China.
  • Dällenbach KR; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki Helsinki Finland simo.hakala@helsinki.fi.
  • Fu Y; Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology Beijing China.
  • Jiang J; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki Helsinki Finland simo.hakala@helsinki.fi.
  • Kangasluoma J; Extreme Environments Research Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL) Valais Sion 1951 Switzerland.
  • Kujansuu J; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute 5232 Villigen Switzerland.
  • Liu Y; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University Beijing China.
  • Petäjä T; Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology Beijing China.
  • Wang L; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki Helsinki Finland simo.hakala@helsinki.fi.
  • Yan C; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute 5232 Villigen Switzerland.
  • Kulmala M; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University Beijing China.
  • Paasonen P; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University Beijing China.
Environ Sci Atmos ; 2(2): 146-164, 2022 Mar 17.
Article in English | MEDLINE | ID: covidwho-1788325
ABSTRACT
Atmospheric aerosols have significant effects on the climate and on human health. New particle formation (NPF) is globally an important source of aerosols but its relevance especially towards aerosol mass loadings in highly polluted regions is still controversial. In addition, uncertainties remain regarding the processes leading to severe pollution episodes, concerning e.g. the role of atmospheric transport. In this study, we utilize air mass history analysis in combination with different fields related to the intensity of anthropogenic emissions in order to calculate air mass exposure to anthropogenic emissions (AME) prior to their arrival at Beijing, China. The AME is used as a semi-quantitative metric for describing the effect of air mass history on the potential for aerosol formation. We show that NPF events occur in clean air masses, described by low AME. However, increasing AME seems to be required for substantial growth of nucleation mode (diameter < 30 nm) particles, originating either from NPF or direct emissions, into larger mass-relevant sizes. This finding assists in establishing and understanding the connection between small nucleation mode particles, secondary aerosol formation and the development of pollution episodes. We further use the AME, in combination with basic meteorological variables, for developing a simple and easy-to-apply regression model to predict aerosol volume and mass concentrations. Since the model directly only accounts for changes in meteorological conditions, it can also be used to estimate the influence of emission changes on pollution levels. We apply the developed model to briefly investigate the effects of the COVID-19 lockdown on PM2.5 concentrations in Beijing. While no clear influence directly attributable to the lockdown measures is found, the results are in line with other studies utilizing more widely applied approaches.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Environ Sci Atmos Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Environ Sci Atmos Year: 2022 Document Type: Article