Jiangyue Zhao This email address is being protected from spambots. You need JavaScript enabled to view it.1, Pak Lun Fung2, Martha Arbayani Zaidan2,3, Birgit Wehner4, Kay Weinhold4, Alfred Wiedensohler4, Tareq Hussein This email address is being protected from spambots. You need JavaScript enabled to view it.2,5 

1 Department for Material Analysis and Indoor Chemistry, Fraunhofer WKI, 38108 Braunschweig, Germany
2 Institute for Atmospheric and Earth System Research (INAR/Physics), Faculty of Science, University of Helsinki, PL-64, FI-00014, Helsinki, Finland
3 Department of Computer Science, Faculty of Science, University of Helsinki, 00560 Helsinki, Finland
4 Leibniz Institute for Tropospheric Research (TROPOS), 04318 Leipzig, Germany 
5 Environmental and Atmospheric Research Laboratory (EARL), Department of Physics, School of Science, University of Jordan, Amman 11942, Jordan

Received: September 25, 2023
Revised: February 15, 2024
Accepted: February 20, 2024

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.4209/aaqr.230228  

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Cite this article:

Zhao, J., Fung, P.L., Zaidan, M.A., Wehner, B., Weinhold, K., Wiedensohler, A., Hussein, T. (2024). Indoor Black Carbon Concentrations and their Sources in Residential Environments: Validation of an Input-adaptive Proxy Model. Aerosol Air Qual. Res. 24, 230228. https://doi.org/10.4209/aaqr.230228


  • Equivalent Black Carbon (eBC) mass concentrations were studied for 40 homes.
  • Indoor sources caused higher eBC in the cold seasons than in the warm season.
  • We developed a proxy model to predict indoor eBC using other common pollutant data.
  • The model categorized weather and indoor activities to six scenarios for households.
  • The indoor eBC mass concentration can be predicted accurately with the model.


Exposure to black carbon (BC) in the residential environment was found to be positively associated with elevated blood pressure and cardiovascular disease. However, BC has been under-measured and under-studied compared to other common indoor gaseous and particulate pollutants. Representative indoor mass concentrations of equivalent black carbon (eBC) and the sources' contribution from indoors and outdoors in real-life residential environments in 40 German households were evaluated and presented in this work. During the 500 measurement days, the mean indoor eBC mass concentration was 0.6 µg m–3, which is less than half of the outdoor concentration in the urban background in Germany. However, common indoor sources contributed differently to indoor eBC, which also resulted in higher mass concentrations in the cold season than in the warm season. Indoor pollutant measurements are often performed with only a limited number of instruments and pollutant data. To fill in the missing knowledge of indoor BC, a proxy model was developed. This proxy model can predict indoor eBC concentrations based on existing indoor databases or in cases where direct measurements of indoor eBC concentrations are not available. Due to the complex influence of climate and indoor activities, the model separated six scenarios for weather (including warm and cold seasons) and indoor activities (burning, non-burning, and other activities) for typical urban residential environments in Germany. In this study, indoor eBC mass concentrations were found to be best estimated by indoor and outdoor PM1. For different scenarios, the model achieved a satisfactory to good coefficient of determination (0.49 < R2 < 0.77). With the aid of this model, a more accurate prediction of indoor eBC mass concentration and the resulting exposure and health risk assessment can be achieved for households under similar climatic conditions and activity habits of the occupants, e.g., in Central Europe.

Keywords: Equivalent black carbon measurement, Indoor combustion source, Seasonal variation, Particle number and mass concentrations, White-box model

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