28 Jun 2023
 | 28 Jun 2023
Status: a revised version of this preprint is currently under review for the journal AMT.

Quantifying Functional Group Compositions of Household Fuel Burning Emissions

Emily Y. Li, Amir Yazdani, Ann M. Dillner, Guofeng Shen, Wyatt M. Champion, James J. Jetter, William T. Preston, Lynn M. Russell, Michael D. Hays, and Satoshi Takahama

Abstract. Globally, billions of people burn fuels indoors for cooking and heating, which contributes to millions of chronic illnesses and premature deaths annually. Additionally, residential burning contributes significantly to black carbon emissions, which have the highest global warming impacts after carbon dioxide and methane. In this study, we use Fourier transform infrared spectroscopy (FTIR) to analyze fine particulate emissions collected on Teflon membrane filters from fifteen cookstove types and five fuel types. Emissions from three fuel types (charcoal, kerosene, and red oak wood) were found to have enough FTIR spectral response for functional group (FG) analysis. We present distinct spectral profiles for particulate emissions of these three fuel types. We highlight the influential FGs constituting organic carbon (OC) using a multivariate statistical method and show that OC estimates by collocated FTIR and thermal optical transmittance (TOT) are highly correlated, with a coefficient of determination of 82.5 %. As FTIR analysis is fast, non-destructive, and provides complementary FG information, the analysis method demonstrated herein can substantially reduce the need for thermal-optical measurements for source emissions.

Emily Y. Li et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-90', Anonymous Referee #1, 24 Jul 2023
  • RC2: 'Comment on amt-2023-90', Anonymous Referee #2, 24 Aug 2023

Emily Y. Li et al.

Emily Y. Li et al.


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Short summary
Infrared spectroscopy is a cost-effective measurement technique to characterize chemical composition of organic aerosol emissions. This technique differentiates the organic matter emission factor from different fuel sources by their characteristic functional groups. Comparison with collocated measurements suggest polycyclic aromatic hydrocarbon concentrations in emissions estimated by conventional chromatography may be substantially under-estimated.