Quantifying functional group compositions of household fuel-burning emissions

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 15 cookstove types and 5 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 determination of 82.5ĝ€¯%. As FTIR analysis is fast and non-destructive and provides complementary FG information, the analysis method demonstrated herein can substantially reduce the need for thermal-optical measurements for source emissions.