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Indoor PM2.5 Characteristics and CO Concentration Related to Water-Based and Oil-Based Cooking Emissions Using a Gas Stove

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Volume: 11 | Issue: 4 | Pages: 401-411
DOI: 10.4209/aaqr.2011.02.0016
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Haryono S. Huboyo 1, Susumu Tohno1, Renqiu Cao2

  • 1 Dept of Socio-Environmental Energy Science, Graduate School of Energy Science, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
  • 2 Tokyo Dylec Co., Shinjuku-ku, Tokyo 160-0014, Japan

Abstract

Pollutant emissions from indoor cooking activities using clean fuels such as natural gas or LPG are strongly influenced by cooking ingredients and cooking methods. In this study, we explore the characterization of indoor fine particles (PM2.5) and CO that are produced by two distinctive cooking methods: frying and boiling. This characterization includes quantifying the presence of fine particles in a kitchen as well as in the adjoining room, analyzing size-segregated carbonaceous materials (EC and OC), and identifying variations in CO associated with the cooking method. Four monitoring devices—a UCB particle monitor, an optical particle counter, a cascade impactor, and a CO monitor—were simultaneously used to measure temporal variations in mass concentrations of fine particles (PM2.5), particle number concentrations, their size distributions, and CO concentrations in the two rooms, respectively. EC and OC analyses of the particles collected on a quartz filter by cascade impactor were conducted using the thermal optical method. Frying produced higher emissions of fine particles with a wider range of aerodynamic sizes than boiling. Particle spatial distribution was uniform across the rooms during boiling, because emissions were dominated by very fine particle size. It was observed that particle mass size distributions with cut size ≤ 0.25 µm were predominant in all cooking methods. CO concentration was lowest in tofu boiling and about one-tenth of the stove background level. This is possibly due to the absorption of CO by steam cooking.

Keywords

Indoor air pollution Fine particles Size distribution Temporal variation


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