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Temperature-dependent particle number emission rates and emission characteristics during heating processes of edible oils
School of Architecture, Harbin Institute of Technology; Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, Harbin 150090, China.
School of Architecture, Harbin Institute of Technology; Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, Harbin 150090, China.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Sustainable Buildings.ORCID iD: 0000-0003-1285-2334
Institute of Science and Technology Research and Development, China Academy of Building Research, No.30 Beisanhuandonglu, Beijing 100013, China, No.30 Beisanhuandonglu.
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2023 (English)In: Environmental Pollution, ISSN 0269-7491, E-ISSN 1873-6424, Vol. 333, article id 122045Article in journal (Refereed) Published
Abstract [en]

The goal of this research is to investigate the temperature-dependent emission rates of particle numbers and emission characteristics during oil heating. Seven regularly used edible oils were studied in a variety of tests to attain this objective. First, total particle number emission rates ranging from 10 nm to 1 μm were measured, followed by an examination within six size intervals from 0.3 μm to 10 μm. Following that, the impacts of oil volume and oil surface area on the emission rate were investigated, and multiple regression models were developed based on the results. The results showed that corn, sunflower and soybean oils had higher emission rates than other oils above 200 °C, with peak values of 8.22 × 109#/s, 8.19 × 109#/s and 8.17 × 109#/s, respectively. Additionally, peanut and rice oils were observed to emit the most particles larger than 0.3 μm, followed by medium-emission (rapeseed and olive oils) and low-emission oils (corn, sunflower and soybean oils). In most cases, oil temperature (T) has the most significant influence on the emission rate during the smoking stage, but its influence was not as pronounced in the moderate smoking stage. The models obtained are all statistically significant (P < 0.001), with R2 values greater than 0.9, and the classical assumption test concluded that regressions were in accordance with the classical assumptions regarding normality, multicollinearity, and heteroscedasticity. In general, low oil volume and large oil surface area were more recommended for cooking to mitigate UFPs emission.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 333, article id 122045
Keywords [en]
Cooking pollution, Edible oil, Emission rate, Multiple linear regression, Ultrafine particle
National Category
Environmental Engineering
Identifiers
URN: urn:nbn:se:kth:diva-331418DOI: 10.1016/j.envpol.2023.122045ISI: 001025720100001PubMedID: 37328126Scopus ID: 2-s2.0-85162025927OAI: oai:DiVA.org:kth-331418DiVA, id: diva2:1781260
Note

QC 20230707

Available from: 2023-07-07 Created: 2023-07-07 Last updated: 2023-07-31Bibliographically approved

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Liu, Wei

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