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温度依赖性颗粒数排放率及食用油加热过程中的排放特性。

Temperature-dependent particle number emission rates and emission characteristics during heating processes of edible oils.

机构信息

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.

Division of Sustainable Buildings, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Brinellvägen 23, Stockholm, 100 44, Sweden.

出版信息

Environ Pollut. 2023 Sep 15;333:122045. doi: 10.1016/j.envpol.2023.122045. Epub 2023 Jun 14.

Abstract

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 × 10#/s, 8.19 × 10#/s and 8.17 × 10#/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 R 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.

摘要

本研究旨在探究油加热过程中粒子数和排放特性的温度依赖性。为实现这一目标,我们对七种常用食用油进行了多种测试。首先,测量了从 10nm 到 1μm 的总粒子数排放率,然后在 0.3μm 到 10μm 的六个尺寸间隔内进行了检查。接着,研究了油体积和油表面积对排放率的影响,并根据结果建立了多元回归模型。结果表明,玉米油、葵花籽油和大豆油在 200°C 以上的排放率高于其他油,峰值分别为 8.22×10#/s、8.19×10#/s 和 8.17×10#/s。此外,花生油和米糠油排放的大于 0.3μm 的粒子最多,其次是中等排放(菜籽油和橄榄油)和低排放油(玉米油、葵花籽油和大豆油)。在大多数情况下,油温和(T)在吸烟阶段对排放率的影响最大,但在中度吸烟阶段影响不明显。获得的模型均具有统计学意义(P<0.001),R 值大于 0.9,经典假设检验表明回归符合正态性、多重共线性和异方差性的经典假设。总的来说,为了减少 UFP 排放,建议使用低油体积和大油表面积进行烹饪。

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