Temperature-dependent particle mass emission rate during heating of edible oils and their regression models.
Temperature-dependent particle mass emission rate during heating of edible oils and their regression models.
复制标题
DOI：
10.1016/j.envpol.2023.121221
复制
发表时间：
2023-02
影响因子：
8.9
通讯作者：
Shengyuan Ma;W. Liu;Chong Meng;Jiankai Dong;Shizheng Zhang
中科院分区：
文献类型：
--
作者：
Shengyuan Ma;W. Liu;Chong Meng;Jiankai Dong;Shizheng Zhang
加热食用油排放的颗粒物对人体健康有害。要制定有效的缓解策略，了解排放颗粒物的数量至关重要。本研究的目的是估计食用油颗粒质量释放率随温度的变化，并建立基于多元线性回归方法的来源强度模型。首先，本研究通过加热实验检测了七种常用油脂。测量了PM2.5和PM10的排放速率，分析了油量、比表面积等参数对排放速率的影响。然后测定了试验油的起始烟点(Ts‘)和加重烟点(Tss’)。结果表明，烟点较低的机油具有较大的排放速率。值得注意的是，在240℃的温度下，花生、大米、油菜籽和橄榄油产生PM2.5的速度(最高排放条件下分别为2.22、1.50、0.82和0.80 mg/S)远远快于葵花籽油、大豆和玉米油(分别为0.15、0.12和0.11 mg/S)。油品的温度、体积和比表面积都对颗粒质量释放率有显著影响，其中油品温度的影响最大。所得到的回归模型具有统计学意义(P<0.001)，R2值多数大于0.85.因此，根据我们的研究结果，建议使用葵花油、大豆油和玉米油，这些油的烟点较高，排放率较低，烹饪时使用较小的平底锅。
Particulate matter emitted by heated cooking oil is hazardous to human health. To develop effective mitigation strategies, it is critical to know the amount of the emitted particles. The purpose of this research is to estimate the temperature-dependent particle mass emission rates of edible oils and to develop models for source strength based on the multiple linear regression method. First, this study examined seven commonly used oils by heating experiments. The emission rates of PM2.5 and PM10 were measured, and the effects of parameters such as oil volume and surface area on the emission rates were also analysed. Following that, the starting smoke points (Ts') and aggravating smoke points (Tss') of tested oils were determined. The results showed that oils with lower smoke points had greater emission rates. Notably, the experiments performed observed that peanut, rice, rapeseed and olive oil generated PM2.5 much faster at 240 °C (2.22, 1.50, 0.82 and 0.80 mg/s, respectively, at the highest emission conditions) than that of sunflower, soybean, and corn oil (0.15, 0.12 and 0.11 mg/s, respectively). The temperature, volume, and surface area of oils all had a significant impact on the particle mass emission rate, with oil temperature being the most influential. The regression models obtained were statistically significant (P < 0.001), with the majority of R2values greater than 0.85. Using sunflower, soybean and corn oils, which have higher smoke points and lower emission rates, and smaller pans for cooking is therefore recommended based on our research findings.