title: Determination of time- and size-dependent fine particle emission with varied oil heating in an experimental kitchen.
abstract: Particulate matter (PM) from cooking has caused seriously indoor air pollutant and aroused risk to human health. It is urged to get deep knowledge of their spatial-temporal distribution of source emission characteristics, especially ultrafine particles (UFP<100nm) and accumulation mode particles (AMP 100-665nm). Four commercial cooking oils are auto dipped water to simulate cooking fume under heating to 265°C to investigate PM emission and decay features between 0.03 and 10μm size dimension by electrical low pressure impactor (ELPI) without ventilation. Rapeseed and sunflower produced high PM2.5around 6.1mg/m3, in comparison with those of soybean and corn (5.87 and 4.65mg/m3, respectively) at peak emission time between 340 and 460sec since heating oil, but with the same level of particle numbers 6-9×105/cm3. Mean values of PM1.0/PM2.5and PM2.5/PM10at peak emission time are around 0.51-0.66 and 0.23-0.29. After 15min naturally deposition, decay rates of PM1.0, PM2.5and PM10are 13.3%-29.8%, 20.1%-33.9% and 41.2%-54.7%, which manifest that PM1.0is quite hard to decay than larger particles, PM2.5and PM10. The majority of the particle emission locates at 43nm with the largest decay rate at 75%, and shifts to a larger size between 137 and 655nm after 15min decay. The decay rates of the particles are sensitive to the oil type.
authors.affiliation: State Key Laboratory of Multi-phase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: sdli@ipe.ac.cn.
authors.forename: Shuangde
authors.initials: S
authors.lastname: Li
authors.affiliation: Key Laboratory of Healthy & Intelligent Kitchen System Integration, Zhejiang, Ningbo, 315336, China.
authors.forename: Jiajia
authors.initials: J
authors.lastname: Gao
authors.affiliation: Key Laboratory of Healthy & Intelligent Kitchen System Integration, Zhejiang, Ningbo, 315336, China.
authors.forename: Yiqing
authors.initials: Y
authors.lastname: He
authors.affiliation: Key Laboratory of Healthy & Intelligent Kitchen System Integration, Zhejiang, Ningbo, 315336, China.
authors.forename: Liuxu
authors.initials: L
authors.lastname: Cao
authors.affiliation: Key Laboratory of Healthy & Intelligent Kitchen System Integration, Zhejiang, Ningbo, 315336, China.
authors.forename: Ang
authors.initials: A
authors.lastname: Li
authors.affiliation: State Key Laboratory of Multi-phase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Shengpeng
authors.initials: S
authors.lastname: Mo
authors.affiliation: State Key Laboratory of Multi-phase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: yfchen@ipe.ac.cn.
authors.forename: Yunfa
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Key Laboratory of Healthy & Intelligent Kitchen System Integration, Zhejiang, Ningbo, 315336, China.
authors.forename: Yaqun
authors.initials: Y
authors.lastname: Cao
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D016902:Air Pollution, Indoor / Q000032:analysis*; D003296:Cooking / Q000379:methods*; D004784:Environmental Monitoring; D009821:Oils; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D014691:Ventilation
chemical_list: D000393:Air Pollutants; D009821:Oils; D052638:Particulate Matter
keywords: Cooking fume; Emission character; Number concentration; Size distribution; Ultrafine particle