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Environ Sci Pollut Res Int

Title:		Comparison of PM(2.5) emission rates and source profiles for traditional Chinese cooking styles
Author(s):		Lin P; He W; Nie L; Schauer JJ; Wang Y; Yang S; Zhang Y;
Address:		"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China. Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China. Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, WI, 53706, USA. Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, 53718, USA. College of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, China. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China. yxzhang@ucas.ac.cn. CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen, 361021, China. yxzhang@ucas.ac.cn"
Journal Title:		Environ Sci Pollut Res Int
Year:		2019
Volume:		20190522
Issue:		21
Page Number:		21239 - 21252
DOI:		10.1007/s11356-019-05193-z
ISSN/ISBN:		1614-7499 (Electronic) 0944-1344 (Linking)
Abstract:		"The number of restaurants is increasing rapidly in recent years, especially in urban cities with dense populations. Particulate matter emitted from commercial and residential cooking is a significant contributor to both indoor and outdoor aerosols. The PM(2.5) emission rates and source profiles are impacted by many factors (cooking method, food type, oil type, fuel type, additives, cooking styles, cooking temperature, source surface area, pan, and ventilation) discussed in previous studies. To determine which cooking activities are most influential on PM(2.5) emissions and work towards cleaner cooking, an experiment design based on multi-factor and level orthogonal tests was conducted in a laboratory that is specifically designed to resemble a professional restaurant kitchen. In this cooking test, four main parameters (the proportion of meat in ingredients, flavor, cooking technique, oil type) were chosen and five levels for each parameter were selected to build up 25 experimental dishes. Concentrations of PM(2.5) emission rates, organic carbon/elemental carbon (OC/EC), water-soluble ions, elements, and main organic species (PAHs, n-alkanes, alkanoic acids, fatty acids, dicarboxylic acids, polysaccharides, and sterols) were investigated across 25 cooking tests. The statistical significance of the data was analyzed by analysis of variance (ANOVA) with ranges calculated to determine the influence orders of the 4 parameters. The PM(2.5) emission rates of 25 experimental dishes ranged from 0.1 to 9.2 g/kg of ingredients. OC, EC, water-soluble ions (WSI), and elements accounted for 10.49-94.85%, 0-1.74%, 10.09-40.03%, and 0.04-3.93% of the total PM(2.5), respectively. Fatty acids, dicarboxylic acids, n-alkanes, alkanoic acids, and sterols were the most abundant organic species and accounted for 2.32-93.04%, 0.84-60.36%, 0-45.05%, and 0-25.42% of total PM(2.5), respectively. There was no significant difference between the 4 parameters on PM(2.5) emission rates, while a significant difference was found in WSI, elements, n-alkanes, and dicarboxylic acids according to ANOVA. Cooking technique was found to be the most influential factor for PM(2.5) source profiles, followed by the proportion of meat in ingredients and oil type which resulted in significant difference of 183.19, 185.14, and 115.08 g/kg of total PM(2.5) for dicarboxylic acids, n-alkanes, and WSI, respectively. Strong correlations were found among PM(2.5) and OC (r = 0.854), OC and sterols (r = 0.919), PAHs and n-alkanes (r = 0.850), alkanoic acids and fatty acids (r = 0.877), and many other species of PM(2.5)"
Keywords:		Aerosols/analysis Air Pollutants/*analysis Alkanes/analysis Carbon/analysis China Cooking/*methods *Environmental Monitoring Particulate Matter/*analysis Polycyclic Aromatic Hydrocarbons/analysis Restaurants Chinese cooking Influential factors PM2.5 emiss;
Notes:		"MedlineLin, Pengchuan He, Wanqing Nie, Lei Schauer, James J Wang, Yuqin Yang, Shujian Zhang, Yuanxun eng 201409017/Public Welfare Project of Ministry of Environmental Protection of China/ Germany 2019/05/23 Environ Sci Pollut Res Int. 2019 Jul; 26(21):21239-21252. doi: 10.1007/s11356-019-05193-z. Epub 2019 May 22"