Please wait a minute...

Frontiers of Environmental Science & Engineering

Front. Environ. Sci. Eng.    2016, Vol. 10 Issue (3) : 559-568     https://doi.org/10.1007/s11783-016-0829-y
RESEARCH ARTICLE |
Chemical characteristics of fine particulate matter emitted from commercial cooking
Bing PEI1,2,Hongyang CUI3,Huan LIU4,*(),Naiqiang YAN1,*()
1. School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200040, China
2. Shanghai Environmental Monitoring Center, Shanghai 200030, China
3. Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
4. School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), Tsinghua University, Beijing 100084, China
Download: PDF(485 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The chemical characteristics of fine particulate matter (PM2.5) emitted from commercial cooking were explored in this study. Three typical commercial restaurants in Shanghai, i.e., a Shanghai-style one (SHS), a Sichuan-style one (SCS) and an Italian-style one (ITS), were selected to conduct PM2.5 sampling. Particulate organic matter (POM) was found to be the predominant contributor to cooking-related PM2.5 mass in all the tested restaurants, with a proportion of 69.1% to 77.1%. Specifically, 80 trace organic compounds were identified and quantified by gas chromatography/mass spectrometry (GC/MS), which accounted for 3.8%–6.5% of the total PM2.5 mass. Among the quantified organic compounds, unsaturated fatty acids had the highest concentration, followed by saturated fatty acids. Comparatively, the impacts of other kinds of organic compounds were much smaller. Oleic acid was the most abundant single species in both SCS and ITS. However, in the case of SHS, linoleic acid was the richest one. ITS produced a much larger mass fraction of most organic species in POM than the two Chinese cooking styles except for monosaccharide anhydrides and sterols. The results of this study could be utilized to explore the contribution of cooking emissions to PM2.5 pollution and to develop the emission inventory of PM2.5 from cooking, which could then help the policy-makers design efficient treatment measures and control strategies on cooking emissions in the future.

Keywords commercial cooking      PM2.5      chemical characteristics      organic matter     
Corresponding Authors: Huan LIU,Naiqiang YAN   
Online First Date: 25 January 2016    Issue Date: 05 April 2016
 Cite this article:   
Bing PEI,Hongyang CUI,Huan LIU, et al. Chemical characteristics of fine particulate matter emitted from commercial cooking[J]. Front. Environ. Sci. Eng., 2016, 10(3): 559-568.
 URL:  
http://journal.hep.com.cn/fese/EN/10.1007/s11783-016-0829-y
http://journal.hep.com.cn/fese/EN/Y2016/V10/I3/559
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Bing PEI
Hongyang CUI
Huan LIU
Naiqiang YAN
restaurant volume/(m3·h-1) temperature/℃ moisture content/% ambient air temperature/℃
SHS ~16000 32 2.2 30
SCS ~18000 33 2.5 30
ITS ~12000 30 2.6 28
Tab.1  Major flue gas parameters of the three tested restaurants
restaurant flue gas ambient air
(lunchtime periods) (suppertime periods)
SHS 0.649±0.007 0.693±0.227 0.048
SCS 0.394±0.012 0.471±0.314 0.069
ITS 0.325±0.016 0.502±0.142 0.056
Tab.2  PM2.5 concentrations in flue gases and ambient air (mg·m-3)
Fig.1  Mass fractions of different chemical components in PM2.5 emitted from three tested restaurants
Fig.2  Proportions of six major compounds in quantified POM emitted from three tested restaurants
species category species SHS SCS ITS
n-alkanes n-hexadecane nd 13.5 38.5
n-heptadecane 10.6 18.7 60.2
n-octadecane 26.9 8.0 22.0
n-nonadecane 30.4 5.8 11.6
n-eicosane 68.1 34.6 115.7
n-heneicosane 117.1 75.2 164.4
n-docosane 123.1 111.1 301.1
n-tricosane 111.4 138.6 358.2
n-tetracosane 77.7 106.3 239.6
n-pentacosane 41.9 63.8 102.4
n-hexacosane 16.9 29.5 87.9
n-heptacosane 29.9 34.9 118.2
n-octacosane 10.7 9.2 28.8
n-nonacosane 62.4 80.3 297.9
n-triacontane 16.1 10.4 40.5
n-hentriacontane 97.9 62.0 293.2
n-dotriacontane 8.9 7.9 30.0
n-tritriacontane 40.1 22.6 89.4
total 890.2 818.9 2361.0
polycyclic aromatic hydrocarbons naphthalene 0.6 2.0 3.4
acenaphthylene 0.8 1.6 10.6
acenaphthene 0.9 0.9 5.2
fluorene 3.2 2.7 14.0
phenanthrene 8.9 7.0 23.0
anthracene 0.9 2.7 13.8
fluoranthene 13.2 9.0 42.4
pyrene 11.8 11.6 49.4
retene 8.1 3.2 3.7
benzo[ghi]fluoranthene 5.7 3.9 10.8
cyclopenta[cd]pyrene 5.2 0.9 5.5
benz[a]anthracene 1.9 10.2 52.7
chrysene 6.7 13.5 54.2
benzo[b+ k]fluoranthene 5.4 35.2 146.0
benzo[a]fluoranthene nd 0.5 nd
benzo[e]pyrene 7.2 16.6 65.0
benzo[a]pyrene 3.0 10.8 73.0
perylene nd 8.5 54.0
anthanthracene 1.7 5.8 12.8
benzo[123-cd]pyrene 3.8 25.8 144.4
benzo[ghi]perylene 16.1 31.1 141.3
dibenz[ah]anthracene nd 4.7 19.6
coronene 15.6 27.0 116.8
total 120.6 235.2 1061.4
saturated acids octanoic acid 73.7 48.8 109.4
nonaoic acid 153.6 118.7 246.0
decanoic acid 49.4 44.9 81.9
undecanoic acid 21.4 8.0 19.2
dodecanoic acid 113.1 89.8 236.5
tridecanoic acid 32.8 13.8 40.4
tetradecanoic acid 374.2 232.9 989.3
pentadecanoic acid 221.5 126.6 541.7
hexadecanoic acid 5548.6 5226.4 22756.1
heptadecanoic acid 252.4 119.6 550.2
octadecanoic acid 4398.6 2870.7 12672.0
nonadecanoic acid 27.4 15.8 75.0
eicosanoic acid 524.6 178.0 757.3
heneicosanoic acid 51.2 22.0 108.1
docosanoic acid 543.5 238.2 1013.6
tricosanoic acid 70.9 31.5 148.0
tetracosanoic acid 217.3 204.8 859.9
pentacosanoic acid 22.1 9.4 49.5
hexacosanoic acid 27.0 37.0 109.6
heptacosanoic acid 2.4 1.9 7.5
octacosanoic acid 14.6 9.6 36.8
nonacosanoic acid 1.6 nd 5.9
triacontanoic acid 13.5 9.6 32.8
hetriacontanoic acid nd nd nd
dotracontanoic acid 4.4 nd nd
total 12759.8 9657.9 41446.6
unsaturated acids linoleic acid 17793.2 9498.5 22839.3
oleic acid 15625.5 9919.5 23847.5
total 33418.7 19418.0 46686.8
dicarboxylic acids glutaric acid 13.5 3.3 28.3
adipic acid 10.4 3.9 27.5
pimeric acid 17.2 4.9 38.0
suberic acid 63.5 18.7 112.4
azelaic acid 128.2 43.2 189.5
total 232.8 74.1 395.8
monosaccharide anhydrides galactosan 4.0 96.5 60.4
mannosan 19.3 131.3 39.8
levoglucosan 429.9 272.5 85.1
total 453.2 500.4 185.4
sterols cholesterol 325.8 130.2 330.9
campesterol 608.3 239.2 493.4
stigmasterol 637.3 250.0 529.3
b-sitosterol 1302.7 511.3 1045.2
total 2874.0 1130.6 2398.7
Tab.3  Average mass fractions of trace organic compounds in POM from the three tested restaurants (ng?mg-1)
Fig.3  Mass fraction of n-alkanes in POM emitted from the three tested restaurants
Fig.4  Mass fractions of saturated fatty acids in POM emitted from the three tested restaurants
1 Lin L, He X C, Wu J P, Yu P G, Guo T T. Research of Shanghai cooking fume pollution. Environmental Science & Technology, 2014, 37(120): 546–549 (In Chinese)
2 Schauer J J, Rogge W F, Hildemann L M, Mazurek M A, Cass G R, Simoneit B R. Source apportionment of airborne particulate matter using organic compounds as tracers. Atmospheric Environment, 1996, 30(22): 3837–3855
https://doi.org/10.1016/1352-2310(96)00085-4
3 Zheng M, Cass G R, Schauer J J, Edgerton E S. Source apportionment of PM2.5 in the Southeastern United States using solvent-extractable organic compounds as tracers. Environmental Science & Technology, 2002, 36(11): 2361–2371
https://doi.org/10.1021/es011275x pmid: 12075791
4 Robinson A L, Subramanian R, Donahue N M, Bernardo-Bricker A, Rogge W F. Source apportionment of molecular markers and organic aerosol. 3. Food cooking emissions. Environmental Science & Technology, 2006, 40(24): 7820–7827
https://doi.org/10.1021/es060781p pmid: 17256533
5 Abdullahi K L, Delgado-Saborit J M, Harrison R M. Emissions and indoor concentrations of particulate matter and its specific chemical components from cooking: A review. Atmospheric Environment, 2013, 71: 260–294
https://doi.org/10.1016/j.atmosenv.2013.01.061
6 Abbey D E, Ostro B E, Petersen F, Burchette R J. Chronic respiratory symptoms associated with estimated long-term ambient concentrations of fine particulates less than 2.5 microns in aerodynamic diameter (PM2.5) and other air pollutants. Journal of Exposure Analysis and Environmental Epidemiology, 1995, 5(2): 137–159
pmid: 7492903
7 Romieu I, Meneses F, Ruiz S, Sienra J J, Huerta J, White M C, Etzel R A. Effects of air pollution on the respiratory health of asthmatic children living in Mexico City. American Journal of Respiratory and Critical Care Medicine, 1996, 154(2): 300–307
https://doi.org/10.1164/ajrccm.154.2.8756798 pmid: 8756798
8 Lighty J S, Veranth J M, Sarofim A F. Combustion aerosols: factors governing their size and composition and implications to human health. Journal of the Air & Waste Management Association, 2000, 50(9): 1565–1622
https://doi.org/10.1080/10473289.2000.10464197 pmid: 11055157
9 Song Y, Zhang Y H, Xie S D, Zeng L M, Zheng M, Salmon L G, Shao M, Slanina S. Source apportionment of PM2.5 in Beijing by positive matrix factorization. Atmospheric Environment, 2006, 40(8): 1526–1537
https://doi.org/10.1016/j.atmosenv.2005.10.039
10 Shu J, Dearing J A, Morse A P, Yu L, Yuan N. Determining the sources of atmospheric particles in Shanghai, China, from magnetic and geochemical properties. Atmospheric Environment, 2001, 35(15): 2615–2625
https://doi.org/10.1016/S1352-2310(00)00454-4
11 Zhang Y, Wang X, Chen H, Yang X, Chen J, Allen J O. Source apportionment of lead-containing aerosol particles in Shanghai using single particle mass spectrometry. Chemosphere, 2009, 74(4): 501–507
https://doi.org/10.1016/j.chemosphere.2008.10.004 pmid: 19027137
12 Schauer J J, Kleeman M J, Cass G R, Simoneit B R. Measurement of emissions from air pollution sources. 4. C1–C27 organic compounds from cooking with seed oils. Environmental Science & Technology, 2002, 36(4): 567–575
https://doi.org/10.1021/es002053m pmid: 11883419
13 Rogge W F, Hildemann L M, Mazurek M A, Cass G R, Simoneit B R. Sources of fine organic aerosol. 1. Charbroilers and meat cooking operations. Environmental Science & Technology, 1991, 25(6): 1112–1125
https://doi.org/10.1021/es00018a015
14 Schauer J J, Kleeman M J, Cass G R, Simoneit B R. Measurement of emissions from air pollution sources. 1. C1 through C29 organic compounds from meat charbroiling. Environmental Science & Technology, 1999, 33(10): 1566–1577
https://doi.org/10.1021/es980076j
15 McDonald J D, Zielinska B, Fujita E M, Sagebiel J C, Chow J C, Watson J G. Emissions from charbroiling and grilling of chicken and beef. Journal of the Air & Waste Management Association, 2003, 53(2): 185–194
https://doi.org/10.1080/10473289.2003.10466141 pmid: 12617292
16 See S W, Balasubramanian R. Chemical characteristics of fine particles emitted from different gas cooking methods. Atmospheric Environment, 2008, 42(39): 8852–8862
https://doi.org/10.1016/j.atmosenv.2008.09.011
17 He L Y, Hu M, Huang X F, Yu B D, Zhang Y H, Liu D Q. Measurement of emissions of fine particulate organic matter from Chinese cooking. Atmospheric Environment, 2004, 38(38): 6557–6564
https://doi.org/10.1016/j.atmosenv.2004.08.034
18 Zhao Y, Hu M, Slanina S, Zhang Y. Chemical compositions of fine particulate organic matter emitted from Chinese cooking. Environmental Science & Technology, 2007, 41(1): 99–105
https://doi.org/10.1021/es0614518 pmid: 17265933
19 Zhao Y, Hu M, Slanina S, Zhang Y. The molecular distribution of fine particulate organic matter emitted from Western-style fast food cooking. Atmospheric Environment, 2007, 41(37): 8163–8171
https://doi.org/10.1016/j.atmosenv.2007.06.029
20 China National Environmental Monitoring Centre. Guidelines for Monitoring Methods of Ambient Air Particulate Matter Source Apportionment.Beijing: China National Environmental Monitoring Centre, 2014 (in Chinese).
21 Chow J C, Watson J G, Chen L W A, Chang M C, Robinson N F, Trimble D, Kohl S. The IMPROVE_A temperature protocol for thermal/optical carbon analysis: maintaining consistency with a long-term database. Journal of the Air & Waste Management Association, 2007, 57(9): 1014–1023
https://doi.org/10.3155/1047-3289.57.9.1014 pmid: 17912920
22 Gu Z, Feng J, Han W, Wu M, Fu J, Sheng G. Characteristics of organic matter in PM2.5 from an e-waste dismantling area in Taizhou, China. Chemosphere, 2010, 80(7): 800–806
https://doi.org/10.1016/j.chemosphere.2010.04.078 pmid: 20510434
23 Mattson F H, Lutton E S. The specific distribution of fatty acids in the glycerides of animal and vegetable fats. The Journal of Biological Chemistry, 1958, 233(4): 868–871
pmid: 13587507
24 Simoneit B R, Mazurek M A. Organic matter of the troposphere—II. Natural background of biogenic lipid matter in aerosols over the rural western United States. Atmospheric Environment, 1982, 16(9): 2139–2159
https://doi.org/10.1016/0004-6981(82)90284-0
25 Simoneit B R. Biomass burning—A review of organic tracers for smoke from incomplete combustion. Applied Geochemistry, 200217(3): 129–162
https://doi.org/10.1016/S0883-2927(01)00061-0
26 van Drooge B L, Ballesta P P. Seasonal and daily source apportionment of polycyclic aromatic hydrocarbon concentrations in PM10 in a semirural European area. Environmental Science & Technology, 2009, 43(19): 7310–7316
https://doi.org/10.1021/es901381a pmid: 19848139
27 Gao B, Guo H, Wang X M, Zhao X Y, Ling Z H, Zhang Z, Liu T Y. Polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China: spatiotemporal patterns and emission sources. Journal of Hazardous Materials, 2012, 239–240: 78–87
https://doi.org/10.1016/j.jhazmat.2012.07.068 pmid: 23021315
Related articles from Frontiers Journals
[1] Litao Wang, Joshua S. Fu, Wei Wei, Zhe Wei, Chenchen Meng, Simeng Ma, Jiandong Wang. How aerosol direct effects influence the source contributions to PM2.5 concentrations over Southern Hebei, China in severe winter haze episodes[J]. Front. Environ. Sci. Eng., 2018, 12(3): 13-.
[2] Wei WEN,Shuiyuan CHENG,Lei LIU,Gang WANG,Xiaoqi WANG. Source apportionment of PM2.5 in Tangshan, China—Hybrid approaches for primary and secondary species apportionment[J]. Front. Environ. Sci. Eng., 2016, 10(5): 6-.
[3] Jianwu SHI,Xiang DING,Yue ZHOU,Ran YOU,Lu HUANG,Jiming HAO,Feng XIANG,Jian YANG,Ze SHI,Xinyu HAN,Ping NING. Characteristics of chemical components in PM2.5 at a plateau city, South-west China[J]. Front. Environ. Sci. Eng., 2016, 10(5): 4-.
[4] Ningning Zhang, Mazhan Zhuang, Jie Tian, Pengshan Tian, Jieru Zhang, Qiyuan Wang, Yaqing Zhou, Rujin Huang, Chongshu Zhu, Xuemin Zhang, Junji Cao. Development of source profiles and their application in source apportionment of PM2.5 in Xiamen, China[J]. Front. Environ. Sci. Eng., 2016, 10(5): 17-.
[5] Yuan ZHANG,Chunming HU,Tao YU. Photodegradation of chromophoric dissolved organic matters in the water of Lake Dianchi, China[J]. Front. Environ. Sci. Eng., 2015, 9(4): 575-582.
[6] Xiaojiang FAN,Yi TAO,Dequan WEI,Xihui ZHANG,Ying LEI,Hiroshi NOGUCHI. Removal of organic matter and disinfection by-products precursors in a hybrid process combining ozonation with ceramic membrane ultrafiltration[J]. Front. Environ. Sci. Eng., 2015, 9(1): 112-120.
[7] Yuan ZHANG,Yan ZHANG,Tao YU. Quantitative characterization of Cu binding potential of dissolved organic matter (DOM) in sediment from Taihu Lake using multiple techniques[J]. Front.Environ.Sci.Eng., 2014, 8(5): 666-674.
[8] Yan ZHANG,Yuan ZHANG,Tao YU. Characterization of interaction between different adsorbents and copper by simulation experiments using sediment-extracted organic matter from Taihu Lake, China[J]. Front.Environ.Sci.Eng., 2014, 8(4): 510-518.
[9] Qing ZHOU, Mengqiao WANG, Aimin LI, Chendong SHUANG, Mancheng ZHANG, Xiaohan LIU, Liuyan WU. Preparation of a novel anion exchange group modified hyper-crosslinked resin for the effective adsorption of both tetracycline and humic acid[J]. Front Envir Sci Eng, 2013, 7(3): 412-419.
[10] Can DONG, Lingxiao YANG, Chao YAN, Qi YUAN, Yangchun YU, Wenxing WANG. Particle size distributions, PM2.5 concentrations and water-soluble inorganic ions in different public indoor environments: a case study in Jinan, China[J]. Front Envir Sci Eng, 2013, 7(1): 55-65.
[11] Shuang XUE, Qingliang ZHAO, Liangliang WEI, Xiujuan HUI, Xiping MA, Yingzi LIN. Fluorescence spectroscopic studies of the effect of granular activated carbon adsorption on structural properties of dissolved organic matter fractions[J]. Front Envir Sci Eng, 2012, 6(6): 784-796.
[12] Jing ZHANG, Shigong WANG, Can WANG, Hongying HU. Chemical identification and genotoxicity analysis of petrochemical industrial wastewater[J]. Front Envir Sci Eng, 2012, 6(3): 350-359.
[13] Jin GUO, Feng SHENG, Jianhua GUO, Xiong YANG, Mintao MA, Yongzhen PENG. Characterization of the dissolved organic matter in sewage effluent of sequence batch reactor: the impact of carbon source[J]. Front Envir Sci Eng, 2012, 6(2): 280-287.
[14] Fang FANG, Yan YANG, Jinsong GUO, Hong ZHOU, Chuan FU, Zhe LI. Three-dimensional fluorescence spectral characterization of soil dissolved organic matters in the fluctuating water-level zone of Kai County, Three Gorges Reservoir[J]. Front Envir Sci Eng Chin, 2011, 5(3): 426-434.
[15] Liu YANG, Ye WU, Jerry M. DAVIS, Jiming HAO. Estimating the effects of meteorology on PM2.5 reduction during the 2008 Summer Olympic Games in Beijing, China[J]. Front Envir Sci Eng Chin, 2011, 5(3): 331-341.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed