恶臭污染的测定方法与预测模型研究进展

doi:10.13745/j.esf.sf.2023.9.10

地学前缘 ›› 2024, Vol. 31 ›› Issue (2): 13-19.DOI: 10.13745/j.esf.sf.2023.9.10

• 场地土壤污染机制与风险管控 • 上一篇下一篇

恶臭污染的测定方法与预测模型研究进展

祝富杰¹(), 曲龙泽¹, 李平², 魏文侠³, 李培中³, 王立夫¹, 李本行¹, 王姣¹, 任更波¹, 吴志能¹, 马小东¹^,^*()

1.河北工业大学能源与环境工程学院, 天津 300401
2.河北师范大学化学与材料科学学院, 河北石家庄 050024
3.北京市科学技术研究院资源环境研究所, 北京 100089

收稿日期:2023-07-19 修回日期:2023-08-16 出版日期:2024-03-25 发布日期:2024-04-18
通讯作者: *马小东(1972—),男,博士,特聘教授,主要从事场地污染诊断与治理技术研究工作。E-mail: maxd@hebut.edu.cn
作者简介:祝富杰(1994—),男,博士,讲师,主要从事场地有机污染物环境行为研究工作。E-mail: zhu_fujie@163.com
基金资助:
国家重点研发计划重点专项课题“场地土壤污染成因与治理技术”(2020YFC1808603)

Odor measurement methods and prediction models: A review

ZHU Fujie¹(), QU Longze¹, LI Ping², WEI Wenxia³, LI Peizhong³, WANG Lifu¹, LI Benhang¹, WANG Jiao¹, REN Gengbo¹, WU Zhineng¹, MA Xiaodong¹^,^*()

1. School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China
2. College of Chemistry and Materials Science, Hebei Normal University, Shijiazhuang 050024, China
3. Institute of Resources and Environment, Beijing Academy of Science and Technology, Beijing 100089, China

Received:2023-07-19 Revised:2023-08-16 Online:2024-03-25 Published:2024-04-18

摘要/Abstract

摘要：

随着人们对环境问题的认识,恶臭污染已经成为一类典型的环境公害。我国的恶臭污染来源广泛,臭气浓度的测定成本昂贵,构建基于简易输入参数的臭气预测模型降低恶臭污染判定与控制的难度,是目前恶臭污染研究的热点问题。本研究从臭气定义的基本概念入手,总结对比了不同的臭气标准和测定方法。综述了目前常用的臭气预测模型,包括基于污染物浓度的多元线性回归法和不同的臭气浓度/强度预测模型,发现不同研究或者不同模型得到的结果差异较大。其中,为预测模型提供准确的嗅觉阈值是优化模型的关键。另外,作为一种环境问题,本研究也对臭气的大气扩散以及排放速率进行了综述研究,研究中使用不同的大气扩散模型对臭气的大气扩散过程进行预测。但不同模型需要的基础数据和知识背景不同,因此需要根据实际的应用场景选择合适的模型。排放速率作为大气扩散模型中的重要输入参数,可以通过不同的方法和装置进行测定,不同方法的测定结果存在差异,后续研究中需要依据更多的现场数据对预测结果进行验证。基于以上综述,本研究将为恶臭污染的识别和控制提供科学指导。

关键词: 恶臭污染, 臭气浓度/强度, 测定方法, 预测模型, 大气扩散模型

Abstract:

With the increasing awareness of environmental issues, odor pollution has been recognized as a typical environmental hazard. Odor pollution in China comes from a variety of sources and the cost of odor measurements is high. Currently a hot topic in odor pollution control is to develop odor prediction models based on easily measurable parameters to decrease the difficulty of odor measurement and control. This paper introduces the basic concept of odor pollution and summarizes and compares different odor classification standards and measurement methods. Research progress on odor prediction models is reviewed, including multiple linear regression commonly used to establish quantitative relationship between odor concentration/intensity and pollutant concentrations. There are obvious differences in the results obtained from different studies and models, and accurate odor threshold values are key to optimizing the models. Furthermore, as an environmental issue, atmospheric dispersion and emission rate of odor pollutants are discussed. Different atmospheric diffusion models have been used to predict odor diffusion in the atmosphere, however, different models require different basic data and knowledges, therefore it is important to choose an appropriate model based on the actual application scenario. Emission rate, as an important input parameter in atmospheric dispersion models, can also be measured using different methods and devices, but differences between the results are to be expected, and cross-validation is needed. This review provides scientific guidance for the identification and control of odor pollution.

Key words: odor pollution, odor concentration/intensity, determination method, prediction model, atmospheric diffusion model

中图分类号:

X512

祝富杰, 曲龙泽, 李平, 魏文侠, 李培中, 王立夫, 李本行, 王姣, 任更波, 吴志能, 马小东. 恶臭污染的测定方法与预测模型研究进展[J]. 地学前缘, 2024, 31(2): 13-19.

ZHU Fujie, QU Longze, LI Ping, WEI Wenxia, LI Peizhong, WANG Lifu, LI Benhang, WANG Jiao, REN Gengbo, WU Zhineng, MA Xiaodong. Odor measurement methods and prediction models: A review[J]. Earth Science Frontiers, 2024, 31(2): 13-19.

图/表 2

参考文献 34

[1]	HAYES E T, CURRAN T P, DODD V A. A dispersion modelling approach to determine the odour impact of intensive poultry production units in Ireland[J]. Bioresource Technology, 2006, 97(15): 1773-1779.
[2]	何品晶, 李健晨, 吕凡, 等. 生活垃圾填埋场恶臭污染的时空变化与膜阻隔效果[J]. 环境科学, 2022, 43(9):4506-4512.
[3]	LIU Y J, LIU Y T, LI H, et al. Health risk impacts analysis of fugitive aromatic compounds emissions from the working face of a municipal solid waste landfill in China[J]. Environment International, 2016, 97: 15-27.
[4]	国家环境保护局国家技术监督局. 恶臭污染物排放标准:GB 14554—1993[S]. 北京: 中国标准出版社, 1994.
[5]	李春芸. 关于臭气浓度和臭气强度两种表示法的探讨[C]// 第四届全国恶臭污染测试与控制技术研讨会论文集. 天津: 天津科学技术出版社, 淄博, 2012.
[6]	WU C D, LIU J M, ZHAO P, et al. Conversion of the chemical concentration of odorous mixtures into odour concentration and odour intensity: a comparison of methods[J]. Atmospheric Environment, 2016, 127: 283-292.
[7]	CHENG Z W, SUN Z T, ZHU S J, et al. The identification and health risk assessment of odor emissions from waste landfilling and composting[J]. Science of the Total Environment, 2019, 649: 1038-1044.
[8]	DINCER F, ODABASI M, MUEZZINOGLU A. Chemical characterization of odorous gases at a landfill site by gas chromatography-mass spectrometry[J]. Journal of Chromatography A, 2006, 1122(1/2): 222-229.
[9]	RINCÓN C A, DE GUARDIA A, COUVERT A, et al. Odor concentration (OC) prediction based on odor activity values (OAVs) during composting of solid wastes and digestates[J]. Atmospheric Environment, 2019, 201: 1-12.
[10]	许建光, 刘甜恬. 三点比较式臭袋法与动态稀释嗅觉计测定臭气浓度的比较[J]. 三峡环境与生态, 2010(3): 35-37.
[11]	LI C, AL-DALALI S, WANG Z P, et al. Investigation of volatile flavor compounds and characterization of aroma-active compounds of water-boiled salted duck using GC-MS-O, GC-IMS, and E-nose[J]. Food Chemistry, 2022, 386: 132728.
[12]	ZHU J C, NIU Y W, XIAO Z B. Characterization of the key aroma compounds in Laoshan green teas by application of odour activity value (OAV), gas chromatography-mass spectrometry-olfactometry (GC-MS-O) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-qMS)[J]. Food Chemistry, 2021, 339: 128136.
[13]	KIM K H, PARK S Y. A comparative analysis of malodor samples between direct (olfactometry) and indirect (instrumental) methods[J]. Atmospheric Environment, 2008, 42(20): 5061-5070.
[14]	COLÓN J, ALVAREZ C, VINOT M, et al. Characterization of odorous compounds and odor load in indoor air of modern complex MBT facilities[J]. Chemical Engineering Journal, 2017, 313: 1311-1319.
[15]	BLANES-VIDAL V, HANSEN M N, ADAMSEN A P S, et al. Characterization of odor released during handling of swine slurry: part I. Relationship between odorants and perceived odor concentrations[J]. Atmospheric Environment, 2009, 43(18): 2997-3005.
[16]	JIANG J, COFFEY P, TOOHEY B. Improvement of odor intensity measurement using dynamic olfactometry[J]. Journal of the Air and Waste Management Association, 2006, 56(5): 675-683.
[17]	DINCER F, MUEZZINOGLU A. Odor determination at wastewater collection systems: olfactometry versus H₂S analyses[J]. CLEAN-Soil, Air, Water, 2007, 35(6): 565-570.
[18]	FRANKE W, FRECHEN F B, GIEBEL S. H₂S, VOC, TOC, electronic noses and odour concentration: use and comparison of different parameters for emission measurement on air treatment systems[J]. Water Science and Technology, 2009, 59(9): 1721-1726.
[19]	GOSTELOW P, PARSONS S A, STUETZ R M. Odour measurements for sewage treatment works[J]. Water Research, 2001, 35(3): 579-597.
[20]	PALMIOTTO M, FATTORE E, PAIANO V, et al. Influence of a municipal solid waste landfill in the surrounding environment: toxicological risk and odor nuisance effects[J]. Environment International, 2014, 68: 16-24.
[21]	UJJAINI S, STEPHEN E H, PHILIP L. Dispersion of odour: a case study with a municipal solid waste landfill site in North London, United Kingdom[J]. Journal of Environmental Management, 2003, 68(2): 153-160.
[22]	HAYES J E, STEVENSON R J, STUETZ R M. The impact of malodour on communities: a review of assessment techniques[J]. Science of the Total Environment, 2014, 500/501: 395-407.
[23]	XU A K, CHANG H M, ZHAO Y, et al. Dispersion simulation of odorous compounds from waste collection vehicles: mobile point source simulation with ModOdor[J]. Science of the Total Environment, 2020, 711: 135109.
[24]	ZHANG Y, NING X Y, LI Y H, et al. Impact assessment of odor nuisance, health risk and variation originating from the landfill surface[J]. Waste Management, 2021, 126: 771-780.
[25]	LIU Y J, LU W J, LI D, et al. Estimation of volatile compounds emission rates from the working face of a large anaerobic landfill in China using a wind tunnel system[J]. Atmospheric Environment, 2015, 111: 213-221.
[26]	LU W J, DUAN Z H, LI D, et al. Characterization of odor emission on the working face of landfill and establishing of odorous compounds index[J]. Waste Management, 2015, 42: 74-81.
[27]	BRANCHER M, PIRINGER M, FRANCO D, et al. Assessing the inter-annual variability of separation distances around odour sources to protect the residents from odour annoyance[J]. Journal of Environmental Sciences, 2019, 79: 11-24.
[28]	DRESSER A L, HUIZER R D. CALPUFF and AERMOD model validation study in the near field: martins creek revisited[J]. Journal of the Air and Waste Management Association, 2011, 61(6): 647-659.
[29]	MANDURINO C, VESTRUCCI P. Using meteorological data to model pollutant dispersion in the atmosphere[J]. Environmental Modelling and Software, 2009, 24(2): 270-278.
[30]	CANEPA E. An overview about the study of downwash effects on dispersion of airborne pollutants[J]. Environmental Modelling and Software, 2004, 19(12): 1077-1087.
[31]	BOCKREIS A, STEINBERG I. Measurement of odour with focus on sampling techniques[J]. Waste Management, 2005, 25(9): 859-863.
[32]	HUDSON N, AYOKO G A. Odour sampling. 2. Comparison of physical and aerodynamic characteristics of sampling devices: a review[J]. Bioresource Technology, 2008, 99(10): 3993-4007.
[33]	KIM K H, KIM M Y, KIM J. Application of micrometeorological approaches to measure methane exchange in a dry paddy field in the western coast of Korea[J]. Chemosphere, 2005, 59(11): 1613-1624.
[34]	HUDSON N, AYOKO G, DUNLOP M, et al. Comparison of odour emission rates measured from various sources using two sampling devices[J]. Bioresource Technology, 2008, 100(1): 118-124.

臭气强度	嗅觉感觉
0	无臭
1	能稍微感觉到极弱臭味(检知阈值浓度),臭味似有似无
2	能辨别出何种气味(确认阈值浓度),例如可以勉强嗅到酸味和糊焦味
3	能明显嗅到臭味,例如医院里明显的来苏水气味
4	强烈臭气味,例如管理不善的厕所
5	强烈恶臭气味,使人感到恶心、想呕吐、头疼,进而引起气管炎的强烈气味

臭气强度	嗅觉感觉
0	无臭
1	能稍微感觉到极弱臭味(检知阈值浓度),臭味似有似无
2	能辨别出何种气味(确认阈值浓度),例如可以勉强嗅到酸味和糊焦味
3	能明显嗅到臭味,例如医院里明显的来苏水气味
4	强烈臭气味,例如管理不善的厕所
5	强烈恶臭气味,使人感到恶心、想呕吐、头疼,进而引起气管炎的强烈气味

分级
分级		氨		三甲胺	硫化氢	甲硫醇	甲硫醚	二甲二硫	二硫化碳	苯乙烯	臭气浓度
一级			1.0	0.05	0.03	0.004	0.03	0.03	2.00	3.00	10.00
二级	新扩改建		1.50	0.08	0.06	0.01	0.07	0.06	3.00	5.00	20.00
二级	现有		2.00	0.15	0.10	0.01	0.15	0.13	5.00	7.00	30.00
三级	新扩改建		4.00	0.45	0.32	0.02	0.55	0.42	8.00	14.00	60.00
三级	现有		5.00	0.80	0.60	0.04	1.10	0.71	10.00	19.00	70.00

分级
分级		氨		三甲胺	硫化氢	甲硫醇	甲硫醚	二甲二硫	二硫化碳	苯乙烯	臭气浓度
一级			1.0	0.05	0.03	0.004	0.03	0.03	2.00	3.00	10.00
二级	新扩改建		1.50	0.08	0.06	0.01	0.07	0.06	3.00	5.00	20.00
二级	现有		2.00	0.15	0.10	0.01	0.15	0.13	5.00	7.00	30.00
三级	新扩改建		4.00	0.45	0.32	0.02	0.55	0.42	8.00	14.00	60.00
三级	现有		5.00	0.80	0.60	0.04	1.10	0.71	10.00	19.00	70.00

恶臭污染的测定方法与预测模型研究进展

Odor measurement methods and prediction models: A review

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