| 餐饮行业细颗粒物(PM2.5)排放测算方法:以上海市为例 |
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| 引用本文： | 王红丽,景盛翱,楼晟荣,陶士康,乔利平,李莉,黄成,林立,陈长虹.餐饮行业细颗粒物(PM2.5)排放测算方法:以上海市为例[J].环境科学,2018,39(5):1971-1977. |
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| 作者姓名： | 王红丽 景盛翱 楼晟荣 陶士康 乔利平 李莉 黄成 林立 陈长虹 |
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| 作者单位： | 上海市环境科学研究院国家环境保护城市大气复合污染成因与防治重点实验室 |
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| 基金项目： | 环境保护公益性行业科研专项（201409018）；上海市重大环保科研项目（2017-02）；上海市科委科技攻关项目（16DZ1204604） |
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| 摘 要： | 以上海市餐饮企业为例,研究了餐饮企业PM_(2.5)排放特征以及排放测算方法.按照单位灶头、单位时间、单位就餐人次这3种计算基准,获得了不同类型餐饮企业PM_(2.5)的排放因子,并在此基础上结合2014年上海市餐饮企业活动水平测算了PM_(2.5)的排放清单.结果表明,餐饮企业排放PM_(2.5)的浓度范围0.1~1.8 mg·m~(-3),甚至超过国家饮食业标准中关于油烟1mg·m~(-3)的排放限值;PM_(2.5)中OC质量贡献超过50%,OC/EC比值的变化范围为58.8~752.3,平均值为128.4,可作为餐饮排放的示踪特征.企业规模是影响餐饮企业PM_(2.5)排放因子的重要因素.按照灶头活动、餐饮作业时间以及就餐人次这3种方法计算得出的餐饮企业PM_(2.5)排放因子均表明,大型、中型企业明显高于小型和微型企业(食堂、快餐).基于上述3种排放因子,计算2014年上海PM_(2.5)排放量相对一致,表明本研究获得基于3种活动水平的排放因子比较可靠,未来可应用于其他城市餐饮企业排放清单的核算.
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| 关 键 词： | 细颗粒物(PM2.5) 排放测算方法 餐饮业 排放因子 上海 |
| 收稿时间： | 2017/8/28 0:00:00 |
| 修稿时间： | 2017/10/23 0:00:00 |
Estimation of Fine Particle (PM2.5) Emission Inventory from Cooking: Case Study for Shanghai |
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| WANG Hong-li,JING Sheng-ao,LOU Sheng-rong,TAO Shi-kang,QIAO Li-ping,LI Li,HUANG Cheng,LIN Li and CHEN Chang-hong.Estimation of Fine Particle (PM2.5) Emission Inventory from Cooking: Case Study for Shanghai[J].Chinese Journal of Environmental Science,2018,39(5):1971-1977. |
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| Authors: | WANG Hong-li JING Sheng-ao LOU Sheng-rong TAO Shi-kang QIAO Li-ping LI Li HUANG Cheng LIN Li and CHEN Chang-hong |
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| Institution: | State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China,State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China and State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China |
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| Abstract: | Cooking is one of important emission sources of fine particles (PM2.5). This study using the catering enterprises of Shanghai as an example, presents a method to estimate the PM2.5 emission inventory from cooking according to the number of stoves, cooking time, and number of customers. Based on in situ measurements, the concentrations of PM2.5 emissions ranged from 0.1 mg ·m-3 to 1.8 mg ·m-3, which exceeded the limit (1.0 mg ·m-3 for lampblack) in the national standard. Organic carbon dominated the PM2.5 emitted from cooking, accounting for more than 50%. Extremely high ratios of organic carbon to elemental carbon were observed, ranging from 58.8 to 752.3, which could be used as an indicator of cooking emissions. The emission factors of PM2.5 in the catering industry are closely related to the scale of the catering enterprises. The emission factors of large-and medium-sized enterprises are obviously higher than those of small and micro enterprises. The PM2.5 emissions of catering enterprises are mainly attributed to high emission loads of large enterprises and those for a large number of small and medium enterprises. The PM2.5 emission inventory of cooking in Shanghai was calculated according to the three emission factors above, and the results were very close. Therefore, the method for estimating the PM2.5 emission inventory for cooking presented in this study is helpful for other Chinese cities to calculate their PM2.5 emission inventory from cooking. |
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| Keywords: | PM2 5 emission calculation method catering industry emission factor Shanghai |
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