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广州市臭氧污染溯源:基于拉格朗日光化学轨迹模型的案例分析
摘要点击 3070  全文点击 930  投稿时间:2020-09-06  修订日期:2020-10-14
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中文关键词  臭氧  溯源  拉格朗日光化学轨迹模型  区域传输  挥发性有机物(VOCs)
英文关键词  ozone  trace source  Lagrangian photochemical trajectory model  regional transport  volatile organic compounds(VOCs)
作者单位E-mail
裴成磊 广东省广州生态环境监测中心站, 广州 510060
广东省环珠江口气候环境与空气质量变化野外科学观测研究站, 广州 510275 
peichenglei@163.com 
牟江山 山东大学环境研究院, 青岛 266237  
张英南 山东大学环境研究院, 青岛 266237  
申恒青 山东大学环境研究院, 青岛 266237 hqshen@sdu.edu.cn 
陈玉茹 壹点环境科技(广州)有限公司, 广州 510000  
黄杰生 壹点环境科技(广州)有限公司, 广州 510000  
丁浩然 壹点环境科技(广州)有限公司, 广州 510000  
李成柳 壹点环境科技(广州)有限公司, 广州 510000  
中文摘要
      分析了2018年10月初广州市一次为期6 d的臭氧污染事件,利用拉格朗日光化学轨迹模型对广州市的臭氧污染进行了溯源分析,量化了不同区域对臭氧污染的贡献,评估了重点排放区域不同行业和不同前体物减排对臭氧污染控制的效果.结果表明,本次污染事件期间,日最大8 h臭氧均值均超过160 μg·m-3,最高达271 μg·m-3,氮氧化物(NOx)和挥发性有机物(VOCs)的平均浓度为(77.7±42.8)μg·m-3和(71.9±56.2)μg·m-3.芳香烃和烯烃是主要的VOCs反应活性物种,分别贡献了38%和30%的·OH反应活性以及51%和16%的臭氧生成潜势.本次臭氧污染事件主要受3类气团输送影响,3类气团中的高排放区域分别为广东省外、广东省内和广州市本地,在高排放区域中臭氧生成均受VOCs控制.途经区域前体物减排的敏感性分析表明,减排VOCs对于降低臭氧浓度的效果优于减排NOx.在100%减排情况下控制高排放区域的交通源排放对广州市臭氧控制的效果(臭氧降低14.6%~21.0%)高于控制工业(8.4%~15.3%)、电厂(0.9%~6.2%)和民用源(2.3%~4.7%)的排放,但单独控制交通源在小于90%减排比例下对臭氧污染控制的效果并不显著(<10%).此外,珠江三角洲地区的生物源排放也对臭氧生成有重要贡献,在模型中关闭生物源排放后,广州市臭氧浓度降低6%~19%.本研究证实了拉格朗日光化学轨迹模型在区域臭氧污染溯源的应用效果,并为广州市臭氧污染的区域协同控制提供了对策建议.
英文摘要
      A six-day ozone pollution episode in Guangzhou in early October 2018 was analyzed with the application of a Lagrangian photochemical trajectory model to trace the sources of ozone, quantify the contributions of different regions, and evaluate the effects of emission reduction measures targeted at different emission sectors and different precursors on ozone pollution. The results showed that during the ozone pollution episode, the maximum daily 8 h ozone exceeded 160 μg·m-3 and the highest value reached 271 μg·m-3. The average concentrations of nitrogen oxides and volatile organic compounds (VOCs) were (77.7±42.8) μg·m-3 and (71.9±56.2) μg·m-3, respectively. Aromatics and alkenes were the dominant reactive VOCs, with contributions of 38% and 30% to·OH reactivity and 51% and 16% to ozone formation potential, respectively. The ozone pollution in Guangzhou during this episode was affected by three types of air masses, with the primary source regions of Guangzhou, Guangdong Province, and regions outside Guangdong Province. For all three air mass types, ozone production in these source region was controlled by VOCs. Sensitivity tests showed that, in the primary source regions, reducing the emissions of VOCs is more effective than reducing NOx in terms of reducing ozone concentrations. Under the condition of full emission reduction, regulating traffic emissions could substantially reduce ozone levels by 14.6%-21.0% in Guangzhou, which was a more significant reduction than regulating controlled industry (8.4%-15.3%), power plant (0.9%-6.2%) and residential (2.3%-4.7%) emissions. However, the traffic emission reduction is not as effective (induced ozone reduction<10%) when the emissions reduction ratio is lower than 90%. In addition, biogenic emissions in the Pearl River Delta also substantially contributed to the ozone levels under certain circumstances, as indicated by the ozone reduction up to 19% when biogenic emissions were shut off.

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