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淄博市城郊臭氧污染特征及影响因素分析
摘要点击 2327  全文点击 759  投稿时间:2021-05-03  修订日期:2021-06-21
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中文关键词  挥发性有机物(VOCs)  臭氧(O3)  污染特征  影响因素  相关性分析
英文关键词  volatile organic compounds (VOCs)  ozone (O3)  pollution characteristics  influencing factors  correlation analysis
作者单位E-mail
王雨燕 南开大学环境科学与工程学院, 天津 300350 15364519618@163.com 
杨文 中国环境科学研究院, 北京 100012  
王秀艳 南开大学环境科学与工程学院, 天津 300350 wangsy@nankai.edu.cn 
王帅 南开大学环境科学与工程学院, 天津 300350  
白瑾丰 南开大学环境科学与工程学院, 天津 300350  
程颖 南开大学环境科学与工程学院, 天津 300350  
中文摘要
      本文基于淄博市2019年18个自动监测站连续1 a的O3与前体物(NOx、VOCs和CO),及常规气象监测数据(气温、相对湿度、风速和能见度),选取城区和郊区代表性站点,研究了O3与前体物的污染特征以及O3生成的影响因素.结果表明,淄博市2019年O3-8h浓度超标率为25.8%,超标天多出现在5~9月;城区NOx浓度高于郊区,而O3和VOCs浓度较低;各污染物的小时变化率具有明显的季节特征,秋冬季节O3上升和前体物下降时间均较春夏季节晚1 h左右,且O3生成累积的高峰时段缩短,城区O3浓度的整体上升速率高于郊区;对O3及各影响因素的相关性分析、偏相关分析及线性回归分析得到,O3与前体物和相对湿度呈负相关,与能见度、气温和风速呈正相关,各因素间存在相互影响;城区站点O3生成的主控因子有相对湿度、NOx、能见度和VOCs等,郊区站点为相对湿度、气温、NOx和VOCs等.
英文摘要
      In this study, we obtained monitoring data of O3 and its precursors (NOx, VOCs, and CO), as well as meteorological data (temperature, relative humidity, wind speed, and visibility), in 2019 to analyze the characteristics of O3 pollution and the influencing factors in urban and suburban areas. The results showed that the O3 episodes accounted for 25.8% of the whole observation period, mostly occurring from May to September. The concentration of NOx in urban areas was higher than that in suburban areas, whereas the concentrations of O3 and VOCs were lower. The hourly rate of variation in each pollutant had obvious seasonal characteristics; for example, the time of O3 rise and precursor decline in autumn and winter was approximately 1 h later than that in summer, and the peak period of O3 generation and accumulation was shortened. The increase rate in O3 in urban areas was higher than that in suburban areas. Correlation analysis and partial correlation analysis were used to study the relationship between O3 and its influencing factors. The results showed that O3 was negatively correlated with precursors and relative humidity and positively correlated with visibility, temperature, and wind speed, and these factors interacted with each other. According to the multivariate linear regression analysis, the main controlling factors in urban areas were relative humidity, NOx, visibility, and VOCs, whereas in suburban areas they were relative humidity, temperature, NOx, and VOCs.

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