唐山市PM2.5和O3的演变特征及其对大气复合污染的协同影响 |
摘要点击 2680 全文点击 690 投稿时间:2023-08-15 修订日期:2023-11-16 |
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中文关键词 PM2.5 O3 协同作用 复合污染 气团传输 |
英文关键词 PM2.5 O3 synergistic effect compound pollution air mass transport |
作者 | 单位 | E-mail | 韩力慧 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | hlh@bjut.edu.cn | 兰童 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | | 程水源 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | | 王迎澳 | 北京工业大学环境与生命学部, 北京 100124 | | 齐超楠 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | | 田健 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | | 王海燕 | 北京工业大学环境与生命学部, 北京 100124 区域大气复合污染防治北京市重点实验室, 北京 100124 | | 韩登越 | 北京工业大学环境与生命学部, 北京 100124 | | 王慎澳 | 北京工业大学环境与生命学部, 北京 100124 | |
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中文摘要 |
通过采集唐山市2015~2021年7年间大气污染物PM2.5、 O3、 SO2、 NO2和CO浓度,以及气象要素温度(T)、相对湿度(RH)、风速等相关数据,结合相关性分析和后向轨迹聚类分析技术,分析研究了唐山市近7年间PM2.5和O3不同时段的变化特征,及其影响因素,探讨了气团传输对PM2.5和O3污染的贡献,揭示了PM2.5和O3对大气复合污染的协同影响机制.结果表明,唐山市2015~2021年间PM2.5浓度呈逐年下降的趋势,而O3浓度则呈现出单峰态变化趋势,峰值出现在2017年. PM2.5和O3浓度均呈现出明显的季节变化,其中PM2.5表现为冬季最高夏季最低的特征,而O3则表现为夏季最高而冬季最低的特征.此外,PM2.5的日变化呈双峰态分布,峰值分别发生在工作日早高峰和晚高峰期间. O3日变化则呈单峰态分布,峰值出现在下午紫外线照射较强时段. PM2.5主要受SO2、 NO2和CO的正向影响,而O3则主要受太阳辐射强度和温度的正向影响.在不同污染背景下,PM2.5和O3会受到来自不同方向气团传输的影响. PM2.5和O3对大气复合污染的协同作用在诸多因素的共同影响下,呈现出冬季明显的负向影响,而春、夏和秋季则明显的正向影响.在不同污染背景下,当PM2.5浓度超过150 μg·m-3时,PM2.5和O3的协同作用则表现为明显的负向作用. |
英文摘要 |
The concentrations of atmospheric pollutants PM2.5, O3, SO2, NO2, and CO together with the meteorological factors of temperature (T), relative humidity (RH), wind speed, and other relevant data in Tangshan from 2015 to 2021 were collected to study the variation characteristics of PM2.5 and O3 at different periods in Tangshan City in the past seven years and their influencing factors, to discuss the contributions of air mass transport to PM2.5 and O3 pollution, and to reveal the synergistic influence mechanism of PM2.5 and O3 on atmospheric compound pollution by using correlation analysis and backward trajectory cluster analysis techniques. The results showed that PM2.5 concentrations in Tangshan decreased year by year from 2015 to 2021, whereas O3 concentration showed a unimodal trend, with the peak appearing in 2017. Both PM2.5 and O3 concentrations showed obvious seasonal variation trends; PM2.5 was characterized by the highest concentration in winter and the lowest concentration in summer, whereas O3 was characterized by the highest concentration in summer and the lowest concentration in winter. In addition, the diurnal variation in PM2.5 showed a bimodal distribution, with the peak occurring during the morning and evening on weekdays, and O3 showed a unimodal distribution, with the peak value appearing during the period with strong ultraviolet radiation in the afternoon. PM2.5 had a significant positive correlation with SO2, NO2, and CO, whereas O3 had a significant positive correlation with radiation and temperature. Under the different pollution conditions, PM2.5 and O3 were affected by air mass transports from different directions. Being impacted by various factors, the synergistic effect of PM2.5 and O3 on atmospheric compound pollution showed an obvious negative effect in winter, whereas there was an obvious positive effect in spring, summer, and autumn. Under the backgrounds of different pollutions, when the concentration of PM2.5 exceeded 150 μg·m-3, the synergistic effect of PM2.5 and O3 showed an obvious negative effect. |
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