COVID-19期间区域大气高污染发生的非线性动力机制

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摘要以长株潭城市群3个城市（长沙、株洲和湘潭）疫情期间（2020年1月24日~2020年5月31日）大气PM_2.5和O₃小时平均浓度时间序列数据为研究对象，对污染物日变化规律、长期持续性、多重分形性及自组织演化动力学特性进行研究.以期阐释疫情期间高污染事件发生及演化的内在动力机制.首先，对3个城市PM_2.5和O₃质量浓度的日变化规律进行分析，发现O₃呈现出昼高夜低的单峰型，而PM_2.5日变化规律表现出昼低夜高单峰型，与非疫情期间的特征有所差异.进一步，应用消除趋势波动分析法（DFA）、多重分形消除趋势波动分析法（MFDFA）和概率统计分析，研究了大气复合系统中PM_2.5和O₃质量浓度序列的长期持续性和多重分形结构.结果发现3个城市PM_2.5和O₃浓度序列均具有显著的长期持续性特征和较强的多重分形结构，同时，应用去趋势互相关分析法（DCCA）方法和多重分形去趋势互相关分析法（MFDCCA）对PM_2.5和O₃两者之间的互相关性进行了分析，发现PM_2.5-O₃之间的互相关也存在显著的长期持续性特征以及在不同时间尺度存在多重分形特征.进一步将疫情期间得到的非线性分析结果与2018年和2019年同期非疫情期间的结果进行了对比分析.最后，基于自组织临界理论（SOC）探讨了大气PM_2.5和O₃浓度时空演化的内在动力规律，并结合典型区域气象特征，阐明了SOC内禀动力机制可能是COVID-19疫情期间大气高污染形成的主导机制之一.疫情期间大气PM_2.5和O₃浓度并非分别独自演化，而是依然保持复杂的相互作用.静稳气象条件下，大气复合污染内部的非线性耦合作用可能达到动力学临界状态，将导致长株潭城市群在疫情期间仍有发生大气高污染的风险.

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	吴波
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	鲍冰逸
	杜娟
	史凯

关键词 ：日变化规律, 长期持续性, 多重分形, 幂律统计, 自组织临界, PM_2.5, O₃

Abstract：Based on hourly concentration of PM_2.5 and O₃ during the epidemic period (January 24, 2020 to May 31, 2020) in Changsha, Zhuzhou and Xiangtan, the diurnal patterns, long-term persistence, multifractality and self-organization evolution dynamics of these two pollutants were studied to reveal the internal dynamic mechanism of the occurrence and evolution of heavy pollution events during the epidemic period. Firstly, the diurnal patterns of PM_2.5 and O₃ concentrations were investigated. It showed that O₃ showed a single peak of high concentration in the daytime and low in the night, while PM_2.5 showed a single lowest peak concentration in the day and high in the night, which was different from the pattern in non-epidemic periods. Furthermore, detrended fluctuation analysis (DFA), the multifractal detrended fluctuation analysis (MFDFA) and probability statistical analysis were applied to study the long-term persistence, multi-fractal structure of PM_2.5 and O₃ series. The results showed that PM_2.5 and O₃ series had significant long-term persistence characteristics and strong multi-fractal structures for the three cities. Meanwhile, detrended cross-correlation analysis (DCCA) and multifractal detrended cross-correlation analysis (MFDCCA) were conducted to estimate the cross-correlations between PM_2.5 and O₃ series. Long-term persistence as well as multifractal features at different time scales was also observed in PM_2.5-O₃ cross-correlations. Next, nonlinear analysis results obtained during epidemic period were compared with those obtained in the same periods of non-epidemic years of 2019 and 2018. Finally, based on the self-organized criticality (SOC) theory, the internal dynamic law of spatial and temporal evolution of PM_2.5 and O₃ series was discussed. Combined with the typical regional meteorological characteristics, it was found that the intrinsic dynamic mechanism of SOC may be one of the leading mechanisms of heavy air pollution episodes during the COVID-19 lockdown period. During the epidemic period, PM_2.5and O₃ concentrations did not evolve independently but remained complex interactions. Under the stable meteorological conditions, the nonlinear coupling effect inside the air combined pollution might reach the dynamic critical state, thus, lead to the risk of heavy air pollution in Greater Changsha Metropolitan Region during the epidemic period.

Key words： diurnal patterns long-term persistence characteristics multifractal characteristics power-law self-organized criticality PM_2.5 O₃

收稿日期: 2020-09-27

PACS:

X513

基金资助:湖南省自然科学基金资助项目（2020JJ4504）；吉首大学校级科研项目资助（Jdy20062,Jdx02）

通讯作者: 史凯,教授,einboplure@163.com E-mail: einboplure@163.com

作者简介: 吴波(1995-),男,湖南吉首人,吉首大学硕士研究生,主要从事应用统计分析.发表论文1篇.

引用本文:

吴波, 刘春琼, 张娇, 李彦辉, 陈郁兵, 文烨, 鲍冰逸, 杜娟, 史凯. COVID-19期间区域大气高污染发生的非线性动力机制[J]. 中国环境科学, 2021, 41(5): 2028-2039. WU Bo, LIU Chun-qiong, ZHANG Jiao, LI Yan-hui, CHEN Yu-bing, WEN Ye, BAO Bing-yi, DU Juan, SHI Kai. Nonlinear dynamic mechanism of regional air pollution during the COVID-19 lockdown. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(5): 2028-2039.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2021/V41/I5/2028

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