研究报告
史凯.成都市一次重度灰霾期间大气PM2.5的自组织临界特性[J].环境科学学报,2014,34(10):2645-2653
成都市一次重度灰霾期间大气PM2.5的自组织临界特性
- Self-organized criticality of PM2.5 during a typical haze period in Chengdu,China
- 基金项目：国家自然科学基金 (No.41105118);湖南省教育厅科学研究青年项目(No.13B089);湖南省自然科学基金青年人才培养联合基金(No.13JJB012)
- 作者
- 单位
- 史凯
- 吉首大学生态旅游湖南省重点实验室,吉首 416000;吉首大学生物资源与环境科学学院,吉首 416000
- 摘要：2013年1—2月期间,四川省成都市出现大范围、长时间、高浓度的严重霾污染.本文运用频度统计分析和消除趋势波动分析方法,研究了成都市2013年1月25日—2月7日一次典型重度灰霾期间8个监测站点(草堂寺、人民公园、梁家巷、金泉两河、十里店、沙河铺、三瓦窑、灵岩寺)大气PM2.5小时平均浓度序列的时空演化规律.结果表明,各站点大气PM2.5的浓度波动并非随机,而在统计上服从典型的负幂律分布,同时均表现出很强的长期持续性特征.这些特征刻画了灰霾期间大气PM2.5浓度波动的宏观特征.将PM2.5浓度演化与沙堆崩塌进行类比,发现大气PM2.5演化具有自组织临界性复杂系统的基本特征.进一步根据自组织临界(SOC)理论,建立了大气PM2.5数值沙堆模型,模型算法考虑了此次灰霾期间成都市的气象因素和PM 2.5的迁移扩散机制.通过对该模型的数值模拟,能够定量阐明此次重度灰霾期间成都市各监测站点大气PM2.5浓度时空波动宏观统计规律的产生根源.同时,深入讨论了该模型的自组织临界特征.模拟结果和实际结果的高度一致表明该模型真正阐明了导致PM2.5浓度时空波动的重要动力机制.SOC内禀机制是控制此次成都市灰霾期间大气PM2.5浓度演化的主要机制之一.本研究可为灰霾期间PM2.5的演化动力学提供新的研究方法.
- Abstract：The cumulative distributions statistics and temporal scaling properties of the hourly PM2.5 average concentration series during a typical haze episode (from 25 January to 7 February,2013) at eight air monitoring stations of Chengdu (southwestern China) were explored by using frequency-size analysis and detrended fluctuation analysis method.The results show that the probability distribution functions of PM2.5 concentrations are characterized by power-law distribution,and the temporal scaling behaviors exhibit long term correlation. Further,we attempt to find the answers on the emergence of long-term correlation and power-law distribution in PM2.5 by a self-organized criticality (SOC) framework specially designed to model the dynamics of complex systems.A novel PM2.5 evolution model is developed on the bases of SOC theory.The model is a continuous,directional,non-conservative,attenuated cellular automation modeling,which shows robust SOC behaviour in certain dynamical region.The self-organized criticality properties of PM2.5 evolution are discussed. This SOC behavior is related to a statistically steady state that implies the presence of long-term correlation and power-law distribution in PM2.5 evolution during the haze period.We have shown that a simplest possible mechanism for PM2.5 evolution is suffici-ent to recover essentially long-term correlation and power-law distribution documented in PM2.5 concentrations of Chengdu city.The high correspondence of the results to observations indicates that the model provides an effective parameterization of the key physical process that governs PM2.5 fluctuation in the whole haze period.
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