运用复杂系统理论理解中国长三角工业基地 PM2.5 和 O3 的协调控制效应

IF 3.9 3区 环境科学与生态学 Q1 ENGINEERING, CIVIL Stochastic Environmental Research and Risk Assessment Pub Date : 2024-08-06 DOI:10.1007/s00477-024-02791-3
Ruhui Cao, Yaxi Xiao, Yangbin Dong, Fuwang Zhang, Kai Shi, Zhanyong Wang
{"title":"运用复杂系统理论理解中国长三角工业基地 PM2.5 和 O3 的协调控制效应","authors":"Ruhui Cao, Yaxi Xiao, Yangbin Dong, Fuwang Zhang, Kai Shi, Zhanyong Wang","doi":"10.1007/s00477-024-02791-3","DOIUrl":null,"url":null,"abstract":"<p>Regional air pollution represents a multifaceted and dynamic system, rendering linear statistical approaches insufficient for capturing its inherent variability, particularly the intricate fluctuations of multiple pollution indicators. Therefore, this study investigates the synergistic evolution mechanisms of PM<sub>2.5</sub> and O<sub>3</sub> in four cities within China’s Yangtze River Delta industrial base from 2013 to 2022, employing complex systems theory. Initially, the presence of multifractality and long-term persistence between PM<sub>2.5</sub> and O<sub>3</sub> is confirmed in each city using the multifractal detrended cross-correlation analysis. Quantitative indicators are then established to evaluate the synergistic control effects of PM<sub>2.5</sub> and O<sub>3</sub>. Furthermore, factors influencing coordinated control are analyzed using the ensemble empirical mode decomposition. Finally, the self-organized criticality (SOC) theory is introduced to elucidate dynamic pollution patterns. The results indicate the following: (1) Multifractality and long-term persistence exist between PM<sub>2.5</sub> and O<sub>3</sub> in the four cities, with persistence strengthening alongside the implementation of atmospheric pollution prevention and control policies. The application of complex systems theory facilitates the explanation and quantification of the synergistic control effectiveness of PM<sub>2.5</sub> and O<sub>3</sub>. (2) Since 2013, with the exception of Nanjing, the coordinated control effects of PM<sub>2.5</sub> and O<sub>3</sub> in Shanghai, Hangzhou, and Suzhou have been unsatisfactory and have shown little improvement. (3) Compared to short-term pollution emissions from human activities, annual atmospheric control measures, periodic meteorological variations, and long-range transport of regional pollutants exert a greater influence on the synergistic regulation effects of PM<sub>2.5</sub> and O<sub>3</sub>. (4) SOC may serve as the primary mechanism influencing the effectiveness of the synergistic regulation of PM<sub>2.5</sub> and O<sub>3</sub>. Sudden events, such as epidemic control measures, can disrupt the existing balance between PM<sub>2.5</sub> and O<sub>3</sub>, thereby diminishing the coordinated control effects.</p>","PeriodicalId":21987,"journal":{"name":"Stochastic Environmental Research and Risk Assessment","volume":"12 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using complex systems theory to comprehend the coordinated control effects of PM2.5 and O3 in Yangtze River Delta industrial base in China\",\"authors\":\"Ruhui Cao, Yaxi Xiao, Yangbin Dong, Fuwang Zhang, Kai Shi, Zhanyong Wang\",\"doi\":\"10.1007/s00477-024-02791-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Regional air pollution represents a multifaceted and dynamic system, rendering linear statistical approaches insufficient for capturing its inherent variability, particularly the intricate fluctuations of multiple pollution indicators. Therefore, this study investigates the synergistic evolution mechanisms of PM<sub>2.5</sub> and O<sub>3</sub> in four cities within China’s Yangtze River Delta industrial base from 2013 to 2022, employing complex systems theory. Initially, the presence of multifractality and long-term persistence between PM<sub>2.5</sub> and O<sub>3</sub> is confirmed in each city using the multifractal detrended cross-correlation analysis. Quantitative indicators are then established to evaluate the synergistic control effects of PM<sub>2.5</sub> and O<sub>3</sub>. Furthermore, factors influencing coordinated control are analyzed using the ensemble empirical mode decomposition. Finally, the self-organized criticality (SOC) theory is introduced to elucidate dynamic pollution patterns. The results indicate the following: (1) Multifractality and long-term persistence exist between PM<sub>2.5</sub> and O<sub>3</sub> in the four cities, with persistence strengthening alongside the implementation of atmospheric pollution prevention and control policies. The application of complex systems theory facilitates the explanation and quantification of the synergistic control effectiveness of PM<sub>2.5</sub> and O<sub>3</sub>. (2) Since 2013, with the exception of Nanjing, the coordinated control effects of PM<sub>2.5</sub> and O<sub>3</sub> in Shanghai, Hangzhou, and Suzhou have been unsatisfactory and have shown little improvement. (3) Compared to short-term pollution emissions from human activities, annual atmospheric control measures, periodic meteorological variations, and long-range transport of regional pollutants exert a greater influence on the synergistic regulation effects of PM<sub>2.5</sub> and O<sub>3</sub>. (4) SOC may serve as the primary mechanism influencing the effectiveness of the synergistic regulation of PM<sub>2.5</sub> and O<sub>3</sub>. Sudden events, such as epidemic control measures, can disrupt the existing balance between PM<sub>2.5</sub> and O<sub>3</sub>, thereby diminishing the coordinated control effects.</p>\",\"PeriodicalId\":21987,\"journal\":{\"name\":\"Stochastic Environmental Research and Risk Assessment\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stochastic Environmental Research and Risk Assessment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1007/s00477-024-02791-3\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Environmental Research and Risk Assessment","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s00477-024-02791-3","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

摘要

区域空气污染是一个多方面的动态系统,线性统计方法不足以捕捉其内在的可变性,特别是多个污染指标的复杂波动。因此,本研究运用复杂系统理论,研究了 2013 年至 2022 年中国长三角工业基地内四个城市 PM2.5 和 O3 的协同演化机制。首先,利用多分形去趋势交叉相关分析,证实了每个城市的 PM2.5 和 O3 之间存在多分形性和长期持续性。然后建立定量指标来评估 PM2.5 和 O3 的协同控制效果。此外,还利用集合经验模式分解分析了影响协同控制的因素。最后,引入自组织临界(SOC)理论来阐明动态污染模式。研究结果表明(1) 四个城市的 PM2.5 和 O3 之间存在多重性和长期持续性,随着大气污染防治政策的实施,持续性不断加强。复杂系统理论的应用有助于解释和量化 PM2.5 和 O3 的协同控制效果。(2)2013 年以来,除南京外,上海、杭州、苏州等地的 PM2.5 和 O3 协同控制效果并不理想,改善幅度不大。(3)与人类活动的短期污染排放相比,年度大气控制措施、周期性气象变化和区域污染物的长程飘移对 PM2.5 和 O3 的协同调控效果影响更大。(4)SOC 可能是影响 PM2.5 和 O3 协同调节效果的主要机制。突发事件(如流行病控制措施)可能会打破 PM2.5 和 O3 之间的现有平衡,从而削弱协同控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Using complex systems theory to comprehend the coordinated control effects of PM2.5 and O3 in Yangtze River Delta industrial base in China

Regional air pollution represents a multifaceted and dynamic system, rendering linear statistical approaches insufficient for capturing its inherent variability, particularly the intricate fluctuations of multiple pollution indicators. Therefore, this study investigates the synergistic evolution mechanisms of PM2.5 and O3 in four cities within China’s Yangtze River Delta industrial base from 2013 to 2022, employing complex systems theory. Initially, the presence of multifractality and long-term persistence between PM2.5 and O3 is confirmed in each city using the multifractal detrended cross-correlation analysis. Quantitative indicators are then established to evaluate the synergistic control effects of PM2.5 and O3. Furthermore, factors influencing coordinated control are analyzed using the ensemble empirical mode decomposition. Finally, the self-organized criticality (SOC) theory is introduced to elucidate dynamic pollution patterns. The results indicate the following: (1) Multifractality and long-term persistence exist between PM2.5 and O3 in the four cities, with persistence strengthening alongside the implementation of atmospheric pollution prevention and control policies. The application of complex systems theory facilitates the explanation and quantification of the synergistic control effectiveness of PM2.5 and O3. (2) Since 2013, with the exception of Nanjing, the coordinated control effects of PM2.5 and O3 in Shanghai, Hangzhou, and Suzhou have been unsatisfactory and have shown little improvement. (3) Compared to short-term pollution emissions from human activities, annual atmospheric control measures, periodic meteorological variations, and long-range transport of regional pollutants exert a greater influence on the synergistic regulation effects of PM2.5 and O3. (4) SOC may serve as the primary mechanism influencing the effectiveness of the synergistic regulation of PM2.5 and O3. Sudden events, such as epidemic control measures, can disrupt the existing balance between PM2.5 and O3, thereby diminishing the coordinated control effects.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.10
自引率
9.50%
发文量
189
审稿时长
3.8 months
期刊介绍: Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.
期刊最新文献
Hybrid method for rainfall-induced regional landslide susceptibility mapping Prediction of urban flood inundation using Bayesian convolutional neural networks Unravelling complexities: a study on geopolitical dynamics, economic complexity, R&D impact on green innovation in China AHP and FAHP-based multi-criteria analysis for suitable dam location analysis: a case study of the Bagmati Basin, Nepal Risk and retraction: asymmetric nexus between monetary policy uncertainty and eco-friendly investment
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1