基于网络理论的城市周末效应时空演化研究

IF 1 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
Atmosfera Pub Date : 2021-02-22 DOI:10.20937/ATM.52993
I. Hernández-Paniagua, Rodrigo Lopez Farias, J. Corpus
{"title":"基于网络理论的城市周末效应时空演化研究","authors":"I. Hernández-Paniagua, Rodrigo Lopez Farias, J. Corpus","doi":"10.20937/ATM.52993","DOIUrl":null,"url":null,"abstract":"The occurrence of higher ground-level O 3 concentrations on weekends rather than on weekdays, despite reduced anthropogenic activity in urban areas, is known as the O 3 weekend effect (OWE). Here, we present an approach to analyse OWE spatio-temporal variations in urban areas, integrated by the trend, prediction and network representation. We used data from ten monitoring sites geographically distributed within the Mexico City Metropolitan Area (MCMA) recorded during 1994-2018. The OWE occurrence within the MCMA ranged typically between 40 and 60 % of the total weeks per year. The annual differences between weekday and weekend O 3 peaks (magnitudes) showed were most significant on Sundays. Naive, Linear and Auto-regressive Integrated Moving Average models were tested for predicting the OWE annual occurrences and magnitudes. There was no single model that outperformed significantly for predicting OWE at all sites. The proposed concept of generalised OWE ( GOWE ) implies that at least half of the sites under study exhibited simultaneous OWE occurrence. GOWE is represented as a network and its integration with prediction models is useful to determinate the OWE spread over the MCMA in the following years. The GOWE occurrence showed an increasing trend interpreted as the spread of VOC-limited conditions over most of the MCMA. Predicted data suggest that, with the current emission control policies, the GOWE will continue occurring. The integrated methodology presented permits the acquisition of valuable insights into the design of potential air quality control strategies.","PeriodicalId":55576,"journal":{"name":"Atmosfera","volume":"1 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2021-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of network theory to study spatio-temporal evolution in the weekend effect in urban areas\",\"authors\":\"I. Hernández-Paniagua, Rodrigo Lopez Farias, J. Corpus\",\"doi\":\"10.20937/ATM.52993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The occurrence of higher ground-level O 3 concentrations on weekends rather than on weekdays, despite reduced anthropogenic activity in urban areas, is known as the O 3 weekend effect (OWE). Here, we present an approach to analyse OWE spatio-temporal variations in urban areas, integrated by the trend, prediction and network representation. We used data from ten monitoring sites geographically distributed within the Mexico City Metropolitan Area (MCMA) recorded during 1994-2018. The OWE occurrence within the MCMA ranged typically between 40 and 60 % of the total weeks per year. The annual differences between weekday and weekend O 3 peaks (magnitudes) showed were most significant on Sundays. Naive, Linear and Auto-regressive Integrated Moving Average models were tested for predicting the OWE annual occurrences and magnitudes. There was no single model that outperformed significantly for predicting OWE at all sites. The proposed concept of generalised OWE ( GOWE ) implies that at least half of the sites under study exhibited simultaneous OWE occurrence. GOWE is represented as a network and its integration with prediction models is useful to determinate the OWE spread over the MCMA in the following years. The GOWE occurrence showed an increasing trend interpreted as the spread of VOC-limited conditions over most of the MCMA. Predicted data suggest that, with the current emission control policies, the GOWE will continue occurring. The integrated methodology presented permits the acquisition of valuable insights into the design of potential air quality control strategies.\",\"PeriodicalId\":55576,\"journal\":{\"name\":\"Atmosfera\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2021-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmosfera\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.20937/ATM.52993\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmosfera","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.20937/ATM.52993","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

尽管城市地区的人为活动减少,但周末地面臭氧浓度高于工作日,这被称为臭氧周末效应(OWE)。在此,我们提出了一种综合趋势、预测和网络表征的方法来分析城市地区的OWE时空变化。我们使用了1994-2018年期间在墨西哥城大都市区(MCMA)地理上分布的十个监测点的数据。在MCMA范围内,OWE的发生率通常在每年总周数的40%至60%之间。平日与周末臭氧峰值(量级)的年差异在周日最为显著。对朴素、线性和自回归的综合移动平均模型进行了测试,用于预测OWE的年发生率和强度。没有一个单一的模型在预测所有站点的OWE方面表现明显。提出的广义欠欠(GOWE)概念意味着至少有一半的研究地点同时发生欠欠。GOWE被表示为一个网络,它与预测模型的集成有助于确定未来几年在MCMA上的OWE分布。GOWE的发生呈增加趋势,这被解释为voc限制条件在MCMA大部分地区的扩散。预测数据表明,在当前的排放控制政策下,GOWE将继续发生。所提出的综合方法可以为设计潜在的空气质量控制策略提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of network theory to study spatio-temporal evolution in the weekend effect in urban areas
The occurrence of higher ground-level O 3 concentrations on weekends rather than on weekdays, despite reduced anthropogenic activity in urban areas, is known as the O 3 weekend effect (OWE). Here, we present an approach to analyse OWE spatio-temporal variations in urban areas, integrated by the trend, prediction and network representation. We used data from ten monitoring sites geographically distributed within the Mexico City Metropolitan Area (MCMA) recorded during 1994-2018. The OWE occurrence within the MCMA ranged typically between 40 and 60 % of the total weeks per year. The annual differences between weekday and weekend O 3 peaks (magnitudes) showed were most significant on Sundays. Naive, Linear and Auto-regressive Integrated Moving Average models were tested for predicting the OWE annual occurrences and magnitudes. There was no single model that outperformed significantly for predicting OWE at all sites. The proposed concept of generalised OWE ( GOWE ) implies that at least half of the sites under study exhibited simultaneous OWE occurrence. GOWE is represented as a network and its integration with prediction models is useful to determinate the OWE spread over the MCMA in the following years. The GOWE occurrence showed an increasing trend interpreted as the spread of VOC-limited conditions over most of the MCMA. Predicted data suggest that, with the current emission control policies, the GOWE will continue occurring. The integrated methodology presented permits the acquisition of valuable insights into the design of potential air quality control strategies.
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
Atmosfera
Atmosfera 地学-气象与大气科学
CiteScore
2.20
自引率
0.00%
发文量
46
审稿时长
6 months
期刊介绍: ATMÓSFERA seeks contributions on theoretical, basic, empirical and applied research in all the areas of atmospheric sciences, with emphasis on meteorology, climatology, aeronomy, physics, chemistry, and aerobiology. Interdisciplinary contributions are also accepted; especially those related with oceanography, hydrology, climate variability and change, ecology, forestry, glaciology, agriculture, environmental pollution, and other topics related to economy and society as they are affected by atmospheric hazards.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信