Clustering time series analysis of tropospheric NO2 and AOD satellite data in global megacities: exploring patterns linked to energy-related variables

IF 5.3 Q2 ENVIRONMENTAL SCIENCES
City and Environment Interactions Pub Date : 2026-04-01 Epub Date: 2026-05-01 DOI:10.1016/j.cacint.2026.100377
Matias I. Volke , Lisdelys González-Rodríguez
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引用次数: 0

Abstract

Megacities, with their high population density and intensive industrial activity, are among the largest contributors to global air pollution. This study analyzes annual trends of tropospheric nitrogen dioxide (tropoNO2) and aerosol optical depth (AOD) using satellite observations across 34 megacities from 2005 to 2022. To capture variability and underlying drivers, we applied Non-Negative Matrix Factorization combined with Hierarchical Clustering, linking pollutant dynamics to energy, socioeconomic, and environmental indicators, with particular attention to the global financial crisis (2008–2009) and the COVID-19 pandemic (2020–2021). Key findings include: (i) tropoNO2 shows stronger correlations with energy consumption indicators than AOD, especially in developed cities, (ii) Cluster analysis revealed three distinct response patterns to global crises: cities with minimal, moderate, or significant emission changes, (iii) Developing cities exhibited greater AOD fluctuations, highlighting vulnerability to economic shocks and weaker regulatory frameworks, (iv) tropoNO2 displayed heterogeneous behaviors, with developed cities often grouped in clusters showing significant changes, potentially associated with motorized transport emissions. This study highlights the contrasting behaviors of tropoNO2 and AOD across megacities, shaped by socioeconomic conditions, regulatory strength, and energy dependence. The proposed methodology provides a robust tool for identifying urban emission patterns and their relationship with economic stability, offering valuable insights for environmental mitigation strategies and sustainable urban planning, as well as for understanding and anticipating the future impacts of global crises or structural changes in energy consumption patterns. These findings contribute to advancing healthier and more resilient urban environments on a global scale.
全球特大城市对流层NO2和AOD卫星数据的聚类时间序列分析:探索与能源相关变量相关的模式
人口密度高、工业活动密集的特大城市是造成全球空气污染的最大因素之一。本研究利用2005年至2022年34个特大城市的卫星观测数据,分析了对流层二氧化氮(tropoNO2)和气溶胶光学深度(AOD)的年趋势。为了捕捉可变性和潜在驱动因素,我们将非负矩阵分解与分层聚类相结合,将污染物动态与能源、社会经济和环境指标联系起来,特别关注全球金融危机(2008-2009年)和COVID-19大流行(2020-2021年)。主要发现包括:(i) tropoNO2与能源消耗指标的相关性强于AOD,特别是在发达城市;(ii)聚类分析揭示了对全球危机的三种不同响应模式:排放变化最小、中等或显著的城市;(三)发展中城市AOD波动较大,突出表明易受经济冲击影响,监管框架薄弱;(四)tropoNO2表现出异质性行为,发达城市往往聚集在一起,表现出显著变化,可能与机动交通排放有关。该研究强调了大城市中tropoNO2和AOD的差异行为,这些差异受社会经济条件、监管力度和能源依赖的影响。拟议的方法为确定城市排放模式及其与经济稳定的关系提供了强有力的工具,为环境缓解战略和可持续城市规划以及了解和预测全球危机或能源消费模式结构性变化的未来影响提供了宝贵的见解。这些发现有助于在全球范围内促进更健康和更有弹性的城市环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
City and Environment Interactions
City and Environment Interactions Social Sciences-Urban Studies
CiteScore
6.00
自引率
3.00%
发文量
15
审稿时长
27 days
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