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<p>Air pollution, particularly fine particulate matter (PM2.5), presents complex challenges for urban sustainability. This study aims to analyze the spatio-temporal dynamics of PM2.5 pollution in Mashhad by providing an integrated and novel framework to examine this phenomenon. The distinguishing feature of this framework is the integration of systems dynamics, pollution dissemination, integrated air pollution management, and urban governance theories, using spatial statistical methods and Geographic Information Systems (GIS) to accurately analyze complex pollution patterns and identify the contributing factors. Data from 22 air quality monitoring stations was analyzed using Moran’s I, hotspot analysis, K-function, and IDW interpolation. Key findings revealed a clustered distribution of PM2.5 pollution, with eastern and western areas identified as hotspots and an incredible 327 z-score index The PM2.5 concentration in this city was mostly highest during autumn and peak at the 24.21 mark. An analysis of the AQI index shows that in 1398, air quality has reached the condition of 70.9% in medium and was unhealthy for sensitive areas at 16.7%. The analysis of the time patterns showed an increase in pollution during the cold seasons and the key role of industrial activities and atmospheric conditions (temperature inversion and prevailing wind) in intensifying this phenomenon. In all by giving a view to a better process of what to do in all sides of data with better clarity and the use of those things for the betterment and long term use for urban planning is the point of this research.</p>

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Spatio-Temporal Dynamic Analysis of Urban PM2.5 Pollution: Presenting a Novel Framework for Air Pollution Assessment and Management in Mashhad

  • 期刊论文

  • 发表日期：

    2025年11月21日

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  • Keramatollah Ziari,
  • Vahid Yousefpour Targhi,
  • Mohammad Mohammadzadeh,
  • Majid Golzar

摘要

Air pollution, particularly fine particulate matter (PM2.5), presents complex challenges for urban sustainability. This study aims to analyze the spatio-temporal dynamics of PM2.5 pollution in Mashhad by providing an integrated and novel framework to examine this phenomenon. The distinguishing feature of this framework is the integration of systems dynamics, pollution dissemination, integrated air pollution management, and urban governance theories, using spatial statistical methods and Geographic Information Systems (GIS) to accurately analyze complex pollution patterns and identify the contributing factors. Data from 22 air quality monitoring stations was analyzed using Moran’s I, hotspot analysis, K-function, and IDW interpolation. Key findings revealed a clustered distribution of PM2.5 pollution, with eastern and western areas identified as hotspots and an incredible 327 z-score index The PM2.5 concentration in this city was mostly highest during autumn and peak at the 24.21 mark. An analysis of the AQI index shows that in 1398, air quality has reached the condition of 70.9% in medium and was unhealthy for sensitive areas at 16.7%. The analysis of the time patterns showed an increase in pollution during the cold seasons and the key role of industrial activities and atmospheric conditions (temperature inversion and prevailing wind) in intensifying this phenomenon. In all by giving a view to a better process of what to do in all sides of data with better clarity and the use of those things for the betterment and long term use for urban planning is the point of this research.