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<p>Urban atmospheres tend to have nonlinear interactions with other physical parameters that conventional air quality indices rarely capture. To address this limitation, the present study developed a unified complexity-based framework for characterising instability, persistence, and causal coupling in Kolkata’s pollution dynamics. In this context, hourly concentration levels of PM₂.₅, PM₁₀, temperature, relative humidity, and AQI from ten monitoring stations of kolkata were used to calculate four complementary indicators: Environmental Entropy of Stability (EES), Fractal Pollution Memory Index (FPMI), Transfer Entropy (TE), and the integrated Multi-Scalar Urban Environmental Stability Index (MUESI). The EES illustrated a notable spatial gradient in disorder, with PM₂.₅ entropy rising from 2.28 at Avidipta to 2.42 at Flora Fountain, reflecting stronger temporal irregularity that corresponds to the impact of adjacent industrial complex clusters. FPMI reveals contrasting memory regimes in Bidhannagar and Ballygunge, which exhibit strong persistence of h₂ ≈ 1.87 and 0.95, respectively, whereas Urbana Complex and Vivekananda College clearly indicate anti-persistence of h₂ = − 1.999, suggesting rapid pollutant dissipation in better-ventilated zones. TE analysis classified Bidhannagar, Dhapa, and Ballygunge as major causal transmitters due to multiple downwind trajectories, highlighting Kolkata’s air quality as an interconnected dynamical network rather than isolated nodes. The composite MUESI derived from these multi-dimensional signals, illustrate highly stable areas such as Avidipta (–4.639) from strongly unstable hotspots including Sarsuna (+ 4.105). The findings indicate that atmospheric vulnerability in megacities such as Kolkata emerges from the interplay of entropy, long-range trajectories, and directional coupling, offering a new technique for resilience-based air-quality assessment.</p>

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The hidden geometry of urban air: entropy, memory, and causal networks in Kolkata’s atmospheric complexity

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Sajal Mondal

摘要

Urban atmospheres tend to have nonlinear interactions with other physical parameters that conventional air quality indices rarely capture. To address this limitation, the present study developed a unified complexity-based framework for characterising instability, persistence, and causal coupling in Kolkata’s pollution dynamics. In this context, hourly concentration levels of PM₂.₅, PM₁₀, temperature, relative humidity, and AQI from ten monitoring stations of kolkata were used to calculate four complementary indicators: Environmental Entropy of Stability (EES), Fractal Pollution Memory Index (FPMI), Transfer Entropy (TE), and the integrated Multi-Scalar Urban Environmental Stability Index (MUESI). The EES illustrated a notable spatial gradient in disorder, with PM₂.₅ entropy rising from 2.28 at Avidipta to 2.42 at Flora Fountain, reflecting stronger temporal irregularity that corresponds to the impact of adjacent industrial complex clusters. FPMI reveals contrasting memory regimes in Bidhannagar and Ballygunge, which exhibit strong persistence of h₂ ≈ 1.87 and 0.95, respectively, whereas Urbana Complex and Vivekananda College clearly indicate anti-persistence of h₂ = − 1.999, suggesting rapid pollutant dissipation in better-ventilated zones. TE analysis classified Bidhannagar, Dhapa, and Ballygunge as major causal transmitters due to multiple downwind trajectories, highlighting Kolkata’s air quality as an interconnected dynamical network rather than isolated nodes. The composite MUESI derived from these multi-dimensional signals, illustrate highly stable areas such as Avidipta (–4.639) from strongly unstable hotspots including Sarsuna (+ 4.105). The findings indicate that atmospheric vulnerability in megacities such as Kolkata emerges from the interplay of entropy, long-range trajectories, and directional coupling, offering a new technique for resilience-based air-quality assessment.