دانشگاه اصفهان جغرافیا و برنامه ریزی محیطی 2008-5362 37 1 2026 03 21 Increasing Contribution of Absorbing Aerosols and Stabilization of Dust Pollution Regime in Isfahan Province Based on Remote Sensing and Markov Chain Analysis افزایش سهم آئروسل‌های جذبی و تثبیت الگوی آلودگی گردوغبار در استان اصفهان بر پایه سنجش‌ازدور و زنجیره مارکوف 67 106 30505 10.22108/gep.2026.148394.1775 FA علیرضا یوسفی کبریا دکتری هواشناسی کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی، ساری، ایران مهدی نادی دانشیار هواشناسی کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران 0000-0003-0854-8380 بهاره شامگانی مشهدی دانشجوی دکتری هواشناسی کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی، ساری، ایران Journal Article 2026 02 18 Abstract This study investigated the increasing trend, persistence, and spatiotemporal evolution of air pollution and dust aerosols in Isfahan Province over the period of 2020–2025 with particular emphasis on identifying intensification patterns and shifts in aerosol regimes. The spatial and temporal variations in air pollution were examined by using Aerosol Optical Depth (AOD) data from MODIS and the Absorbing Aerosol Index (AAI) derived from Sentinel-5 satellite observations. Analytical approaches included monthly and seasonal heatmaps, time series analysis, frequency distribution assessments, Kernel Density Estimation (KDE), and a Markov chain model to evaluate the stability and daily transition probabilities of pollution classes at the monitoring station of Isfahan. The results revealed that in 2020, AOD values ranged between 0.37 and 0.56; however, in critical areas—including the desiccated Gavkhouni Wetland, Isfahan City, and Khur County—values exceeded 0.96, indicating unhealthy to very unhealthy conditions. In 2021, pollution intensity escalated further with AOD levels reaching 0.72 to over 1.1 in these regions. Although a relative decline was observed during 2022–2025, the central and eastern parts of the province continued to experience unhealthy and very unhealthy conditions. Regarding AAI, a marked increase in absorbing aerosols was recorded in 2022 with values approaching 2.0 followed by a persistent high-pollution state. Notably, more than half of the days throughout the study period were classified as unhealthy or very unhealthy, underscoring the severity and continuity of the pollution episode. Statistically, AOD exhibited a bimodal distribution, whereas AAI displayed a broader distribution concentrated within the 0.5 to 1.5 range, reflecting the structural persistence of pollution and an increased frequency of extreme events. The annual mean AOD rose from 0.245 in 2020 to 0.305 in 2025, representing a 24% increase, while AAI escalated from near-zero values to approximately 1.4 over the same period. Markov chain analysis revealed that the "Moderate" class for AOD with a persistence probability of 66% constituted the most stable state, whereas the "Unhealthy" class for AAI with a 74% persistence probability emerged as the dominant state. The transition probability from Moderate to Unhealthy and Unhealthy to Very Unhealthy were estimated at about 25% and 10–15%, respectively. Overall, only 4–24% of days were classified as clean, while more than 75% of days fell within the Moderate to Very Unhealthy categories. These findings indicated the establishment of a persistent pollution regime in Isfahan Province characterized by a rising AOD baseline, a sharp AAI shift in 2022, and sustained elevated pollution levels. The concentration of pollution sources in the central and eastern regions—specifically the Gavkhouni Wetland, Isfahan City, and Khur County—underscored the need for air quality management strategies to transition toward structural and source-oriented control measures. Keywords: Air pollution, Pollution Persistence, AOD and AAI Indices, Time-Series Analysis, Markov Chain Modeling. Introduction Dust storms represent critical natural phenomena in arid and semi-arid regions, exerting severe impacts on the environment, climate, human health, and economic activities. Although remote sensing has been extensively employed to monitor these storms and identify their source areas, the majority of previous research has remained confined to descriptive analyses of spatial and temporal trends. The present study addressed this gap by focusing on Isfahan Province, a region particularly vulnerable to dust events due to its geographical setting and climatic conditions. The primary objective of this research was to analyze the temporal dynamics of dust events through an integrated approach that combined remote sensing data—specifically Aerosol Optical Depth (AOD) and Absorbing Aerosol Index (AAI)—with Markov chain modeling. This innovative methodological framework enabled the quantitative assessment of transition probabilities among different air pollution levels, thereby offering valuable insights into the stochastic, time-dependent behavior of dust phenomena. By identifying critical hotspots and modeling the evolution of pollution states over time, this study sought to establish a quantitative foundation for a more comprehensive understanding of dust dynamics, ultimately supporting effective environmental management and informed decision-making in Isfahan Province. Materials & Methods Isfahan Province is situated in central Iran, extending between 30°30' to 34°42' N latitude and 49°36' to 55°32' E longitude. The province exhibited considerable topographical diversity, encompassing the Central Zagros mountain ranges in the west and southwest, alongside arid lowland plains—such as Varzaneh and the margins of the Isfahan-Yazd desert—in the central and eastern portions. The region experiences an arid to semi-arid climate with mean annual temperatures ranging from 16 to 18°C and average yearly precipitation of 100–150 mm. Water resources including the Zayandeh-Rud River and groundwater aquifers have substantially diminished in recent decades due to prolonged drought and excessive extraction. Concurrently, industrial expansion and population growth compounded by reduced water availability have exacerbated air pollution and contributed to the intensification of local dust events (Arvin, 2019). This study utilized remote sensing data spanning the period from 2020 to 2025 to analyze dust dynamics across Isfahan Province. The principal datasets comprised AOD derived from the MODIS sensor and the AAI obtained from the Sentinel-5P satellite. All data were processed at daily, monthly, and annual temporal scales using Google Earth Engine (GEE), a cloud-based geospatial analysis platform. Remote Sensing Data Processing GEE was employed to process MODIS and Sentinel-5P data products. For AOD estimation, MODIS data—specifically the Optical_Depth_047 band—were utilized to map spatiotemporal variations in particulate matter concentrations. Sentinel-5P data (COPERNICUS/S5P/OFFL/AER_AI) were used to derive the AAI, which served as an indicator of the intensity and spatial distribution of absorbing aerosols. MODIS, aboard the Terra and Aqua satellites, provided multispectral imagery at spatial resolutions ranging from 250 m to 1000 m (Xiong et al., 2006). Air Pollution Indices AOD (Aerosol Optical Depth):This index quantifies the extinction of solar radiation by atmospheric aerosols. MODIS-derived AOD data were employed to generate spatial distribution maps across the study area. AAI (Absorbing Aerosol Index):This index indicates the presence of UV-absorbing aerosols, such as mineral dust. AAI data from Sentinel-5P were utilized in a comparable manner to assess aerosol characteristics. AQI (Air Quality Index):As a standardized metric ranging from 0 to 500, the AQI is used to report daily air quality levels. Lower values correspond to cleaner air, whereas higher values indicate elevated health risks (Yousefi Kebriya & Nadi, 2025). The classification criteria for AQI, AOD, and AAI are presented in Table 1. Generally, AOD values exceeding 0.3 and AAI values above 0.5 signify unhealthy or hazardous conditions, while an AQI of greater than 100 indicates air that is unhealthy for sensitive groups (Yousefi Kebriya et al., 2025). Markov Chain Model In this study, a Markov chain model was employed to simulate transitions between different pollution states. This discrete-time stochastic model operates on the first-order Markov property, whereby the future state depends solely on the current state, independent of the full historical sequence. The approach involves the calculation of a transition probability matrix (Pij), which estimates the likelihood of moving from one air quality class (i) to another (j) over a given time step (Stoner & Economou, 2020; Morton & Finkenstädt, 2005). Initially, Google Earth Engine was utilized to map the spatial distribution of AOD and AAI across Isfahan Province. Subsequently, the Markov chain model was applied to analyze temporal trends, assess state stability, and predict transitions among different pollution categories. The integration of satellite-derived observations with Markov chain modeling provided a robust analytical framework for spatiotemporal air pollution assessment, thereby offering a scientific foundation for the development of management strategies aimed at controlling particulate matter in Isfahan Province. Research Findings Large portions of Isfahan and Khur counties remained classified within the unhealthy and very unhealthy categories, underscoring the chronic persistence of air pollution in these areas. In 2025, the spatial pattern of the AOD index was largely consistent with that of 2024; however, a further reduction in the extent of polluted zones was observed. During this year, Ardestan and Kashan were predominantly free of significant pollution, with only limited areas falling within the unhealthy range for sensitive groups. Isolated parts of Nain recorded unhealthy conditions with AOD values ranging from 0.38 to 0.58. Nevertheless, the central and eastern regions of the province—particularly Khur County and Isfahan City—continued to experience unhealthy and very unhealthy conditions with AOD values predominantly ranging between 0.56 and 0.87 and exceeding 0.87 in some areas. In 2023, the AAI index exhibited a decreasing trend; nonetheless, numerous cities remained in an unhealthy state. Extensive areas across the eastern, northern, central, and southern parts of the province recorded AAI values between 0.46 and 0.68, as well as above 0.68, confirming the relative persistence of pollution in known hotspots. This declining trend continued into 2024 with unhealthy zones shrinking to more localized patches. In that year, only parts of Isfahan City and the counties of Khur, Nain, Ardestan, and Aran va Bidgol remained in the unhealthy class with values exceeding 0.55, indicating a relative reduction in both the intensity and spatial extent of pollution. In 2025, the AAI index showed a slight increase compared to the previous year; yet, the overall extent of polluted zones continued to diminish. In parts of Aran va Bidgol, Ardestan, and Nain, index values ranged between 0.45 and 0.65, while in portions of Khur and Isfahan City, values exceeding 0.65 were recorded—higher than in other areas—continuing to identify these regions as the primary aerosol hotspots. Time series analysis of the AOD index revealed an upward trend, increasing from approximately 0.245 at the beginning of 2020 to about 0.305 by the end of 2025, which was equivalent to a 24% increase in mean aerosol concentration over the 6-year period. Analysis of the daily transition probability matrix for AAI pollution classes indicated that Unhealthy days exhibited the highest stability with a 74% probability of persistence followed by Very Unhealthy and Good classes, which showed persistence probabilities of 47% and 56%, respectively. Discussion of Results & Conclusion The findings indicated that the spatiotemporal variations in air pollution across the province arose from the simultaneous interaction of an increased overall particulate matter load and changes in the physicochemical properties of aerosols. The convergence of peak values in both indices during critical years—particularly in 2022—suggested that this period witnessed not only a rise in general particulate matter concentrations, but also intensification in the contribution of absorbing aerosols, such as mineral dust and anthropogenic combustion particles. However, the observed discrepancies between the two indices implied that a portion of the AOD fluctuations might be attributed to the accumulation of non-absorbing particles, stable atmospheric conditions, and humidity effects, whereas the AAI more specifically delineated active dust sources and combustion-related emissions. Although these indices were complementary in aerosol pollution assessment, they differed considerably in terms of the informational content they provided and their spatial resolution. The Markovian stability analysis of this long-term distribution revealed that the majority of days in Isfahan were characterized by moderate to unhealthy pollution levels, with clean air being a rare occurrence. Conversely, critical days, though infrequent, exerted severe and abrupt impacts. Overall, the daily AOD pollution system in Isfahan exhibited relative stability within the moderately polluted and polluted classes with a natural tendency toward intensification of pollution. The marked decline in the probability of reverting to clean classes underscored the narrowing window of clean air episodes and the escalating chronic pressure on both public health and the environment. This analysis demonstrates that effective air quality management must prioritize the reduction of moderately polluted and unhealthy days, while also implementing measures to prevent transitions to the Very Unhealthy and Hazardous categories. چکیده این مطالعه با هدف تحلیل افزایش و پایداری آلودگی هوا و گردوغبار و تغییر الگوهای زمانی - مکانی آن در استان اصفهان طی دوره ۲۰۲۰ تا ۲۰۲۵، با تأکید بر شناسایی روندهای تشدید آلودگی و تغییر رژیم آئروسل‌ها انجام شد. تغییرات و پراکنش آلودگی با استفاده از شاخص AOD (MODIS) و AAI (Sentinel-5) تحلیل شد. تحلیل‌ها شامل نقشه‌های حرارتی ماهانه و فصلی، سری‌های زمانی، توزیع فراوانی، منحنی KDE و مدل زنجیره مارکوف برای ارزیابی پایداری و انتقال روزانه کلاس‌های آلودگی در ایستگاه اصفهان بود. نتایج نشان داد در سال ۲۰۲۰ مقادیر AOD در بازه ۰.۳۷ تا ۰.۵۶ قرار داشت و در نواحی بحرانی (تالاب گاوخونی، اصفهان، خور) مقادیر بیش از ۰.۹۶ مشاهده شد. در سال ۲۰۲۱ شدت آلودگی افزایش یافت و مقادیر در این مناطق به بازه ۰.۷۲ تا بیش از ۱.۱ رسید. در دوره ۲۰۲۲ تا ۲۰۲۵، پهنه‌های مرکزی و شرقی همچنان ناسالم باقی ماندند. در شاخص AAI، افزایش شدید ذرات جذبی در سال ۲۰۲۲ با مقادیر نزدیک به ۲ مشاهده شد و سپس وضعیت تثبیت شد؛ به‌طوری‌که بیش از نیمی از روزها در کلاس‌های ناسالم یا بسیار ناسالم قرار داشتند. از نظر آماری، AOD دارای توزیع دووجهی و AAI دارای توزیع پهن در بازه ۰.۵ تا ۱.۵ بود. میانگین سالانه AOD از ۰.۲۴۵ در ۲۰۲۰ به ۰.۳۰۵ در ۲۰۲۵ (افزایش ۲۴٪) و AAI از نزدیک صفر به حدود ۱.۴ افزایش یافت. نتایج زنجیره مارکوف نشان داد کلاس «متوسط» در AOD با احتمال ماندگاری ۶۶٪ پایدارترین وضعیت است، درحالی‌که کلاس «ناسالم» در AAI با احتمال ماندگاری ۷۴٪ به‌عنوان حالت غالب عمل می‌کند. احتمال انتقال از متوسط به ناسالم حدود ۲۵٪ و از ناسالم به بسیار ناسالم حدود ۱۰-۱۵٪ برآورد شد. درمجموع، تنها حدود ۴ تا ۲۴٪ روزها هوای پاک دارند و بیش از ۷۵٪ روزها در وضعیت متوسط تا بسیار ناسالم قرار دارند. نتایج بیانگر شکل‌گیری رژیم آلودگی پایدار در استان اصفهان همراه با افزایش خط پایه AOD، جهش AAI در ۲۰۲۲ و تداوم بالای کلاس‌های ناسالم است. تمرکز کانون‌های آلودگی در مناطق مرکزی و شرقی (تالاب گاوخونی، شهر اصفهان و خور) نشان می‌دهد مدیریت آلودگی باید به سمت کنترل ساختاری و منبع‌محور تغییر یابد.

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