Urban Air Quality Assessment: Variability and Behavior of Fine Particles under Tehran’s Climatic Conditions

Urban Air Quality Assessment: Variability and Behavior of Fine Particles under Tehran’s Climatic Conditions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Urban Air Quality Assessment: Variability and Behavior of Fine Particles under Tehran’s Climatic Conditions Balal Oroji This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8207062/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Due to rapid industrialization, population growth, and urban development, Tehran faces serious air pollution challenges. In this study, the concentration of fine particles with an average diameter of 0.4 µm was monitored at four stations across Tehran over a one year period. The results indicated that the annual mean concentration ranged from 0.33 µg/m 3 in winter to 0.70 µg/m 3 in summer, exhibiting a clear seasonal pattern. Concentrations increased during warm months due to higher temperatures, lower relative humidity, atmospheric stability, and urban activities, while they decreased in cold months under the influence of precipitation and atmospheric cleansing. Statistical analysis revealed a relatively strong inverse relationship between relative humidity and particle concentration (R 2 = 0.73) and a direct correlation between temperature and particle concentration (R 2 = 0.81). Spatially, stations near urban pollution sources recorded higher concentrations, whereas peripheral stations showed lower levels. SEM analysis indicated a diverse particle composition of dual origin (natural and anthropogenic), with finer particles primarily from combustion and mobile sources, and coarser particles from dust, construction, and mineral sources. These findings highlight the critical role of climatic conditions and local sources in fine particle variability and underscore their importance in urban air quality management and forecasting. Fine Particles Air Pollution Particulate Matter Climatic Parameters Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Suspended particles in the atmosphere exhibit a wide range of sizes and chemical compositions depending on their pollution sources. These particles can originate from natural sources or human activities. Among natural sources, phenomena such as volcanic eruptions, large scale forest and grassland fires, local storms, and the dispersion of mineral materials are considered the main contributors to particle emissions. In contrast, human activities play a significant role in increasing the concentration of suspended particles. Processes such as the combustion of fossil fuels, biomass burning, vehicular traffic, tire wear and abrasion during braking, aviation and maritime transportation, construction and infrastructure projects, the use of wood burning stoves, and the operation of building heating and cooling systems are also important sources of atmospheric particulate emissions [ 1 – 6 ]. A significant relationship has been observed atmospheric suspended particles and various diseases, including respiratory and cardiovascular conditions [ 7 – 10 ]. Also, fluctuations in the concentration of particulate matter with diameters less than 2.5 micrometers (PM 2.5 ) in the air are significantly associated with changes in mortality rates and the daily incidence of health complications in human populations [ 11 – 13 ]. Particles smaller than 2.5 micrometers have the greatest impact on human health because they can penetrate the deepest parts of the respiratory system and lungs, causing harmful effects [ 14 , 7 ]. Although the health effects of air pollutant exposure in adults are considerable, children and individuals with pre-existing conditions are significantly more vulnerable and at higher risk. Therefore, exposure to air pollutants represents a major public health and environmental concern [ 15 , 16 ]. One of the sensitive issues regarding particulate matter is the harmful impact of fine particles on human health. Due to their ability to penetrate deep into the respiratory system, prolonged exposure to these particles poses serious health concerns. Such exposure has been associated with a range of adverse health effects, including respiratory disorders, cardiovascular problems, brain inflammation and neurological damage, digestive disturbances, and an increased risk of developing diabetes [ 2 , 17 , 18 ]. Therefore, assessing the concentration of these particles can help prevent health risks to humans. The process of industrialization, especially in developing countries, is one of the main factors contributing to environmental damage. One of the significant consequences of this process is air pollution, which is listed among the top ten serious environmental health challenges and is directly linked to increased global mortality [ 19 , 20 ]. Research indicates that this issue results from a combination of factors, including the growth in private vehicle use, aging vehicles, consumption of low quality fuels, poor road conditions, and insufficient efficient urban infrastructure. This complexity makes air pollution management feasible only through the enforcement of strict environmental regulations [ 21 ]. Although the detrimental effects of air pollutants are most evident in urban areas, this phenomenon is not limited to cities; pollutants can be transported over long distances and even affect background pollution on a hemispheric scale [ 22 ]. Therefore, air pollution should be considered not merely a local concern but a global and long term issue [ 23 ]. According to the Environmental Protection Agency, pollutants from fuel combustion are classified into two groups: criteria pollutants and non criteria pollutants. In recent years, Tehran has become one of the cities with the highest levels of air pollution in the country due to rapid urban expansion, increased industrial activities, and climate changes. The rise in atmospheric particulate matter is considered one of the most significant environmental and health challenges for the residents of this metropolis. Studies indicate that a large portion of these particles originates from human activities, including motor vehicle traffic, industrial operations, and local dust storms, while a share of the particulate matter is also attributable to natural phenomena such as local dust storms [ 24 ]. Atmospheric stability has increased personal vehicle traffic within the city, and the construction of high rise buildings in recent years has raised particulate matter concentrations to highly hazardous levels, severely reducing air quality [ 25 ]. The presence of fine particle sources across the city has elevated their concentrations to dangerous levels. In this study, we aim to investigate the concentration of fine particles (0.4 micrometers) over a one year period in Tehran and examine their variations with respect to climatic parameters. The diverse climatic conditions in Tehran, along with atmospheric stability during the cold seasons, can prolong particle residence times during the day and potentially increase long term human exposure. 2 Materials and Methods 2.1 Sampling Station Locations Suspended particulate matter is one of the most significant atmospheric pollutants, with adverse effects on human health and environmental quality. Due to its high population density, heavy traffic, and construction activities, Tehran is exposed to elevated levels of air pollution. Examining seasonal variations in particulate matter concentrations can help identify major sources and inform the design of effective control policies. Climatically, Tehran is located in a semi arid region, experiencing cold and humid winters and hot, dry summers. The prevailing winds come from the west and northwest, but their speed decreases upon encountering the Alborz Mountains. On many days of the year, weak airflows and stable weather conditions prevail. This atmospheric stability, especially during the colder months, increases the occurrence of temperature inversions in the lower layers of the atmosphere, leading to the accumulation of pollutants and suspended particles. In addition to natural factors, uneven urban development, population growth, and increased pollutant sources including industries, vehicles, power plants, and heating systems have reduced the environment's self purification capacity. This trend has resulted in chronic air pollution crises, which in recent years have even led to widespread urban shutdowns. Therefore, Tehran’s geographical location and natural characteristics not only provide the environmental context but also serve as determining factors in the intensity of air pollution. Considering the geographical position and regional characteristics, as well as the prevailing wind direction, four points were selected as sampling stations. The study area and the distribution of sampling stations are shown in Fig. 1 . 2.2 Sampling This study was conducted from September 2021 to August 2022 in Tehran, the capital of Iran. In selecting the sampling locations, parameters such as distance from the main roads, prevailing wind direction, urban traffic, point source pollutants, and pedestrian activity were considered. The average sampling height above ground level was 13 meters, and the average duration of each sampling session was 6 hours. Additionally, local storms and atmospheric stability were taken into account when choosing sampling days to assess the influence of these conditions on the sample quantities. To collect particulate matter, an Andersen cascade impactor was used. This device operates at a constant flow rate of 28.3 liters per minute, maintained by a continuous vacuum pump, and consists of eight aluminum stages [ 26 ]. In this system, the airflow directs suspended particles along curved paths, separating and collecting them at each stage according to their aerodynamic size. Based on this mechanism, particles settle on metallic plates according to their aerodynamic diameter. In the last stage of the sampler, a backup layer is placed, where particles with a diameter of 0.4 micrometers and smaller are captured. The particle concentration is generally determined by weighing the collected particles or by counting them, which allows for quantitative analysis of particle composition and distribution in the environment [ 27 ]. In each sampling session, the weight of the backup filter was measured before and after particle collection, and the difference between these two values was considered as the particle concentration. 3 Results and discussion The results obtained from the measurement of 0.4 µm particulate matter at the four stations are presented in Fig. 2 . According to these results, the average concentration of these particles reached its minimum in January at 0.33 µg/m 3 , indicating more favorable conditions during the winter season. The maximum concentration was observed in August and September at 0.70 µg/m 3 , reflecting higher particle concentrations in summer. Overall, the general trend showed an increase from winter to summer, with a relative decrease in autumn. The observed pattern indicates the significant role of meteorological conditions in the dispersion and accumulation of particulate matter. During winter and the colder months, precipitation and atmospheric cleansing reduce particle concentrations, whereas in summer, due to atmospheric stability, lower rainfall, and increased pollutant sources such as dust, construction activities, and vehicular traffic, particle concentrations reach their peak. In autumn, the onset of seasonal precipitation leads to a gradual decrease in concentrations. According to previous studies and the results of this research, the occurrence of temperature inversion in late autumn and early winter is one of the reasons for the increased concentration of particulate matter in Tehran, particularly for particles smaller than 2.5 µm. Although fine particles constitute a smaller fraction of the total particulate matter by mass, even a slight increase in their concentration can pose health risks to humans. Evidence suggests that the toxicity of fine particles per unit mass increases as particle size decreases [ 28 , 29 ]. The results indicate that the temporal variations of 0.4 µm particle concentrations in the study area follow both seasonal and spatial patterns over the course of a year. In general, the annual mean concentration of particles varied from 0.33 µg/m 3 in January to 0.70 µg/m 3 in September. These variations indicate higher particle concentrations during the warm season (July to September) and lower concentrations during the cold season (January and February). This pattern can be attributed to a combination of climatic and urban factors. During the warmer months, increased Temperatures, intensified photochemical processes, and weaker atmospheric stability contribute to higher fine particle concentrations, whereas during the colder months, precipitation, higher relative humidity, and occasional Temperature inversions lead to relatively lower concentrations. Spatially, stations St2 and St3 generally exhibited the highest concentrations for most months. The maximum values for these stations were recorded in August and September at 0.85 and 0.80 µg/m 3 , respectively. This may indicate the influence of local pollutant sources such as heavy traffic, construction activities, or proximity to urban industries. Considering the locations of these two stations, their proximity to major city streets and high traffic volumes, along with the aging of urban transport fleets, likely contributed to increased particle concentrations in these areas. In contrast, station St4 recorded the lowest 0.4 µm particulate matter concentrations for most months. In January and February, the concentrations were 0.23 and 0.27 µg/m 3 , respectively, possibly due to its greater distance from high traffic roads or better atmospheric ventilation in that area. This range of variations reflects a distinct seasonal pattern in particle concentration fluctuations, with the lowest values in the cold months (January and February) and the highest in the warm months (July to September). Such a pattern can be attributed to the effects of climatic conditions on pollutant dispersion and stability. During the cold months, precipitation and higher relative humidity wash out the atmosphere, reducing particulate matter, whereas during the warm months, higher Temperatures, local dust storms, intensified photochemical processes, and increased secondary particle formation lead to elevated fine particle concentrations. The observed pattern in the data indicates that Tehran exhibits spatial heterogeneity in fine particle pollution, and this heterogeneity can play an important role in assessing health risks and developing pollution reduction policies. Furthermore, the significant increase in particle concentration during the warm season may serve as a warning for public health, particularly for vulnerable groups such as children, the elderly, and patients with respiratory conditions. Given that this monitoring station is located in the eastern part of Tehran and considering the prevailing wind direction, there is consistently greater concern about the accumulation of fine particles in this area compared to other parts of the city. A simultaneous examination of the concentration of suspended particles with an average size of 0.4 µm and relative humidity variations in Tehran shows an inverse relationship between these two parameters. Specifically, the data indicate that when relative humidity is low (between 16 and 22%), particle concentrations reach their maximum. For example, at 16% humidity, particle concentration is approximately 0.70 µg/m 3 , and at 22% humidity, the concentration ranges from 0.58 to 0.70 µg/m 3 . Conversely, under higher humidity conditions, particle concentration decreases; for instance, at 48.5% humidity, the concentration reaches its minimum value of around 0.35 µg/m 3 . This pattern suggests that under low humidity conditions, particle stability and residence time in the atmosphere are higher, while natural removal mechanisms such as condensation and precipitation are less effective. In addition, under such conditions, increased dust from dry air and resuspension of particles from soil and urban surfaces can contribute to higher fine particle concentrations. The opposite occurs under high humidity conditions. When relative humidity is high, particles tend to absorb water due to hygroscopic growth and rapidly transform into larger particles, increasing their likelihood of deposition. High humidity also raises the possibility of precipitation or dew, which washes out particles and reduces their atmospheric concentration. The data indicate that low relative humidity is one of the conditions facilitating increased 0.4 µm particle concentrations in Tehran. This is particularly important during hot and dry seasons, such as summer, when rising Temperatures and decreasing humidity, combined with atmospheric stability and urban dust resuspension, can lead to a significant increase in particulate matter load. Therefore, in air quality management, attention to humidity conditions alongside other climatic variables is essential for more accurately predicting and controlling fine particle fluctuations. The results also show that at intermediate humidity levels of approximately 31.5 to 39.5%, particle concentrations fluctuated between 0.40 and 0.53 µg/m 3 . This indicates that relative humidity alone is not the sole determining factor; other environmental parameters, such as wind speed and direction, Temperature, and traffic intensity, also play a significant role in particle concentrations alongside humidity. A linear regression model based on the monitoring data demonstrated a relatively strong inverse relationship between relative humidity and suspended particle concentration. According to the results, for each 1% increase in relative humidity, the particle concentration decreases by an average of approximately 0.01 µg/m 3 , while the intercept of the Eq. (0.831 µg/m 3 ) represents the approximate particle concentration under near zero humidity conditions. Moreover, the coefficient of determination (R² = 0.73) indicates that about 73% of the variation in particle concentration can be explained by changes in relative humidity. This finding aligns with existing scientific understanding: under low humidity, particle residence time is longer and concentrations are higher, whereas increasing humidity leads to hygroscopic growth and deposition, reducing concentrations. Figure 3 illustrates the relationship between particle concentration and relative humidity over the study period. As shown in the figure, under low humidity conditions (below 20%), particle concentration reaches its maximum (around 0.7 µg/m 3 ), while at higher humidity levels (above 45%), concentrations drop below 0.35 µg/m 3 . These results indicate that low relative humidity can create conditions conducive to longer particle residence times and higher atmospheric concentrations. Conversely, increasing relative humidity promotes particle hygroscopic growth and enhances the likelihood of deposition or washout, leading to decreased concentrations. Overall, this analysis confirms that relative humidity is a key factor in variations of fine particle concentrations in Tehran and, along with other climatic variables (such as Temperature, wind, and air pressure), can be used in predicting and managing air quality. Figure 4 , illustrates the trend of 0.4 micrometer particle concentrations relative to Temperature over the study period. Analysis of the environmental Temperature data and particulate matter concentrations in the region indicates that Temperature variations play a significant role in particle concentration fluctuations. In general, increases in Temperature were associated with an upward trend in particle concentrations. Specifically, at Temperatures between 5.4 and 6.8°C, particle concentrations averaged between 0.33 and 0.39 µg/m 3 , whereas at Temperatures between 26 and 28°C, concentrations increased to over 0.70 µg/m 3 . Under Temperature conditions of 5–7°C, particle concentrations were at their lowest, averaging 0.33–0.39 µg/m 3 . In contrast, at Temperatures above 25°C, concentrations reached their highest levels, exceeding 0.70 µg/m 3 . These findings suggest that rising Temperature can enhance particulate matter through multiple mechanisms, including intensified photochemical reactions, increased secondary particle formation from volatile organic compounds, and reduced relative humidity. Examination of Temperature and 0.4 micrometer particulate matter data in Tehran revealed a significant relationship between the two variables. During the sampling period, ambient Temperatures ranged from 5.4 to 28.2°C, while particle concentrations varied between 0.33 and 0.70 µg/m 3 .Trend analysis indicates that Temperature increases are generally associated with higher particle concentrations. This pattern suggests that higher Temperatures may enhance fine particle levels via various mechanisms, such as accelerated photochemical reactions at elevated Temperatures, evaporation and conversion of volatile compounds to secondary particles, and intensified combustion processes from urban sources. Additionally, rising Temperatures are often accompanied by lower relative humidity and greater atmospheric boundary layer stability, which promote particle accumulation near the surface. The results indicate that higher Temperatures, by enhancing photochemical reactions, converting gaseous compounds to secondary particles, and reducing atmospheric dispersion, lead to increased fine particle concentrations. Consequently, the regression model in this study is not only statistically significant but also physically consistent with known particle formation and dispersion processes. Moreover, at moderate Temperatures, such as 13–19°C, particle concentrations averaged between 0.40 and 0.52 µg/m 3 . This suggests that mild climatic conditions, with better ventilation and atmospheric mixing, partially prevent excessive particle accumulation. Overall, these results indicate that Temperature is a key variable influencing 0.4 micrometer particulate concentrations in Tehran and can affect air quality both directly and indirectly through changes in atmospheric physical and chemical processes. These findings align with similar studies in other major cities worldwide, which report higher fine particle concentrations under elevated Temperature conditions. Therefore, considering the role of Temperature and other climatic parameters in air quality monitoring and management is essential especially in megacities like Tehran, where multiple combustion sources and unique topographical features create conditions favorable for increased particle concentrations. To quantitatively analyze the relationship between ambient Temperature and particulate matter concentration, simple linear regression was employed. In this model, Temperature was considered the independent variable, and particle concentration was the dependent variable. The results showed that with each one degree increase in Temperature, particle concentration increased by approximately 0.013 mg/m 3 . The correlation coefficient (R = 0.90) indicates a very strong relationship between the two variables, and the coefficient of determination (R 2 = 0.81) shows that over 81% of the variations in particle concentration are explained by Temperature. Temperature increase is generally associated with intensified photochemical reactions, secondary pollutant formation, conversion of volatile organic compounds into fine particles, reduced relative humidity, and atmospheric stability processes that, in the megacity of Tehran, have greater impact due to the high density of combustion sources and ventilation limitations caused by topographic conditions. Data analysis also revealed that at low Temperatures (5–7°C), particle concentrations were at their minimum (0.33–0.39 µg/m 3 ), whereas at Temperatures above 25°C, concentrations reached their maximum levels (around 0.7 µg/m 3 ). This upward trend aligns closely with the regression equation and the obtained coefficients. Overall, the results indicate that Temperature is one of the key parameters influencing variations in 0.4 µm particulate matter in the city and can serve as a predictive indicator in air quality models. The simultaneous analysis of 0.4 µm particle concentrations and wind speed in Tehran shows a clear inverse pattern between these two variables. Data indicate that during periods of lower wind speed, particularly in the range of 11–14 m/s, fine particle concentrations are at their highest. For example, at a wind speed of 11 m/s, particle concentration was approximately 0.59 µg/m 3 , while at 13 m/s, concentrations varied between 0.35 and 0.63 µg/m 3 . This suggests that under calmer conditions, the natural atmospheric ventilation capacity is reduced, and fine particles remain suspended in the atmosphere for longer periods. Conversely, at higher wind speeds, particularly in the range of 17–19 m/s, particle concentrations decrease compared to lower wind speeds. For instance, at 19 m/s, particle concentration was about 0.58 µg/m 3 , which is lower than the 0.7 µg/m 3 observed at lower wind speeds, indicating the dispersive role of wind. This pattern shows that wind, by enhancing atmospheric turbulence and promoting both horizontal and vertical transport of particles, dilutes and reduces particle density in the lower atmospheric layers. However, this relationship is not entirely linear. At some points, increased wind speed coincided with a relative rise in particle concentrations for example, at 13 m/s, a concentration of 0.63 µg/m 3 was observed. These conditions likely result from the displacement and transport of secondary particles from other areas into the urban domain. In other words, in addition to its dispersive property, wind can carry pollutants from external sources. This phenomenon is particularly relevant in Tehran, which is exposed to wind currents from the eastern and southern desert regions, potentially causing temporary increases in particle concentrations. Overall, the results indicate that wind speed is one of the key factors influencing variations in fine particle concentrations in Tehran. Under low wind conditions, the accumulation of pollutants intensifies, leading to higher particle concentrations. However, at higher wind speeds, the effects of ventilation and dispersion dominate, resulting in a reduction in particle density. This analysis highlights the importance of considering wind patterns in air quality modeling and emphasizes that a proper understanding of the dual role of wind (dispersion versus transport of particles) is essential for explaining the behavior of suspended particles at the urban scale. As shown in Fig. 5 , the overall relationship between wind speed and the concentration of 0.4 µm particles in Tehran tends to be inverse; that is, particle concentration generally decreases with increasing wind speed. Nevertheless, the scattered data points indicate that particle transport from external sources or local variations can cause slight increases in concentration at certain wind speeds. The results of the Pearson correlation coefficient calculation between wind speed and particle concentration showed an r value of 0.26 and a p value of 0.41. These values indicate that there is no statistically significant relationship between wind speed and particle concentration, as the correlation coefficient is low and the p-value is greater than 0.05. In other words, the available data do not suggest that wind has a pronounced or significant effect on increasing or decreasing particle concentrations. However, a weak positive trend is observed, likely associated with short term and episodic variations in particle emission sources. The scatter plot analysis indicated that the data were dispersed, and no strong linear trend was observed between wind speed and particle concentration. Moreover, the plotted linear regression line was nearly flat with a slight slope, confirming a weak correlation. Therefore, statistical analysis suggests that the concentration of 0.4 µm particles in the studied area is influenced by multiple environmental factors, and wind speed alone does not play a decisive role. The data dispersion and low correlation coefficient likely reflect the simultaneous effects of local particle emission sources (such as traffic, construction, and industrial activities), short term meteorological conditions, and atmospheric stability. Correlation analysis of the data shows that the concentration of suspended particles has a strong negative relationship with humidity (-0.856) and a strong positive relationship with temperature (0.901), that is, increasing humidity causes a decrease and increasing temperature causes an increase in particle concentration, while the effect of wind is very weak (0.171). Also, a very strong negative correlation is observed between humidity and temperature (-0.955), a moderate negative correlation is observed between humidity and wind (-0.535), and a moderate positive correlation is observed between temperature and wind (0.426). These results indicate that temperature and humidity are the most important factors affecting the concentration of suspended particles, and wind plays a lesser role (Table 1 ) Table 1 Correlation matrix of average concentration and atmospheric parameters Parameter Mean PM Humidity Wind Temp Mean_PM 1 -0.856 0.171 0.901 Humidity -0.856 1 -0.535 -0.955 Wind 0.171 -0.535 1 0.426 Temp 0.901 -0.955 0.426 1 Chemical and Morphological Composition of Particles The study of the chemical composition and morphology of suspended particles collected using SEM revealed that they were predominantly irregular in shape and composed of both metallic and non metallic elements, such as zinc, titanium, iron, carbon, aluminum, and silicon. These chemical compositions were mostly observed in samples collected at station St3. An example of SEM images is presented in Fig. 6 . These particles can originate from diverse sources, including construction activities, urban transportation, and biomass burning in agricultural practices, natural dust, and sand and gravel workshops. From a mineralogical perspective, the majority of these particles consisted of feldspar (calcium, silicon, and aluminum) and clay (aluminum, iron, and silicon), naturally derived from the Earth's crust. However, processes such as the erosion of construction materials and dust from vehicular traffic also contribute significantly to particle emissions. In addition to the main components, small amounts of magnesium, sodium, titanium, and zinc were detected in aluminosilicate particles. In the collected samples, particles smaller than 0.4 µm exhibited irregular, spherical, rod like, and crystalline shapes. These particles were rich in compounds containing Ca, K, and Zn alongside elements such as Si, Al, Ti, and O. Particles with sizes between 0.4 and 2.5 µm were mainly spherical, clustered, and plate like, and their composition, in addition to K, Ca, Cl, and Fe, included significant amounts of Al, Mg, and Na. In the studied areas, particles larger than 0.4 µm were also present in spherical, clustered, and irregular forms, with the main components being Al, Fe, K, Si, Ca, Mg, Ti, and O. Analysis of SEM results for suspended particles at the sampling stations showed that the particle composition is significantly influenced by extensive fossil fuel consumption and high vehicle traffic. Fine particles were mostly found in clustered and irregular forms, enriched with elements such as O, Zn, Mg, Fe, K, Si, and Na, while particles larger than 0.4 µm contained compounds including Ti, Mg, and Pb. The presence of mineral phases such as CaCO₃ and crustal particles enriched in Na was also observed. The results indicated that suspended particles in Tehran have a dual origin: internal sources, including industries, workshops, and fossil fuel–dependent transportation, and external sources, such as dust storms, biomass burning, and sand and gravel factory activities. These particles ranged from nanometers to several tens of micrometers, with smaller particles undergoing aggregation and collisions in the atmosphere, eventually forming larger particles that settle. Irregularly shaped particles were mainly associated with combustion and mobile sources, whereas spherical and regular particles were more likely of mineral origin or derived from biomass burning. In general, finer particles primarily result from fuel combustion in industries and urban transportation, while coarser particles originate from road dust, construction, and industrial activities. Given the rapid urban growth, increasing mobile sources, and specific meteorological conditions in Tehran, strategic management of pollutant control is essential a goal that cannot be achieved solely through improving fuel and vehicle quality but requires comprehensive approaches in developing public transportation and reducing combustion sources. One of the critical issues regarding suspended particles in urban areas is their penetration into residential, office, and educational buildings. From a health perspective, continuous exposure to suspended particles, especially fine particles, can pose serious risks to residents, particularly children, the elderly, pregnant women, and individuals with underlying cardiovascular or respiratory conditions. Due to their extremely small size, these particles can enter the respiratory system and even penetrate the bloodstream [ 30 ]. Considering that the World Health Organization has classified outdoor air pollution as a Group 1 carcinogen, proper planning to reduce air pollutants in Tehran’s metropolitan area and to prevent their intrusion into indoor environments is essential. Assessment of the Future Air Pollution Status in Tehran Current Situation (Baseline Scenario) Analysis of the results shows that: The concentration of particulate matter increases during the warm seasons (July to October). The highest concentration occurs in September (0.70 µg/m 3 ) and the lowest in January - February (about 0.33 µg/m 3 ). Low humidity and high temperature are the main factors intensifying pollution. Central urban stations (similar to St2 and St3) record the highest values, indicating the effects of traffic and accumulation of local emission sources. Based on data and surveys, the key variables affecting the concentration of particles in the atmosphere of Tehran are shown in Table 2 . Table 2 Important variables affecting particle concentration in the atmosphere of Tehran city Category Key Factors Climatic Air temperature, relative humidity, wind speed and direction, atmospheric stability Urban Building density, traffic, combustion sources, green space Policy and Management Pollution reduction programs, clean transport, fuel control Technological Electric vehicles, urban ventilation and filtration systems Social Changes in fuel consumption patterns, public awareness, population migration Given the current situation in Tehran, four scenarios are predicted for the future, which are: Scenario 1 Green and Smart Tehran (Sustainable and Low Carbon) Pollution reduction policies are effectively implemented (clean transport, green spaces, renewable energy). Although summer temperatures rise, management of the urban heat island reduces particle levels. The average concentration of 0.4 µm particles is predicted to decrease by about 30% (≈ 0.35 µg/m 3 ). Outcome Improved air quality index and more clean air days. Scenario 2 Warming and Climatic Stress (Seasonal Pollution Increase) Annual mean temperature rises by 2–3°C and humidity decreases by 10%. Local winds weaken, reducing natural city ventilation. Particle concentration, especially in summer, increases up to 0.8 µg/m 3 . More pollution-alert days, especially in July - September. Outcome Intensified health risks; urgent need for climate adaptation mechanisms. Scenario 3 Ineffective Management and Chronic Pollution Intensification Control policies are poorly implemented; old vehicles increase. Population growth and construction expansion restrict urban airflow. Higher temperatures and lower humidity ⇒ smaller particles remain suspended longer. Annual mean concentration rises to about 1 µg/m 3 or higher. Outcome Urban health crisis, increased healthcare costs, and climate-driven migration from central areas. Scenario 4 Technological Transformation and Urban Innovation 60% of vehicles replaced by electric ones. Smart monitoring network with rapid pollution response. Use of reflective and cooling materials in urban construction. Combined actions lead to a 40% reduction in particles smaller than 1 µm. Outcome Air quality in dense urban areas approaches WHO acceptable levels. Based on Table 3 provided, the trend of changes in pollution and environmental conditions in different scenarios of Tehran can be analyzed. In the current situation, the average of suspended particles is 0.52 µg/m 3 and the air quality is at a moderate level, with health impacts also assessed as moderate, and the long-term sustainability of environmental conditions is also moderate. In scenario 1, by implementing pollution reduction policies and sustainable urban measures, the average of particles is reduced to 0.35 µg/m 3 and the air quality is improved to a good level; the health impact is reduced and the long term sustainability is increased. Scenario 2, which reflects the effects of warming and reduced humidity, increases the average of particles to 0.80 µg/m 3 and the air quality becomes unhealthy, with a high health impact and low sustainability. Scenario 3, which results from inefficient management and the intensification of chronic pollution, creates a critical situation; suspended particles reach 1 µg/m 3 , the air quality is very unhealthy, health is severely threatened, and environmental sustainability is greatly reduced. In contrast, Scenario 4, by leveraging technological innovations and replacing electric vehicles, average particulate matter is reduced to 0.30 µg/m 3 , air quality reaches good levels, health impacts are low, and long-term sustainability is high. Overall, this table shows that management policies and technology can play a key role in reducing pollution and improving urban health and sustainability. Table 3 Comparative analysis of predicted scenarios Indicator Baseline Scenario 1 Scenario 2 Scenario 3 Scenario 4 Mean PM (µg/m 3 ) 0.52 0.35 0.8 1 0.3 Mean Temperature (°C) 17 18 20 21 18 Relative Humidity (%) 30 35 20 18 33 Air Quality Moderate Good Unhealthy Very Unhealthy Good Health Impact Moderate Low High Critical Low Long Term Sustainability Moderate High Low Very Low High To effectively address air pollution in Tehran, a set of integrated policy measures is essential. First, simultaneous monitoring of particulate matter alongside key climatic parameters will enable dynamic modeling and more accurate prediction of pollution events. Second, optimizing urban design through initiatives like an Urban Cooling Plan can help mitigate the urban heat island effect, reducing temperature-related pollution peaks. Third, developing advanced air quality forecasting systems based on machine learning will support proactive management and timely public advisories. Finally, strengthening the city’s resilience to extreme climate scenarios will ensure long-term sustainability, safeguarding public health and maintaining livable urban conditions despite future environmental challenges. 4 Conclusion The results indicate that particulate matter (PM) concentrations in Tehran follow a distinct seasonal pattern, with the lowest levels observed in winter and the highest in summer. These findings highlight the necessity of managing pollutant sources according to seasonal conditions. In particular, focusing control policies during the summer can help reduce citizens’ exposure to air pollution. Monitoring of 0.4 µm particles at four stations across Tehran showed a clear seasonal fluctuation pattern, with the lowest concentration in winter (0.33 µg/m 3 in January) and the highest in summer (0.70 µg/m 3 in August and September). These variations are primarily influenced by meteorological conditions (precipitation, humidity, temperature, temperature inversion) and local sources (traffic, construction activities, and industries). The inverse relationship of particle concentration with relative humidity and wind speed, as well as the direct relationship with increasing temperature, demonstrates the key role of climatic variables in pollutant dispersion or accumulation. Spatially, high traffic stations recorded the highest concentrations, while stations located away from main roads recorded the lowest. Chemical and morphological analyses of particles indicated that their composition originates from dual natural (dust, minerals) and anthropogenic (fossil fuel combustion, construction, transportation) sources. Given the high toxicity of fine particles, even at low concentrations, these findings underscore the importance of air quality management, control of mobile pollutant sources, and the development of comprehensive pollution reduction policies in Tehran. Considering the substantial production and emission of particulate matter in the open environment, the physical conditions of buildings throughout the city, and the increasing energy imbalances in recent years, having a structured program for managing and controlling this issue has become critical. Achieving favorable outcomes depends on proper implementation of such programs and public cooperation. Ethics approval Not applicable. Declarations Ethics approval Not applicable. Consent to participate Not applicable. Consent to publish Not applicable. Availability of data and material The authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files. Should any raw data files be needed in another format they are available from the corresponding author upon reasonable request. Competing Interests The author declare no Competing Interests. Funding This research project was carried out under the author's grant at Kharazmi University. Author Contributions The author solely contributed to all stages of the work, including material preparation, data collection, and development of graphical illustrations, data analysis, and drafting of the manuscript. Clinical trial number Not applicable. 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Environmental health perspectives , 121(10), 1174–1178. https://doi.org/10.1289/ehp.1206398 Cassee FR, Muijser H, Duistermaat E, Freijer JJ, Geerse KB, Marijnissen JC, Arts JH. Particle size-dependent total mass deposition in lungs determines inhalation toxicity of cadmium chloride aerosols in rats. Application of a multiple path dosimetry model. Arch Toxicol. 2002;76(5):277–86. 10.1007/s00204-002-0344-8 . World Health Organization. Outdoor Air Pollution a Leading Environmental Cause of cancer Deaths. Cancer IAfRo. World Health Organization, Lyon. Press release; 2013. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":203676,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical location and sampling points\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/c37ed355cbb05b9dec6ffc87.jpeg"},{"id":97472415,"identity":"6fce901d-fce1-4d9a-83a3-b74c456fa9c5","added_by":"auto","created_at":"2025-12-04 17:54:17","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":199548,"visible":true,"origin":"","legend":"\u003cp\u003eResults of the concentration of suspended particles smaller than 0.4 micrometers at the sampling stations\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/3b9af8a077939ffef0351ba5.jpeg"},{"id":97472404,"identity":"0380e40d-98a8-406a-9038-7e14f0092581","added_by":"auto","created_at":"2025-12-04 17:54:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48074,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly variations in particle concentration relative to relative humidity\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/a5474c48df21f00dc4c63ba6.png"},{"id":97472407,"identity":"fd76c6c6-0256-4ad4-b47f-3c70078f9f9c","added_by":"auto","created_at":"2025-12-04 17:54:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49519,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly variations in particle concentration relative to Temperature\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/1e611c7ae58e74c20a060b88.png"},{"id":97472408,"identity":"035215a3-4460-4f8f-abb6-f28bf24df178","added_by":"auto","created_at":"2025-12-04 17:54:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":48035,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly variations in particle concentration relative to wind speed\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/e2ea51b9a90d5c66f5a79345.png"},{"id":97472409,"identity":"66f97a98-289e-4351-8fb3-cd2eb8914d24","added_by":"auto","created_at":"2025-12-04 17:54:17","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":227468,"visible":true,"origin":"","legend":"\u003cp\u003eImage of sources of suspended particles in the space of residential buildings.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/2e05beb1bf86e944141706d7.jpeg"},{"id":99796877,"identity":"c651f148-c415-4526-bad8-eb41b1f4178a","added_by":"auto","created_at":"2026-01-08 13:43:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1409993,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8207062/v1/351a70a3-e13f-498f-b2f2-072c68485995.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Urban Air Quality Assessment: Variability and Behavior of Fine Particles under Tehran’s Climatic Conditions","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eSuspended particles in the atmosphere exhibit a wide range of sizes and chemical compositions depending on their pollution sources. These particles can originate from natural sources or human activities. Among natural sources, phenomena such as volcanic eruptions, large scale forest and grassland fires, local storms, and the dispersion of mineral materials are considered the main contributors to particle emissions. In contrast, human activities play a significant role in increasing the concentration of suspended particles. Processes such as the combustion of fossil fuels, biomass burning, vehicular traffic, tire wear and abrasion during braking, aviation and maritime transportation, construction and infrastructure projects, the use of wood burning stoves, and the operation of building heating and cooling systems are also important sources of atmospheric particulate emissions [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A significant relationship has been observed atmospheric suspended particles and various diseases, including respiratory and cardiovascular conditions [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Also, fluctuations in the concentration of particulate matter with diameters less than 2.5 micrometers (PM\u003csub\u003e2.5\u003c/sub\u003e) in the air are significantly associated with changes in mortality rates and the daily incidence of health complications in human populations [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Particles smaller than 2.5 micrometers have the greatest impact on human health because they can penetrate the deepest parts of the respiratory system and lungs, causing harmful effects [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although the health effects of air pollutant exposure in adults are considerable, children and individuals with pre-existing conditions are significantly more vulnerable and at higher risk. Therefore, exposure to air pollutants represents a major public health and environmental concern [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOne of the sensitive issues regarding particulate matter is the harmful impact of fine particles on human health. Due to their ability to penetrate deep into the respiratory system, prolonged exposure to these particles poses serious health concerns. Such exposure has been associated with a range of adverse health effects, including respiratory disorders, cardiovascular problems, brain inflammation and neurological damage, digestive disturbances, and an increased risk of developing diabetes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, assessing the concentration of these particles can help prevent health risks to humans. The process of industrialization, especially in developing countries, is one of the main factors contributing to environmental damage. One of the significant consequences of this process is air pollution, which is listed among the top ten serious environmental health challenges and is directly linked to increased global mortality [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Research indicates that this issue results from a combination of factors, including the growth in private vehicle use, aging vehicles, consumption of low quality fuels, poor road conditions, and insufficient efficient urban infrastructure. This complexity makes air pollution management feasible only through the enforcement of strict environmental regulations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Although the detrimental effects of air pollutants are most evident in urban areas, this phenomenon is not limited to cities; pollutants can be transported over long distances and even affect background pollution on a hemispheric scale [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, air pollution should be considered not merely a local concern but a global and long term issue [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. According to the Environmental Protection Agency, pollutants from fuel combustion are classified into two groups: criteria pollutants and non criteria pollutants.\u003c/p\u003e\u003cp\u003eIn recent years, Tehran has become one of the cities with the highest levels of air pollution in the country due to rapid urban expansion, increased industrial activities, and climate changes. The rise in atmospheric particulate matter is considered one of the most significant environmental and health challenges for the residents of this metropolis. Studies indicate that a large portion of these particles originates from human activities, including motor vehicle traffic, industrial operations, and local dust storms, while a share of the particulate matter is also attributable to natural phenomena such as local dust storms [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Atmospheric stability has increased personal vehicle traffic within the city, and the construction of high rise buildings in recent years has raised particulate matter concentrations to highly hazardous levels, severely reducing air quality [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The presence of fine particle sources across the city has elevated their concentrations to dangerous levels. In this study, we aim to investigate the concentration of fine particles (0.4 micrometers) over a one year period in Tehran and examine their variations with respect to climatic parameters. The diverse climatic conditions in Tehran, along with atmospheric stability during the cold seasons, can prolong particle residence times during the day and potentially increase long term human exposure.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Sampling Station Locations\u003c/h2\u003e\u003cp\u003eSuspended particulate matter is one of the most significant atmospheric pollutants, with adverse effects on human health and environmental quality. Due to its high population density, heavy traffic, and construction activities, Tehran is exposed to elevated levels of air pollution. Examining seasonal variations in particulate matter concentrations can help identify major sources and inform the design of effective control policies. Climatically, Tehran is located in a semi arid region, experiencing cold and humid winters and hot, dry summers. The prevailing winds come from the west and northwest, but their speed decreases upon encountering the Alborz Mountains. On many days of the year, weak airflows and stable weather conditions prevail. This atmospheric stability, especially during the colder months, increases the occurrence of temperature inversions in the lower layers of the atmosphere, leading to the accumulation of pollutants and suspended particles. In addition to natural factors, uneven urban development, population growth, and increased pollutant sources including industries, vehicles, power plants, and heating systems have reduced the environment's self purification capacity. This trend has resulted in chronic air pollution crises, which in recent years have even led to widespread urban shutdowns. Therefore, Tehran\u0026rsquo;s geographical location and natural characteristics not only provide the environmental context but also serve as determining factors in the intensity of air pollution. Considering the geographical position and regional characteristics, as well as the prevailing wind direction, four points were selected as sampling stations. The study area and the distribution of sampling stations are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sampling\u003c/h2\u003e\u003cp\u003eThis study was conducted from September 2021 to August 2022 in Tehran, the capital of Iran. In selecting the sampling locations, parameters such as distance from the main roads, prevailing wind direction, urban traffic, point source pollutants, and pedestrian activity were considered. The average sampling height above ground level was 13 meters, and the average duration of each sampling session was 6 hours. Additionally, local storms and atmospheric stability were taken into account when choosing sampling days to assess the influence of these conditions on the sample quantities. To collect particulate matter, an Andersen cascade impactor was used. This device operates at a constant flow rate of 28.3 liters per minute, maintained by a continuous vacuum pump, and consists of eight aluminum stages [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this system, the airflow directs suspended particles along curved paths, separating and collecting them at each stage according to their aerodynamic size. Based on this mechanism, particles settle on metallic plates according to their aerodynamic diameter. In the last stage of the sampler, a backup layer is placed, where particles with a diameter of 0.4 micrometers and smaller are captured. The particle concentration is generally determined by weighing the collected particles or by counting them, which allows for quantitative analysis of particle composition and distribution in the environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In each sampling session, the weight of the backup filter was measured before and after particle collection, and the difference between these two values was considered as the particle concentration.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results and discussion","content":"\u003cp\u003eThe results obtained from the measurement of 0.4 \u0026micro;m particulate matter at the four stations are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. According to these results, the average concentration of these particles reached its minimum in January at 0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, indicating more favorable conditions during the winter season. The maximum concentration was observed in August and September at 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, reflecting higher particle concentrations in summer. Overall, the general trend showed an increase from winter to summer, with a relative decrease in autumn. The observed pattern indicates the significant role of meteorological conditions in the dispersion and accumulation of particulate matter. During winter and the colder months, precipitation and atmospheric cleansing reduce particle concentrations, whereas in summer, due to atmospheric stability, lower rainfall, and increased pollutant sources such as dust, construction activities, and vehicular traffic, particle concentrations reach their peak. In autumn, the onset of seasonal precipitation leads to a gradual decrease in concentrations. According to previous studies and the results of this research, the occurrence of temperature inversion in late autumn and early winter is one of the reasons for the increased concentration of particulate matter in Tehran, particularly for particles smaller than 2.5 \u0026micro;m. Although fine particles constitute a smaller fraction of the total particulate matter by mass, even a slight increase in their concentration can pose health risks to humans. Evidence suggests that the toxicity of fine particles per unit mass increases as particle size decreases [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The results indicate that the temporal variations of 0.4 \u0026micro;m particle concentrations in the study area follow both seasonal and spatial patterns over the course of a year.\u003c/p\u003e\u003cp\u003eIn general, the annual mean concentration of particles varied from 0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in January to 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in September. These variations indicate higher particle concentrations during the warm season (July to September) and lower concentrations during the cold season (January and February). This pattern can be attributed to a combination of climatic and urban factors. During the warmer months, increased Temperatures, intensified photochemical processes, and weaker atmospheric stability contribute to higher fine particle concentrations, whereas during the colder months, precipitation, higher relative humidity, and occasional Temperature inversions lead to relatively lower concentrations. Spatially, stations St2 and St3 generally exhibited the highest concentrations for most months. The maximum values for these stations were recorded in August and September at 0.85 and 0.80 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, respectively. This may indicate the influence of local pollutant sources such as heavy traffic, construction activities, or proximity to urban industries. Considering the locations of these two stations, their proximity to major city streets and high traffic volumes, along with the aging of urban transport fleets, likely contributed to increased particle concentrations in these areas. In contrast, station St4 recorded the lowest 0.4 \u0026micro;m particulate matter concentrations for most months. In January and February, the concentrations were 0.23 and 0.27 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, respectively, possibly due to its greater distance from high traffic roads or better atmospheric ventilation in that area. This range of variations reflects a distinct seasonal pattern in particle concentration fluctuations, with the lowest values in the cold months (January and February) and the highest in the warm months (July to September). Such a pattern can be attributed to the effects of climatic conditions on pollutant dispersion and stability. During the cold months, precipitation and higher relative humidity wash out the atmosphere, reducing particulate matter, whereas during the warm months, higher Temperatures, local dust storms, intensified photochemical processes, and increased secondary particle formation lead to elevated fine particle concentrations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe observed pattern in the data indicates that Tehran exhibits spatial heterogeneity in fine particle pollution, and this heterogeneity can play an important role in assessing health risks and developing pollution reduction policies. Furthermore, the significant increase in particle concentration during the warm season may serve as a warning for public health, particularly for vulnerable groups such as children, the elderly, and patients with respiratory conditions. Given that this monitoring station is located in the eastern part of Tehran and considering the prevailing wind direction, there is consistently greater concern about the accumulation of fine particles in this area compared to other parts of the city. A simultaneous examination of the concentration of suspended particles with an average size of 0.4 \u0026micro;m and relative humidity variations in Tehran shows an inverse relationship between these two parameters. Specifically, the data indicate that when relative humidity is low (between 16 and 22%), particle concentrations reach their maximum. For example, at 16% humidity, particle concentration is approximately 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, and at 22% humidity, the concentration ranges from 0.58 to 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. Conversely, under higher humidity conditions, particle concentration decreases; for instance, at 48.5% humidity, the concentration reaches its minimum value of around 0.35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. This pattern suggests that under low humidity conditions, particle stability and residence time in the atmosphere are higher, while natural removal mechanisms such as condensation and precipitation are less effective. In addition, under such conditions, increased dust from dry air and resuspension of particles from soil and urban surfaces can contribute to higher fine particle concentrations.\u003c/p\u003e\u003cp\u003eThe opposite occurs under high humidity conditions. When relative humidity is high, particles tend to absorb water due to hygroscopic growth and rapidly transform into larger particles, increasing their likelihood of deposition. High humidity also raises the possibility of precipitation or dew, which washes out particles and reduces their atmospheric concentration. The data indicate that low relative humidity is one of the conditions facilitating increased 0.4 \u0026micro;m particle concentrations in Tehran. This is particularly important during hot and dry seasons, such as summer, when rising Temperatures and decreasing humidity, combined with atmospheric stability and urban dust resuspension, can lead to a significant increase in particulate matter load. Therefore, in air quality management, attention to humidity conditions alongside other climatic variables is essential for more accurately predicting and controlling fine particle fluctuations. The results also show that at intermediate humidity levels of approximately 31.5 to 39.5%, particle concentrations fluctuated between 0.40 and 0.53 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. This indicates that relative humidity alone is not the sole determining factor; other environmental parameters, such as wind speed and direction, Temperature, and traffic intensity, also play a significant role in particle concentrations alongside humidity. A linear regression model based on the monitoring data demonstrated a relatively strong inverse relationship between relative humidity and suspended particle concentration. According to the results, for each 1% increase in relative humidity, the particle concentration decreases by an average of approximately 0.01 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, while the intercept of the Eq.\u0026nbsp;(0.831 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) represents the approximate particle concentration under near zero humidity conditions. Moreover, the coefficient of determination (R\u0026sup2; = 0.73) indicates that about 73% of the variation in particle concentration can be explained by changes in relative humidity. This finding aligns with existing scientific understanding: under low humidity, particle residence time is longer and concentrations are higher, whereas increasing humidity leads to hygroscopic growth and deposition, reducing concentrations. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the relationship between particle concentration and relative humidity over the study period. As shown in the figure, under low humidity conditions (below 20%), particle concentration reaches its maximum (around 0.7 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), while at higher humidity levels (above 45%), concentrations drop below 0.35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. These results indicate that low relative humidity can create conditions conducive to longer particle residence times and higher atmospheric concentrations. Conversely, increasing relative humidity promotes particle hygroscopic growth and enhances the likelihood of deposition or washout, leading to decreased concentrations. Overall, this analysis confirms that relative humidity is a key factor in variations of fine particle concentrations in Tehran and, along with other climatic variables (such as Temperature, wind, and air pressure), can be used in predicting and managing air quality.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, illustrates the trend of 0.4 micrometer particle concentrations relative to Temperature over the study period. Analysis of the environmental Temperature data and particulate matter concentrations in the region indicates that Temperature variations play a significant role in particle concentration fluctuations. In general, increases in Temperature were associated with an upward trend in particle concentrations. Specifically, at Temperatures between 5.4 and 6.8\u0026deg;C, particle concentrations averaged between 0.33 and 0.39 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, whereas at Temperatures between 26 and 28\u0026deg;C, concentrations increased to over 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. Under Temperature conditions of 5\u0026ndash;7\u0026deg;C, particle concentrations were at their lowest, averaging 0.33\u0026ndash;0.39 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. In contrast, at Temperatures above 25\u0026deg;C, concentrations reached their highest levels, exceeding 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. These findings suggest that rising Temperature can enhance particulate matter through multiple mechanisms, including intensified photochemical reactions, increased secondary particle formation from volatile organic compounds, and reduced relative humidity. Examination of Temperature and 0.4 micrometer particulate matter data in Tehran revealed a significant relationship between the two variables. During the sampling period, ambient Temperatures ranged from 5.4 to 28.2\u0026deg;C, while particle concentrations varied between 0.33 and 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e.Trend analysis indicates that Temperature increases are generally associated with higher particle concentrations. This pattern suggests that higher Temperatures may enhance fine particle levels via various mechanisms, such as accelerated photochemical reactions at elevated Temperatures, evaporation and conversion of volatile compounds to secondary particles, and intensified combustion processes from urban sources. Additionally, rising Temperatures are often accompanied by lower relative humidity and greater atmospheric boundary layer stability, which promote particle accumulation near the surface. The results indicate that higher Temperatures, by enhancing photochemical reactions, converting gaseous compounds to secondary particles, and reducing atmospheric dispersion, lead to increased fine particle concentrations. Consequently, the regression model in this study is not only statistically significant but also physically consistent with known particle formation and dispersion processes. Moreover, at moderate Temperatures, such as 13\u0026ndash;19\u0026deg;C, particle concentrations averaged between 0.40 and 0.52 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. This suggests that mild climatic conditions, with better ventilation and atmospheric mixing, partially prevent excessive particle accumulation. Overall, these results indicate that Temperature is a key variable influencing 0.4 micrometer particulate concentrations in Tehran and can affect air quality both directly and indirectly through changes in atmospheric physical and chemical processes. These findings align with similar studies in other major cities worldwide, which report higher fine particle concentrations under elevated Temperature conditions. Therefore, considering the role of Temperature and other climatic parameters in air quality monitoring and management is essential especially in megacities like Tehran, where multiple combustion sources and unique topographical features create conditions favorable for increased particle concentrations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo quantitatively analyze the relationship between ambient Temperature and particulate matter concentration, simple linear regression was employed. In this model, Temperature was considered the independent variable, and particle concentration was the dependent variable. The results showed that with each one degree increase in Temperature, particle concentration increased by approximately 0.013 mg/m\u003csup\u003e3\u003c/sup\u003e. The correlation coefficient (R\u0026thinsp;=\u0026thinsp;0.90) indicates a very strong relationship between the two variables, and the coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.81) shows that over 81% of the variations in particle concentration are explained by Temperature. Temperature increase is generally associated with intensified photochemical reactions, secondary pollutant formation, conversion of volatile organic compounds into fine particles, reduced relative humidity, and atmospheric stability processes that, in the megacity of Tehran, have greater impact due to the high density of combustion sources and ventilation limitations caused by topographic conditions. Data analysis also revealed that at low Temperatures (5\u0026ndash;7\u0026deg;C), particle concentrations were at their minimum (0.33\u0026ndash;0.39 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), whereas at Temperatures above 25\u0026deg;C, concentrations reached their maximum levels (around 0.7 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). This upward trend aligns closely with the regression equation and the obtained coefficients. Overall, the results indicate that Temperature is one of the key parameters influencing variations in 0.4 \u0026micro;m particulate matter in the city and can serve as a predictive indicator in air quality models. The simultaneous analysis of 0.4 \u0026micro;m particle concentrations and wind speed in Tehran shows a clear inverse pattern between these two variables. Data indicate that during periods of lower wind speed, particularly in the range of 11\u0026ndash;14 m/s, fine particle concentrations are at their highest. For example, at a wind speed of 11 m/s, particle concentration was approximately 0.59 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, while at 13 m/s, concentrations varied between 0.35 and 0.63 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. This suggests that under calmer conditions, the natural atmospheric ventilation capacity is reduced, and fine particles remain suspended in the atmosphere for longer periods.\u003c/p\u003e\u003cp\u003eConversely, at higher wind speeds, particularly in the range of 17\u0026ndash;19 m/s, particle concentrations decrease compared to lower wind speeds. For instance, at 19 m/s, particle concentration was about 0.58 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, which is lower than the 0.7 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e observed at lower wind speeds, indicating the dispersive role of wind. This pattern shows that wind, by enhancing atmospheric turbulence and promoting both horizontal and vertical transport of particles, dilutes and reduces particle density in the lower atmospheric layers. However, this relationship is not entirely linear. At some points, increased wind speed coincided with a relative rise in particle concentrations for example, at 13 m/s, a concentration of 0.63 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e was observed. These conditions likely result from the displacement and transport of secondary particles from other areas into the urban domain. In other words, in addition to its dispersive property, wind can carry pollutants from external sources. This phenomenon is particularly relevant in Tehran, which is exposed to wind currents from the eastern and southern desert regions, potentially causing temporary increases in particle concentrations. Overall, the results indicate that wind speed is one of the key factors influencing variations in fine particle concentrations in Tehran. Under low wind conditions, the accumulation of pollutants intensifies, leading to higher particle concentrations. However, at higher wind speeds, the effects of ventilation and dispersion dominate, resulting in a reduction in particle density. This analysis highlights the importance of considering wind patterns in air quality modeling and emphasizes that a proper understanding of the dual role of wind (dispersion versus transport of particles) is essential for explaining the behavior of suspended particles at the urban scale. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the overall relationship between wind speed and the concentration of 0.4 \u0026micro;m particles in Tehran tends to be inverse; that is, particle concentration generally decreases with increasing wind speed. Nevertheless, the scattered data points indicate that particle transport from external sources or local variations can cause slight increases in concentration at certain wind speeds. The results of the Pearson correlation coefficient calculation between wind speed and particle concentration showed an r value of 0.26 and a p value of 0.41. These values indicate that there is no statistically significant relationship between wind speed and particle concentration, as the correlation coefficient is low and the p-value is greater than 0.05. In other words, the available data do not suggest that wind has a pronounced or significant effect on increasing or decreasing particle concentrations. However, a weak positive trend is observed, likely associated with short term and episodic variations in particle emission sources.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe scatter plot analysis indicated that the data were dispersed, and no strong linear trend was observed between wind speed and particle concentration. Moreover, the plotted linear regression line was nearly flat with a slight slope, confirming a weak correlation. Therefore, statistical analysis suggests that the concentration of 0.4 \u0026micro;m particles in the studied area is influenced by multiple environmental factors, and wind speed alone does not play a decisive role. The data dispersion and low correlation coefficient likely reflect the simultaneous effects of local particle emission sources (such as traffic, construction, and industrial activities), short term meteorological conditions, and atmospheric stability. Correlation analysis of the data shows that the concentration of suspended particles has a strong negative relationship with humidity (-0.856) and a strong positive relationship with temperature (0.901), that is, increasing humidity causes a decrease and increasing temperature causes an increase in particle concentration, while the effect of wind is very weak (0.171). Also, a very strong negative correlation is observed between humidity and temperature (-0.955), a moderate negative correlation is observed between humidity and wind (-0.535), and a moderate positive correlation is observed between temperature and wind (0.426). These results indicate that temperature and humidity are the most important factors affecting the concentration of suspended particles, and wind plays a lesser role (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation matrix of average concentration and atmospheric parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean PM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHumidity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWind\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTemp\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean_PM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHumidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.955\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.426\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eChemical and Morphological Composition of Particles\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study of the chemical composition and morphology of suspended particles collected using SEM revealed that they were predominantly irregular in shape and composed of both metallic and non metallic elements, such as zinc, titanium, iron, carbon, aluminum, and silicon. These chemical compositions were mostly observed in samples collected at station St3. An example of SEM images is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. These particles can originate from diverse sources, including construction activities, urban transportation, and biomass burning in agricultural practices, natural dust, and sand and gravel workshops. From a mineralogical perspective, the majority of these particles consisted of feldspar (calcium, silicon, and aluminum) and clay (aluminum, iron, and silicon), naturally derived from the Earth's crust. However, processes such as the erosion of construction materials and dust from vehicular traffic also contribute significantly to particle emissions. In addition to the main components, small amounts of magnesium, sodium, titanium, and zinc were detected in aluminosilicate particles. In the collected samples, particles smaller than 0.4 \u0026micro;m exhibited irregular, spherical, rod like, and crystalline shapes. These particles were rich in compounds containing Ca, K, and Zn alongside elements such as Si, Al, Ti, and O. Particles with sizes between 0.4 and 2.5 \u0026micro;m were mainly spherical, clustered, and plate like, and their composition, in addition to K, Ca, Cl, and Fe, included significant amounts of Al, Mg, and Na. In the studied areas, particles larger than 0.4 \u0026micro;m were also present in spherical, clustered, and irregular forms, with the main components being Al, Fe, K, Si, Ca, Mg, Ti, and O.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of SEM results for suspended particles at the sampling stations showed that the particle composition is significantly influenced by extensive fossil fuel consumption and high vehicle traffic. Fine particles were mostly found in clustered and irregular forms, enriched with elements such as O, Zn, Mg, Fe, K, Si, and Na, while particles larger than 0.4 \u0026micro;m contained compounds including Ti, Mg, and Pb. The presence of mineral phases such as CaCO₃ and crustal particles enriched in Na was also observed. The results indicated that suspended particles in Tehran have a dual origin: internal sources, including industries, workshops, and fossil fuel\u0026ndash;dependent transportation, and external sources, such as dust storms, biomass burning, and sand and gravel factory activities. These particles ranged from nanometers to several tens of micrometers, with smaller particles undergoing aggregation and collisions in the atmosphere, eventually forming larger particles that settle. Irregularly shaped particles were mainly associated with combustion and mobile sources, whereas spherical and regular particles were more likely of mineral origin or derived from biomass burning. In general, finer particles primarily result from fuel combustion in industries and urban transportation, while coarser particles originate from road dust, construction, and industrial activities. Given the rapid urban growth, increasing mobile sources, and specific meteorological conditions in Tehran, strategic management of pollutant control is essential a goal that cannot be achieved solely through improving fuel and vehicle quality but requires comprehensive approaches in developing public transportation and reducing combustion sources.\u003c/p\u003e\u003cp\u003eOne of the critical issues regarding suspended particles in urban areas is their penetration into residential, office, and educational buildings. From a health perspective, continuous exposure to suspended particles, especially fine particles, can pose serious risks to residents, particularly children, the elderly, pregnant women, and individuals with underlying cardiovascular or respiratory conditions. Due to their extremely small size, these particles can enter the respiratory system and even penetrate the bloodstream [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Considering that the World Health Organization has classified outdoor air pollution as a Group 1 carcinogen, proper planning to reduce air pollutants in Tehran\u0026rsquo;s metropolitan area and to prevent their intrusion into indoor environments is essential.\u003c/p\u003e\u003cp\u003eAssessment of the Future Air Pollution Status in Tehran\u003c/p\u003e\u003cp\u003eCurrent Situation (Baseline Scenario)\u003c/p\u003e\u003cp\u003eAnalysis of the results shows that:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe concentration of particulate matter increases during the warm seasons (July to October).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe highest concentration occurs in September (0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) and the lowest in January - February (about 0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLow humidity and high temperature are the main factors intensifying pollution.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCentral urban stations (similar to St2 and St3) record the highest values, indicating the effects of traffic and accumulation of local emission sources.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eBased on data and surveys, the key variables affecting the concentration of particles in the atmosphere of Tehran are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImportant variables affecting particle concentration in the atmosphere of Tehran city\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKey Factors\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClimatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAir temperature, relative humidity, wind speed and direction, atmospheric stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBuilding density, traffic, combustion sources, green space\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolicy and Management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePollution reduction programs, clean transport, fuel control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTechnological\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElectric vehicles, urban ventilation and filtration systems\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChanges in fuel consumption patterns, public awareness, population migration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGiven the current situation in Tehran, four scenarios are predicted for the future, which are:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eScenario 1\u003c/strong\u003e\u003cp\u003eGreen and Smart Tehran (Sustainable and Low Carbon)\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePollution reduction policies are effectively implemented (clean transport, green spaces, renewable energy).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAlthough summer temperatures rise, management of the urban heat island reduces particle levels.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe average concentration of 0.4 \u0026micro;m particles is predicted to decrease by about 30% (\u0026asymp;\u0026thinsp;0.35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003cp\u003eImproved air quality index and more clean air days.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eScenario 2\u003c/strong\u003e\u003cp\u003eWarming and Climatic Stress (Seasonal Pollution Increase)\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAnnual mean temperature rises by 2\u0026ndash;3\u0026deg;C and humidity decreases by 10%.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLocal winds weaken, reducing natural city ventilation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eParticle concentration, especially in summer, increases up to 0.8 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMore pollution-alert days, especially in July - September.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003cp\u003eIntensified health risks; urgent need for climate adaptation mechanisms.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eScenario 3\u003c/strong\u003e\u003cp\u003eIneffective Management and Chronic Pollution Intensification\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eControl policies are poorly implemented; old vehicles increase.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePopulation growth and construction expansion restrict urban airflow.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHigher temperatures and lower humidity \u0026rArr; smaller particles remain suspended longer.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAnnual mean concentration rises to about 1 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e or higher.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003cp\u003eUrban health crisis, increased healthcare costs, and climate-driven migration from central areas.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eScenario 4\u003c/strong\u003e\u003cp\u003eTechnological Transformation and Urban Innovation\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e60% of vehicles replaced by electric ones.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSmart monitoring network with rapid pollution response.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eUse of reflective and cooling materials in urban construction.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCombined actions lead to a 40% reduction in particles smaller than 1 \u0026micro;m.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003cp\u003eAir quality in dense urban areas approaches WHO acceptable levels.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eBased on Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provided, the trend of changes in pollution and environmental conditions in different scenarios of Tehran can be analyzed. In the current situation, the average of suspended particles is 0.52 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and the air quality is at a moderate level, with health impacts also assessed as moderate, and the long-term sustainability of environmental conditions is also moderate. In scenario 1, by implementing pollution reduction policies and sustainable urban measures, the average of particles is reduced to 0.35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and the air quality is improved to a good level; the health impact is reduced and the long term sustainability is increased. Scenario 2, which reflects the effects of warming and reduced humidity, increases the average of particles to 0.80 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and the air quality becomes unhealthy, with a high health impact and low sustainability. Scenario 3, which results from inefficient management and the intensification of chronic pollution, creates a critical situation; suspended particles reach 1 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, the air quality is very unhealthy, health is severely threatened, and environmental sustainability is greatly reduced. In contrast, Scenario 4, by leveraging technological innovations and replacing electric vehicles, average particulate matter is reduced to 0.30 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, air quality reaches good levels, health impacts are low, and long-term sustainability is high. Overall, this table shows that management policies and technology can play a key role in reducing pollution and improving urban health and sustainability.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative analysis of predicted scenarios\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndicator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBaseline\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eScenario 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eScenario 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eScenario 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eScenario 4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean PM (\u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean Temperature (\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelative Humidity (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAir Quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnhealthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVery Unhealthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Impact\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCritical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLong Term Sustainability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVery Low\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo effectively address air pollution in Tehran, a set of integrated policy measures is essential. First, simultaneous monitoring of particulate matter alongside key climatic parameters will enable dynamic modeling and more accurate prediction of pollution events. Second, optimizing urban design through initiatives like an Urban Cooling Plan can help mitigate the urban heat island effect, reducing temperature-related pollution peaks. Third, developing advanced air quality forecasting systems based on machine learning will support proactive management and timely public advisories. Finally, strengthening the city\u0026rsquo;s resilience to extreme climate scenarios will ensure long-term sustainability, safeguarding public health and maintaining livable urban conditions despite future environmental challenges.\u003c/p\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eThe results indicate that particulate matter (PM) concentrations in Tehran follow a distinct seasonal pattern, with the lowest levels observed in winter and the highest in summer. These findings highlight the necessity of managing pollutant sources according to seasonal conditions. In particular, focusing control policies during the summer can help reduce citizens\u0026rsquo; exposure to air pollution. Monitoring of 0.4 \u0026micro;m particles at four stations across Tehran showed a clear seasonal fluctuation pattern, with the lowest concentration in winter (0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in January) and the highest in summer (0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in August and September). These variations are primarily influenced by meteorological conditions (precipitation, humidity, temperature, temperature inversion) and local sources (traffic, construction activities, and industries). The inverse relationship of particle concentration with relative humidity and wind speed, as well as the direct relationship with increasing temperature, demonstrates the key role of climatic variables in pollutant dispersion or accumulation. Spatially, high traffic stations recorded the highest concentrations, while stations located away from main roads recorded the lowest. Chemical and morphological analyses of particles indicated that their composition originates from dual natural (dust, minerals) and anthropogenic (fossil fuel combustion, construction, transportation) sources. Given the high toxicity of fine particles, even at low concentrations, these findings underscore the importance of air quality management, control of mobile pollutant sources, and the development of comprehensive pollution reduction policies in Tehran. Considering the substantial production and emission of particulate matter in the open environment, the physical conditions of buildings throughout the city, and the increasing energy imbalances in recent years, having a structured program for managing and controlling this issue has become critical. Achieving favorable outcomes depends on proper implementation of such programs and public cooperation.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u003c/strong\u003e \u003cstrong\u003eto\u003c/strong\u003e \u003cstrong\u003epublish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files. Should any raw data files be needed in another format they are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declare no Competing Interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research project was carried out under the author\u0026apos;s grant at Kharazmi University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author solely contributed to all stages of the work, including material preparation, data collection, and development of graphical illustrations, data analysis, and drafting of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen C, Zhao Y, Zhang Y, Zhao B. 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Press release; 2013.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fine Particles, Air Pollution, Particulate Matter, Climatic Parameters","lastPublishedDoi":"10.21203/rs.3.rs-8207062/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8207062/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDue to rapid industrialization, population growth, and urban development, Tehran faces serious air pollution challenges. In this study, the concentration of fine particles with an average diameter of 0.4 \u0026micro;m was monitored at four stations across Tehran over a one year period. The results indicated that the annual mean concentration ranged from 0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in winter to 0.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in summer, exhibiting a clear seasonal pattern. Concentrations increased during warm months due to higher temperatures, lower relative humidity, atmospheric stability, and urban activities, while they decreased in cold months under the influence of precipitation and atmospheric cleansing. Statistical analysis revealed a relatively strong inverse relationship between relative humidity and particle concentration (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.73) and a direct correlation between temperature and particle concentration (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.81). Spatially, stations near urban pollution sources recorded higher concentrations, whereas peripheral stations showed lower levels. SEM analysis indicated a diverse particle composition of dual origin (natural and anthropogenic), with finer particles primarily from combustion and mobile sources, and coarser particles from dust, construction, and mineral sources. These findings highlight the critical role of climatic conditions and local sources in fine particle variability and underscore their importance in urban air quality management and forecasting.\u003c/p\u003e","manuscriptTitle":"Urban Air Quality Assessment: Variability and Behavior of Fine Particles under Tehran’s Climatic Conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 17:54:12","doi":"10.21203/rs.3.rs-8207062/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f78f0049-c4cf-40c8-9161-5b213fc4b14b","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-07T10:39:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 17:54:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8207062","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8207062","identity":"rs-8207062","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}