Search Results (14)

In recent years, air pollution has become a significant issue for megacities. This study analyzed the air pollution levels in Tehran and the relationship between pollutant concentrations and atmospheric quantities during 2023. The correlation coefficients between wind speed, temperature, mean sea level pressure (MSLP), and relative humidity (RH) were calculated against the concentrations of NO₂, NO_x, PM₁₀, and PM_2.5. Additionally, one case study was conducted for each pollutant. Approximately 72% of haze phenomena in Tehran were recorded in November, December, and January. The monthly pattern of PM₁₀ concentration indicated higher levels in the southern and western parts of Tehran. For PM_2.5, in addition to these areas, significant concentrations were also observed in the central and eastern parts. NO₂ concentrations were found to be higher in the northeast and northern areas. An inverse relationship was found between wind speed and temperature with pollutant concentrations. Positive correlations between MSLP and pollutant concentrations suggested that the pollutant levels also increased as air pressure rose. RH showed a significant direct relationship with PM_2.5 and NO_x. Synoptic analysis revealed that PM₁₀ case studies often occurred during the warm season, with a thermal low pressure situated over the Iranian plateau. During PM_2.5 and NO₂ pollution events, Tehran was influenced by high pressure, and 10 m wind speeds were weak. Finally, verification of the 24 h forecast of the CAMS model showed that, while the model accurately predicted the spatial distribution of pollutants in most cases, it consistently underestimated the concentration levels. Full article

This study investigated the bioaccumulation of PTEs in the 22 districts of the Tehran metropolis using the lichen Anaptychia setifera collected from Kalpoosh unpolluted area in Semnan province and exposed for 4 months in the study area using the lichen transplant technique. The concentrations of eight potentially toxic elements in the lichen were quantified using ICP-OES analysis. PCA was used to detect common sources of PTEs, and distribution maps were produced using QGIS. A statistically significant difference in the toxic elements was observed among the different stations in the Tehran metropolis. The CF index results indicate severe pollution (CF ≥ 3) for all eight studied toxic elements in the atmosphere of the Tehran metropolis. The values of the PLI index in the monitoring stations were calculated in the range of 14–31, confirming very high pollution (PLI ≥ 2.5) in the study area. The results showed a significant accumulation of all investigated toxic elements. Toxic elements such as Fe, Al, and Cr were primarily derived from natural geogenic sources, whereas Co, Cu, Ni, Pb, and Zn originated from anthropogenic sources, predominantly vehicular traffic, as depicted by the distribution patterns of these toxic elements, with peaks near sites with heavy traffic. Overall, the entire study area exhibited severe pollution levels. Full article

Although recent dramatic political changes in Afghanistan have brought that country to global attention, migration from Afghanistan to Iran has a long history. Nearly three quarters of Afghan immigrants in Iran are located in cities, particularly in Tehran’s metropolitan area. However, despite the long-term presence of Afghan immigrants in Iran, research on patterns and drivers of spatial segregation of immigrants has been very limited. The research method involves a secondary analysis of census data. Therefore, this article utilizes 2006 Iran census tract data to examine patterns of spatial segregation of Afghan immigrants in the Tehran metropolis. The required data for two-group segregation indices, Getis–Ord statistics, and Geographically Weighted Regression, were analyzed as a map using ArcMap and Geo-Segregation Analyzer. The results reveal that the spatial segregation of Afghans is high and that most live in lower-SES census tracts. Multivariable analyses indicate that the extent of segregation can be explained by education, job class, and generation status. It can be concluded that generational transition and access to human capital have reduced various indicators of spatial segregation of Afghan immigrants in Tehran. Full article

Cities play a critical role in anthropogenic CO₂ emissions, which exacerbate climate change and impact urban populations. Urban green infrastructure, such as urban trees, provides essential ecosystem services, including reducing atmospheric CO₂ levels. However, there is a significant knowledge gap regarding the impact of urban trees on climate change in semiarid, polluted cities like Tehran, the capital and largest metropolis of the Middle East. This study assesses the carbon sequestration and storage potential of Tehran’s urban infrastructure using the i-Tree Eco model. A randomized cluster sampling method was employed, collecting data on species composition, diameter at breast height (DBH), and total tree height. The results indicate that Tehran’s urban trees sequester approximately 60,102 tons of carbon per year, equivalent to 220,393 tons of CO₂. The net carbon storage in urban trees is about 254,579 tons, equivalent to 933,455 tons of CO₂. Parks and urban green spaces demonstrate the highest rate of carbon sequestration per hectare, followed by urban services land use. Prioritizing the planting of species with high sequestration rates like Cupressus arizonica (Arizona cypress) and Cupressus sempervirens L. var. horizontalis (Mediterranean cypress) could enhance carbon sequestration efforts in Tehran. These data provide valuable insights into the carbon sequestration potential and environmental impact of different land use types, and may aid in the development of effective environmental policies and land management strategies in semiarid urban areas and other cities in similar settings. Full article

Land use/land cover (LULC) changes in response to natural factors and human activities constitute a pressing issue for the conservation of Protected Areas in urban–rural landscapes. The present study investigated LULC changes in the Jajrud Protected Area (JPA) and the Kavdeh Wildlife Refuge (KWR) in the Tehran province, Iran, between 1989 and 2019. To inform ecological conservation measures for the JPA and KWR, LULC changes were identified and monitored using Landsat imagery from between 1989 and 2019. In addition, the landscape ecological risk (ER) was evaluated by conducting a landscape pattern index analysis. Then, the importance of different indicators affected by ER in these two PAs was assessed using the Delphi method, and expert opinions were solicited through a questionnaire. As for LULC changes in the JPA, high-density pasture declined the most over 1989–2019, from 38.6% (29,241 ha) to 37.7% (28,540 ha). In contrast, built-up areas increased the most, from 10.4% (7895 ha) in 1989 to 11.9% (9048 ha) in 2019. Water bodies also increased, from 0.88% (676 ha) in 1989 to 0.94% (715 ha) in 2019. In the KWR, cropland and gardens increased the most, from 2.14% (1647 ha) in 1989 to 3.4% (2606 ha) in 2019. Built-up areas also increased, from 0.05% (45 ha) in 1989 to 0.09% (75 ha) in 2019. Water bodies increased from 0.69% (538 ha) in 1989 to 0.71% (552 ha) in 2019. Finally, high-density pasture decreased the most, from 29.4% (22,603 ha) in 1989 to 28.5% (21,955 ha) in 2019. At the same time, the high and very high ER classes increased, more so in the JPA compared to the KWR. Finally, considering both LULC and ER changes, the Delphi method demonstrated that the greatest impacts occurred in the JPA. Various illegal economic and physical activities have created LULC changes and caused extensive destruction of ecosystems, posing a high ER in the study areas. The intensity of ER differs between the two PAs because of the varying distance from the metropolis, varying degrees of human activities, LULC changes, along with differences in legal restrictions of use. Aligned with the management plans of these areas, our research shows that it is necessary to develop land only within the designated zones to minimize the amount of ER. Various models of LULC changes have been presented, and a comparison of these models relating to the methodology and model effectiveness can help increase their accuracy and power of interpretation. Full article

Rapid urbanisation, economic growth, and urban spatial development in developing countries, such as Iran, have resulted in tremendous loss of green cover and associated ecological problems. Any effort to achieve sustainable urban development should be supported by recognising and evaluating the ecological health of vegetation cover. This study investigates vegetation cover reduction and changes in the Tehran Metropolis, Iran and identifies the most important factors influencing the observed changes. The aim of this study is two-fold: first, to assess the spatio-temporal changes in vegetation cover in Tehran between 1990 and 2020, and second, to identify the factors contributing to the changes. The Normalised Difference Vegetation Index (NDVI) is used as an indicator of green cover. The spatial and statistical data used in this study were extracted from Landsat satellite imagery and the last approved Master Plan of Tehran (2006). Geographically Weighted Regression (GWR) and geographical modelling methods were employed to analyse vegetation cover in all municipal districts of the Tehran metropolis. The results show that the vegetation density in the Tehran metropolis decreased significantly (from 38,936.80 hectares to 4663.23 hectares) between 1990 and 2020. The expansion of construction lands and the increase of population density were the most significant factors affecting the reduction in vegetation cover in Tehran. In contrast, the growth of industrial units in the urban areas of Tehran had no significant relationship with vegetation cover. The results of this study can help urban planners understand the significant drivers of vegetation loss and identify appropriate interventions to prevent it. Full article

Quantifying the effect of non-point source pollution from different land use types (e.g., agricultural lands, pastures, orchards, and urban areas) on stream water quality is critical in determining the extent and type of land use. The relationship between surface water quality as the primary source of drinking water and land use patterns in suburban areas with an accelerated pace of industrial development and progressive growth of population has drawn much attention recently. This study aims to determine the type and portion of the land use changes over three-time intervals from 2000 to 2015 in the Jajrood River Catchment (Tehran metropolis, north of Iran). We used satellite images of Landsat TM and ETM for 2005, 2010, and 2015 to analyze land use changes as a spatiotemporal model. According to the image processing and analysis, we classified the land uses of the study area into irrigated farming, orchards, pastures, and residential areas. In addition, we used temporal data from sampling stations to identify the relationship between land use and water quality based on a multivariate regression model. The analysis shows a significant correlation between the type and extent of land use and water quality parameters, including pH, Na⁺, Ca⁺, Mg⁺, Cl⁻, SO₄²⁻, NO₃⁻, and TDS. Pastures and residential areas had the highest impact on water quality parameters among all land use types. Besides, we have used the regression analysis results to determine the maximum permissible areas of each land use type. Consequently, effective management strategies such as land use optimization in catchment scale for this catchment and similar areas will help to consciously protect and manage the quality of drinking water resources. Full article

Urban resilience refers to the capacity of an urban system to fully recover from unforeseen calamities. This study aims to assess the physical resilience indicators used to measure urban resilience in Tehran, the political and economic capital of Iran, and to pinpoint the most significant direct and indirect influences on urban resilience. The research process divided into two parts. The environmental scanning approach (reviewing papers and published sources, interviewing specialists, and monitoring conferences) and the literature review were employed in the first part to compile a database of the key information on the elements impacting physical resilience. The most significant factors impacting physical resilience over the next ten years were requested to be identified by specialists and intellectuals in the second part. Finally, the MicMac program was used to analyze the data after 29 variables were specified in Delphi. In light of the trace-analysis-dependence diagram, which depicts the instability of the influential factors and the persistence of their impact on other variables, the results demonstrate that Tehran’s physical resilience is in an unstable condition. According to the results, the factors that have the maximum impact on other variables are granularity drivers, emergency evacuation capacity, rescue and security spaces (emergency, fire station, and police station), impermeability, rate of the amendment and retrofitting measures in the buildings of each zone, building age, and the compatibility of land uses. The variables that are most susceptible to change from other variables include the distribution status of dangerous land uses, the quality of the buildings, the rate of historically vulnerable buildings, the vulnerability of internal and external roads, the rate of improvements and retrofitting measures in buildings in each zone, as well as historically vulnerable historical buildings. Full article

Preparedness against floods in a hazard management perspective plays a major role in the pre-event phase. Hence, assessing urban vulnerability and resilience towards floods for different risk scenarios is a prerequisite for urban planners and decision makers. Therefore, the main objective of this study is to propose the design and implementation of a spatial decision support tool for mapping flood vulnerability in the metropolis of Tehran under different risk scenarios. Several factors reflecting topographical and hydrological characteristics, demographics, vegetation, land use, and urban features were considered, and their weights were determined using expert opinions and the fuzzy analytic hierarchy process (FAHP) method. Thereafter, a vulnerability map for different risk scenarios was prepared using the ordered weighted averaging (OWA) method. Based on our findings from the vulnerability analysis of the case study, it was concluded that in the optimistic scenario (ORness = 1), more than 36% of Tehran’s metropolis area was marked with very high vulnerability, and in the pessimistic scenario (ORness = 0), it was less than 1%was marked with very high vulnerability. The sensitivity analysis of our results confirmed that the validity of the model’s outcomes in different scenarios, i.e., high reliability of the model’s outcomes. The methodical approach, choice of data, and the presented results and discussions can be exploited by a wide range of stakeholders, e.g., urban planners, decision makers, and hydrologists, to better plan and build resilience against floods. Full article

This study aims to calibrate and validate the EPA Storm Water Management Model from field measurements of rainfall and runoff, in order to simulate the rainfall-runoff process in an urban watershed of Tehran metropolis, Iran. During and after three significant storm events, the flow rates, total suspended solids (TSS), total phosphorus (TP), and total Kjeldahl nitrogen (TKN) concentrations were measured at the outlet of the catchment, and were used in the model calibration and validation process. The performance of the SWMM model was evaluated based on the statistical criteria, as well as graphical techniques. In this study, a local sensitivity analysis was carried out to identify the key model parameters, show that “the percentage of impervious surface in each subwatershed had the most effect on the model output”. Based on the analysis of the results, SWMM model calibration and validation can be judged as satisfactory, and the goodness-of-fit indices for simulating runoff quality and quantity are placed in acceptable ranges. The adjustment obtained for the variations in the measured and simulated flow rates, pollutograph concentrations, total pollutant load, peak concentration, and the event mean concentration (EMC) confirms the considerable predictive capability of the SWMM model when it is well calibrated by using field measurements. Full article

Predicting the travel demand plays an indispensable role in urban transportation planning. Data collection methods for estimating the origin–destination (OD) demand matrix are being extensively shifted from traditional survey techniques to the pre-collected data from intelligent transportation systems (ITSs). This shift is partly due to the high cost of conducting traditional surveys and partly due to the diversity of scattered data produced by ITSs and the opportunity to derive extra benefits out of this big data. This study attempts to predict the OD matrix of Tehran metropolis using a set of ITS data, including the data extracted from automatic number plate recognition (ANPR) cameras, smart fare cards, loop detectors at intersections, global positioning systems (GPS) of navigation software, socio-economic and demographic characteristics as well as land-use features of zones. For this purpose, five models based on machine learning (ML) techniques are developed for training and test. In evaluating the performance of the models, the statistical methods show that the convolutional neural network (CNN) leads to the best performance in terms of accuracy in predicting the OD matrix and has the lowest error in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE). Moreover, the predicted OD matrix was structurally compared with the ground truth matrix, and the CNN model also shows the highest structural similarity with the ground truth OD matrix in the presented case. Full article

Since the impacts of climate change will last for many years, adaptation to this phenomenon should be prioritized in urban management plans. Although Tehran, the capital of Iran, has been subject to a variety of climate change impacts in recent years, appropriate adaptation measures to address them are yet to be taken. This study primarily aims to categorize the barriers to climate change adaptation in Tehran and analyze the way they interact with each other. The study was done in three steps: first, the focus group discussion (FGD) method was used to identify the barriers; next, the survey and the structural equation modeling (SEM) were used to validate the barriers, identify their importance, and examine their possible inter-relationships; and finally, the interpretive structural modeling (ISM) was applied to categorize and visualize the relationships between the barriers. Results show that barriers related to the ‘structure and culture of research’, ‘laws and regulations’, and ‘planning’ belong to the cluster of independent barriers and are of greater significance. The ‘social’ barrier and barriers related to ‘resources and resource management’ are identified as dependent barriers and are of lesser importance. Barriers related to ‘governance’, ‘awareness’, ‘education and knowledge’, ‘communication and interaction’, and ‘economy’ are identified at the intermediate cluster. The findings of this study can provide planners and decision makers with invaluable insights as to how to develop strategies for climate change adaptation in Tehran. Despite the scope of the study being confined to Tehran, its implications go far beyond this metropolis. Full article

Urban parks play an important role in increasing the quality of urban life. Thus, a variety of approaches to planning and decision-making regarding sustainable open spaces and urban parks is needed, especially when models from one location are borrowed to another with a very different culture. In many developing countries cities are expanding without proper planning of public green spaces which places pressure on the quality of life. In common with many Middle Eastern cities, Tehran, the capital of Iran is a large sprawling metropolis which has experienced fast growth since 1970 and with little in the way of comprehensive planning of green spaces as an organised system. To date there has been no comprehensive investigation of urban parks regarding their level of use, range of activities, quality of maintenance, evidence of anti-social activities or the demographic character of their catchment—important information for effective park planning. In this study a representative sample of 16 parks in Tehran was studied using a combination of site assessments and user observations. We found that a combination of factors concerning the quality of the parks such as presence of facilities, existence of water and other special attractions, as well as how well-lit they are, how well maintained and safe they are, has a lot to do with their level of use. Some pleasant parks with good facilities are less well used because of, e.g., evidence of anti-social behaviour, poor maintenance and accessibility. A key aspect we found is the difference between male and female users, with some parks being much less-well-used by women. Much more attention is needed for planning and management of parks in Tehran. The approach applied here has potential to help other cities in similar areas to learn more about their green space systems for planning purposes. Full article

In the modern world, the fine balance and delicate relationship between human society and the environment in which we exist has been affected by the phenomena of urbanisation and urban development. Today, various environmental factors give rise to horizontal dispersion, spread and growth of cities. One of the most important results of this is climatic change which is directly affected by the urban sprawl of every metropolis. The aim of this study is to identify the relationship between the various horizontally distributed components of Tehran city and changes in essential microclimate clusters, by means of the humidex index. Results showed that, when the humidex was calculated for each of the obtained clusters, it was evident that it had increased with time, in parallel with Shannon’s entropy, as a consequence of the average temperature and relative humidity of each cluster. At the same time, results have shown that both temperature and relative humidity of the study area are related with urban sprawl, urbanisation and development, as defined by Shannon’s entropy and, in consequence, with humidex. In consequence, this new concept must be considered in future research works to predict and control urban sprawl and microclimate conditions in cities. Full article