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BACKGROUND AND OBJECTIVES: According to global statistics, the amount of energy consumption in recent decades has grown uncontrollably and maximally due to the energy consumption in urban fabrics, except for transportation, which is clearly the quality of placement and construction of building masses in the context of urban morphology is more important. The main purpose of this study was to evaluate the components of energy consumption in urban settlements based on the urban morphological model's sustainability. METHODS: Research in terms of structure was analytical-descriptive, which in terms of the main purpose, was a type of applied and developmental research. The method of data collection was as documentation and using Bing Map data reference and data generation with Arc GIS software and 3D modeling with Google SketchUp software, the dimensions and indicators ofwhich were extracted in the form offigure ground. Case studysample on a scale of 150 by 150 as an isolated urban fabric in the explained scales, different building configurations, the common types ofwhich have been selected and simulated according to the form structure of Khorramshahr urban settlements. Energy considerations were also assessed using energy analysis software with an urban climate analytical approach such as Climate Consultant and Envi-Met. FINDING! The results showed that assigning a ranking weight to each morphotypefor each parameter, the average weight of each case, which includes all 5 parameters, indicates the rank position of morphotypes in Khorramshahr. From four types studied, High-rise buildings with an average of 3.13 worst impact and detached housing with an average of 1.93 have the best impact on the microclimate formed around them, which obviously energy efficiency according to climatic indicators and microclimate metrics can be emphasized the principle of optimal limit. CONCLUSION: The findings of the current research showed the energy consumption status according to the evaluation of morphological variables. It was the morphotypes as well as the climatic parameters that have determined the specific results of each case and also provided the appropriate type and rating. In future research, by explaining the optimal model of urban fabric stability model based on the concept of sustainable morphology, each morphotypes in the optima state can be evaluated. [ABSTRACT FROM AUTHOR]

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Elsevier Ltd. All rights reserved.)

Official statistics demonstrate the role of traffic accidents in the increasing number of fatalities, especially in emerging countries. In recent decades, the rate of deaths and injuries caused by traffic accidents in Iran, a rapidly growing economy in the Middle East, has risen significantly with respect to that of neighboring countries. The present study illustrates an exploratory spatial analysis' framework aimed at identifying and ranking hazardous locations for traffic accidents in Zanjan, one of the most populous and dense cities in Iran. This framework quantifies the spatiotemporal association among collisions, by comparing the results of different approaches (including Kernel Density Estimation (KDE), Natural Breaks Classification (NBC), and Knox test). Based on descriptive statistics, five distance classes (2-26, 27-57, 58-105, 106-192, and 193-364 meters) were tested when predicting location of the nearest collision within the same temporal unit. The empirical results of our work demonstrate that the largest roads and intersections in Zanjan had a significantly higher frequency of traffic accidents than the other locations. A comparative analysis of distance bandwidths indicates that the first (2-26 m) class concentrated the most intense level of spatiotemporal association among traffic accidents. Prevention (or reduction) of traffic accidents may benefit from automatic identification and classification of the most risky locations in urban areas. Thanks to the larger availability of open-access datasets reporting the location and characteristics of car accidents in both advanced countries and emerging economies, our study demonstrates the potential of an integrated analysis of the level of spatiotemporal association in traffic collisions over metropolitan regions., Competing Interests: The authors declare no conflict of interest.