ENVIRONMENTAL HAZARDS MANAGEMENT
Year:2020 | Volume:7 | Issue:3|Papers Count:6

In this study, Shannon's entropy and the TOPSIS techniques have been used for ranking residential areas against the earthquake hazards. For this purpose, 8 variables were examined in 27 districts of Amol city. These variables include released energy, earthquakes of the last 20 years in terms of ton TNT, buildings quality, residential density, building density, population density, network permeability, urban open space, and groundwater depth after construction. Information was ranked based on the proximity to the ideal vulnerability ideal using the Shannon entropy and the TOPSIS multi-character decision model. The rankings obtained from this analysis were added to the city map and the areas of the city were divided into five categories with vulnerability, including ‘ too much’ , ‘ much’ , ‘ medium’ , ‘ little’ , and ‘ too little’ and finally the map of the extent of Amol's vulnerability was prepared. The results showed that the central areas, i. e. 24, 13, 18, 10, and 12, are very vulnerable. Moreover, areas 19, 17, 14, and 16 are highly vulnerable, areas 15, 21, 2, 6, 22, 25, 11, 20, 27, and 4 have moderate vulnerability, areas 26, 9, 23, 3, 1, and 5 have low vulnerability, and finally, areas 8 and 7 have very vulnerable to earthquakes, respectively. Therefore, it is expected that the vulnerability of urban areas will be considered in future constructions.

Environmental hazards cause great human and financial damage to the people of Northern Khorasan province every year. In this research, while introducing different types of environmental hazards in different parts of Northern Khorasan, we aim to classify their issues and problems and to specify the time calendar of each in order to prevent possible damages and crises. The method used in this research is descriptive-analytical based on field studies, library and statistical analysis. Given the importance and incidence of Covid-19 disease, in order to assess its risk in the last three weeks ending August 22, 2020 in the townships of the province, first, the adjusted incidence rate was calculated in the last week (AIRW1), the penultimate week (AIRW2) and two weeks ago (AIRW3). Then, using the relevant relationship, the status of each townships in terms of white, yellow and red was determined. Regarding the risk of frost, long-term statistics of minimum temperature of synoptic and evaporative stations of Bojnourd, Asadli, Aghmazar, Resalat, Shirvan, Cheri, Khosh, Noshirvan and Jajarm were used on a daily scale. To determine the time of the beginning and the end of the glaciation, the days convert to the Julius calendar and Minitab and Arc GIS software were used to draw graphs and maps of temporal and spatial distribution of the beginning and end of glaciation. The results show that geographical location, environmental conditions and spatial planning system make the occurrence of environmental hazards in Northern Khorasan province inevitable and different regions of this province damage from 51 environmental hazards in the form of 4 general types of natural hazards includes geological, climatological, hydrological and biological hazards and two intentional and unintentional human hazards. This situation requires increasing the safety factor of habitats and activities and modifying and changing the methods and instructions by the relevant agencies to deal with these unexpected events. Harmonization of farmers' lives and activities with frost conditions and geographical compatibility with the Corona virus is suggested as the best biological solution.

Improving the resilience of urban fabrics is one of the main steps to reduce the social and economic consequences of natural disasters such as earthquakes. For this reason and in the first step, the status of the resilience of urban fabrics to natural hazards should be evaluated based on the relevant effective factors. This article evaluates the assessment of resilience in historic-commercial urban fabrics (traditional bazaars). The physical, economic, social and institutional dimensions of resilience have been defined and subdivided into 42 sub-indicators. Cultural and historical dimensions have also been added as a new dimension in the assessment of the resilience of these fabrics and are categorized into eight sub-indicators. Therefore, 50 key sub-indicators in 17 indicators in five dimensions were considered in this study. In the next step, and to evaluate the impact of each parameter on resilience, the weights of dimensions, indicators and sub-indicators are determined using the Analytical Hierarchy Process (AHP) procedure. The questionnaire also was developed and circulated among the relevant experts in this field. The results of this assessment indicate that the social dimension is of the essential importance for the resilience of traditional bazaars. In addition, the calculation of the final weights and the ranking of the 50 sub-indicators showed that the first nine sub-categories had an impact of more than 50% on resilience, including 1. Land use, 2. The economic value of the property and goods, 3. The adaptability of different groups for post-earthquake recovery, 4. Capacity for recovery, 5. Previous experiences and preparation, 6. Willingness to pay for risk reduction, 7. Income, 8. Educations in risk reduction and disaster management, and 9. Vulnerability of the roads. The results of this study can be used to prioritize rehabilitation of different places in traditional bazaars and to identify the most effective interventions to improve resilience

Occurrence of the 2003 earthquake caused a wide range of injuries, deaths, physical damages and extensive destruction of the garden-city fabric and, as a result, sudden changes in the social-physical environment of Bam. To date, there has been no quantitative measurement tool to assess the impacts of sudden environmental changes following an earthquake in Iran. The aim of this study is to rebuild, validate and establish a scale for measuring environmental distress following the earthquake. This scale includes 79 items and 6 factors of place attachment, frequency of environmental issue, observations of environmental issue, threats, felt impacts and solastalgia. The questionnaire was parallel translation into Persian, group-based judgment assessment, back translation, adjustment, pilot and field survey. The research method is descriptive-survey with exploratory factor analysis approach. In the pilot phase, 44 residents of Bam completed the questionnaire and scale variance, corrected item-total correlation and mean were calculated. The statistical population of the field survey is 295 residents of Bam who completed the online questionnaire in a non-random and accessible method. Findings indicate that in the Bam Earthquake Environmental Distress Scale, the content of the main scale has been preserved with appropriate adaptation and adjustment for contextual differences. According to the analysis, 9 factors including place attachment, solastalgia, severity and extent of pollution and environmental issues caused by the earthquake and reconstruction operations, changes in the topology and shape of the earth after the earthquake, pollution or disruption of water resources, environmental issues caused by debris and reconstruction, changes in the natural landscape of the city, assessment and perceived impacs of reconstruction, development and benefits and the consequences of the earthquake on the survivors health were identified. This scale is a reliable tool for assessing the psychological impacts of sudden changes in the environment following the earthquake in Iran.

Due to the adverse effects of pollutants on the environment and human health, the analysis of air quality data has an important role in protecting the environment and tackling air pollution problems. Missing data in time series, especially air pollution data, Cause a particular challenge to the analysis of these data, which show the importance of using methods known as imputation in order to deal with this phenomenon. Missing values reduce the volume of data, change time patterns in data and make inaccurate conclusions in data analysis. In this study, in order to estimate the missing values in time series data of PM_2. 5 pollutant concentration from 12 contamination stations in Tehran, a hybrid algorithm based on regression algorithm considering spatial and temporal similarities and dependence by dynamic time wrapping algorithm is presented. Data with missing values with a pattern similar to the original data were simulated in the interval of 10, 15 and 20% missing in data, with the aim of evaluating the performance of the single and multiple imputation models. Then the proposed method in combination with different multiple imputation methods such as classification and regression tree, random sample and predictive mean matching, have been implemented and results have been compared with single imputation methods. Implementation results indicated the superiority of the proposed method combined with regression tree and linear interpolation compared to other methods of multiple and single imputation

Floods are one of the most important hazards that always cause a lot of damage to urban areas. One of the cities exposed to floods is Noorabad city in Lorestan province. Accordingly, this study has identified flooded areas as well as flood-prone areas in the urban area of Noorabad. In this study, in order to identify flooded areas and areas prone to floods, a digital model of 5 m height, 1: 50, 000 topographic map, Sentinel radar images, information about Dubai and river roughness coefficient have been used as research data. ARCGIS, HEC-RAS and SNAP software are also considered as research tools. This research has been done in 4 stages, which in the first and second stages have been determined by using Sentinel 1 radar images and field visits, respectively, in the flooded areas in April 2009. In the third stage, using the HEA-RAS method, the flood-prone areas of the region have been identified and in the fourth stage, the obtained results have been compared and evaluated. The results of the evaluation of the flooded areas using radar images and field visits indicate that due to the floods in April 2019, 0. 562 and 1. 212 km2 of the urban area, respectively, have been flooded. The results of the HEC-RAS method also indicate that 1. 542 km2 of the urban area of Noorabad is at risk of flooding with a 100-year return period. Evaluation and comparison of the results obtained through different methods indicate that the obtained results are consistent with each other. In fact, the areas identified in the field visits as flooded areas are also identified in the radar images as flooded areas. Based on the results of the HEC-RAS method, these areas are considered to be flood-prone areas.