Journal of Spatial Analysis

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Spatial analysis of the factors influencing households’ direct energy
consumption and CO₂ emission in Ardabil
Problem Statement
Carbon management and its production resources are important not only for the preservation of non-renewable resources but also for the prevention of global warming and its adverse consequences. Direct consumption of fuel and energy by households plays a major role in CO₂ production and it’s spatial distribution. Therefore, in order to plan and manage carbon emissions, it is very important to identify the factors influencing household energy consumption. This paper aimed to investigate the relationship between household characteristics such as age, income, family size, household head age, house area, etc. and energy consumption which ordinally results in more emissions. The study area is Ardabil city. It has an area of 6289 ha and a population of about 530000 people.

Research Method
Consumption of natural gas, electricity and car fuel has been the criteria for determining the amount of household energy consumption. The data of the first two cases obtained from the bills of household’s consumption and the data of car fuel consumption and the other other required data, were collected through a survey as well. Based on the Cochran's formula, statistical samples including 383 households were selected as a sample of the households residing in Ardabil. A questionnaire was also used to collect the data. Data on energy consumption variables were first converted to Mj and then converted to CO₂ emissions.  The data was then entered into Arc GIS to draw spatial distribution maps using Kriging interpolation Tool. Finally, using TerrSet Geospatial Monitoring and Modeling System software, the spatial relationship maps were produced and the adjusted R values were calculated.

Findings and Conclusions
Findings demonstrate that in Ardabil, household fuel consumption cause to an emission of more than  226,515 grams of CO₂ per household every month which is three times more than the mean value for all the Iranian households. In the study area, the average amount of energy consumption and carbon emission of households residing in municipality districts 2 and 3 are higher than same figure for all the households residing in the city. In contrast, in the municipality districts of 1 and 5, energy consumption and CO₂ emission are lower than the mean value for the whole Ardabil households. In district 4, the figure is very close to the mean value for all the households. More than 80 percent of household CO₂ emission emitted from fuel consumption in homes and this ratio is almost the same throughout the city and in all municipality districts. After that, the ratio of transportation CO₂ emission is about 15%, and electricity consumption has a ratio of less than 5% as well. In four lots located in the southwest, north, northeast and the center of the city, every year, households emit less than 172640 g/m of CO₂. In contrast, in 4.8% of the city surface area, the lots located in southwestern and southeastern, households’ emission of CO₂ is the most (more than 308923 g/m). The adjusted R, which represents the spatial relationship between the variables with CO₂ emission, for all the 11 variables, were 0.67, 0.66, 0.72, 0.80, 0.87 and 0.88 for the city, district 1, district 2, district 3, district 4 and district 5 respectively and these values indicate that there is a high correlation between these variables. The highest adjusted R values (0.8 and more) belong to the strip-shaped lots locate in the central and eastern fringes of the city and they cover almost half of the surface area of district 2 and a small part of district 1. Areas where R value is less than 0.2 cover almost the whole surface of district 5 in the northeast of the city. Also, variables of “number of people who have a driving license in any household”, “household head age”, “household size and “house surface area”, represent a high correlation between these variables and CO2 emissions. Also, the correlation between the variables level of “education of household head”, “household head income” and “having electrical appliances” indicate that there is the lowest correlation between the variables and with CO₂ emissions.
Key Words: Energy, CO₂, Household consumption, Spatial relation, Ardebil

 

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Conclusion
The results showed that the length of the precipitation period in the study area is 8 months (out of 213 systems, 60 systems were recorded in January and 50 systems were recorded in December). June, July, August and December did not have a comprehensive rainfall system. The difference in height between the Mediterranean Cyclone  and the Arabian Anticyclone, i.e. the MAI index, was identified in 5 categories. The results showed that the higher the value of MAI index, the less rainfall systems and the higher the rainfall intensity. Most rainfall systems occur when the MAI index reaches 100 to 150 geopotential meters. In addition, the concentration of precipitation occurred in February when the MAI index reached 200 geopotential meters and above. In the continuation of the research, the difference between the Sudan Cyclone and Arabian Anticyclone, i.e. the SAI index, was also identified in 5 categories. The results showed that most of the systems occurred in the third category with a value of SAI index between 100 and 150 geopotential meters. Moreover, the results showed that the higher the value of the SAI index (, the lower the number of rainfall systems and the higher the average of rainfall systems.

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Combat readiness in military units indicates the ability of the unit to perform military missions. To conduct research and extract weather threats in the southeastern region, data from 19 synoptic stations with a statistical period of 22 years were used and to prioritize weather threats, combat readiness criteria were used. Dust storms, heat stress, heavy rainfall and sultry conditions were identified as the most important weather threats affecting combat readiness in the region. Based on the hierarchical analysis of dust storms, the most important and effective threat to the combat readiness of military units was identified, the incompatibility rate was calculated and its value was less than 0.1, so pairwise comparison, weighting and prioritization of threats were confirmed. The zoning map of each weather threats was prepared in GIS software and finally, using the weight of each weather threats, it was obtained by combining the zoning maps of the identified threats and using fuzzy hierarchical analysis, a comprehensive map of weather threats was prepared. Zabol and Zahak synoptic stations in spring, the whole region in summer, Saravan station in autumn and Iranshahr, Saravan, Minab and Kahnooj stations in winter are the worst places for military units and also in autumn the lowest frequency of hazards in the region. We witnessed and based on weather maps, this season was recognized as the best season for the deployment and operation of military units in the region.

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Comparative analysis of snowfall events in Iran with emphasis on the location of the polar plateau and remote connection patterns

Abstract
Extream snowfall event that may occur at any time during the cold season, has significant social and economic implications. Therefore, the economic and social consequences of these events reveal the importance of identifying the synoptical mechanisms associated with the extream snowfall events. In order to achieve this goal, using daily precipitation and temperature data during the statistical period of 1951-1 2016 and based on multiple criteria, the two three-days extream snowfall events were identified during February 7-9, 1972 and February 2-4, 1988. After selecting samples, a statistical analysis of the teleconnection indices was done and then, using the NCEP-NCAR reanalysis data, the combined patterns of surface and lower, middle and lower troposphere were plotted in the form of three-days mean. Results obtained from analysis of teleconnection indices and their correspondence to the synoptic patterns indicate the weakening of the tropospheric polar vortex and its division into multi-centers in the periods of extream snowfall events. In the event of February 7-9, 1972, though the centers were moved to mid-latitudes, but they are not completely out of the Arctic and to some extent maintain their position in this area. In February 2-4, 1988, the vortex centers have shown a more equatorwards displacement towards the mid-latitudes that the emergence of negative phases of the NAM and AO represent such a situation. However, in both events, the strong and main center of the polar vortex is located in the eastern hemisphere and therefore in a state close to Iran. The weakening of the sub-tropical jetstream in the eastern hemisphere, especially in the Mediterranean, has resulted in the transmission of potential vorticity tabs to mid-latitudes. The equatorwards progress of these tabs has led to the formation of the trough in the western and eastern Mediterranean regions that accompany with a ridge between them, led to the formation of omega bundle patterns and split flow, respectively, in the events of February 1972 and 1988 in this geographical area. The southern boundary of the progress of the troughs has specified by index contour of the edge of the vortex by 552 gpdam, that extends to the southern part of Iran and in the February 1972, event compared with the pattern of the February 1988, had the more-equatorwards progress toward the middle latitudes, and as a result, over Iran.
Keywords: extream snowfall event, teleconnection, polar vortex, the edge of the vortex, blocking patterns.

 

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Vulnerability assessment of Miangaran wetland ecosystem

To support the proper management of ecosystems, vulnerability analysis of ecosystems is very important. Vulnerability analysis of ecosystems provides information about weaknesses and capacity of the studied ecosystem for recovery after damage. Considering the degradation status of Miangaran wetland, vulnerability evaluation of this wetland is one of the most important management methods in the region. For this purpose, in this study, after identifying and evaluating the threatening factors of Miangaran wetland, these factors were scored using evaluation matrices. Then, the interaction between these values ​​and threatening factors was examined and the vulnerability of wetland values ​​was obtained by multiplying the scores of all studied factors. Finally, management solutions were presented to deal with the most important threatening factors. According to the results, the most vulnerability is to the hydrological and ecological values ​​of the wetland. The highest effects of threats on the ecological value are also on the birds of Miangaran wetland. The results of the evaluation of Miangaran Wetland show that this wetland has a high potential for ecosystem functions of the wetland. These functions have been neglected in the planning and managing of wetlands at the local, regional and national levels. As a result, ecosystem-based management is suggested as the best management approach. The management in these areas should take action to prevent the vulnerability of Miangaran wetland. Also, the vulnerability evaluation method used in this study can provide a good understanding of the relationship between wetland functions and the resulting services for the management of the ecosystem of Miangaran Wetland.
Key words: Miangaran wetland, ecosystem management, vulnerability assessment

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Study the Effects of Covid-19 on Air Pollutants by Using Sentinel-5 Satellite Images (Case Study: Metropolises of Tehran, Isfahan, and Mashhad)

Zeinab shogrkhodaei, PHD. Student of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Amanollah Fathnia*, Assistant Professor of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Vahid Razavi Termeh, PHD. Student of GIS, Faculty of Geodesy and Geomantic, K. N. Toosi University.

Introduction
One of the challenges facing the international community right now is Covid-19. This pandemic has caused a comprehensive change in behavior contrary to the usual routine, which can lead to changes in people's lifestyles (Briz-Redón et al., 2021). The prevalence of this disease has not only affected the economy and health, but also the environment (Sohrabi et al., 2020). Among the effects of Covid-19 on the environment are the effects on beaches, noise, surface and groundwater, municipal solid waste, and air quality (Zambrano-Monserrate et al., 2020). The restrictions applied during the Covid-19 era were accompanied by a reduction in greenhouse gas emissions by transport and industry, which affected air quality (Rybarczyk and Zalakeviciute, 2020). Air is a vital element for the survival of all living things, but human activities have caused the release of many harmful pollutants into the atmosphere and endangered human health (Ghorani-Azam et al., 2016). Among the causes of death, air pollution is the fourth leading cause of death in the world after tobacco (WHO, 2020a). Sulfur dioxide, nitrogen oxide, carbon monoxide, and ozone are some of the pollutants that cause short-term or long-term exposure to heart and lung disease (Briz-Redón et al., 2021). Human activities are one of the main sources of air pollutants, so their concentration is expected to decrease during the Covid-19 period (Ghahremanloo et al., 2021).
Materials and methods
In this study, the required data were the average monthly pollutants of sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone before (20 February 2019 to 20 February 2020) and after (20 February 2020 to 20 February 2021) the prevalence of Covid-19 virus. For this purpose, Sentinel-5P satellite images were used to prepare the required data set. The case study included three metropolises of Tehran, Mashhad, and Isfahan. Google Earth Engine was used to access Sentinel-5P satellite images. The final output of the images for each pollutant was interpolated for better display and exposure in GIS software using the kriging method. Then, a T-test was used to compare the differences between the concentrations of contaminants before and after the outbreak of the Covid-19 virus and to evaluate the mean correlation. Based on this test, values that were p-value <0.05 were considered significant. This was considered as a change in the concentration of the contaminant before and after the Covid-19 virus (decreasing or increasing). Those pollutants with a p-value <0.05 were considered unchanged.
Results and Discussion
Analysis of the T-test showed that for pollutants such as sulfur dioxide, nitrogen dioxide, and carbon monoxide in all three metropolises, there was no significant change in their concentration before and after the outbreak of the Covid-19 virus. However, significant changes were observed for ozone pollutants. Also, its concentration trend in all three metropolises has been a decreasing trend. The main sources of emissions of nitrogen dioxide, carbon monoxide, sulfur dioxide, and ozone are related to human activities, including transportation and industry (Ghahremanloo et al., 2021; Cárcel-Carras et al., 2021). Pollutants such as carbon monoxide, nitrogen dioxide and sulfur dioxide are the primary pollutants; It means that they are emitted directly from sources, while ozone is a secondary pollutant and depends on complex and nonlinear atmospheric chemistry (Bekbulat et al., 2021). Given that the concentration of ozone surface decreases significantly with increasing concentration of nitrogen dioxide. When nitric oxide (NO) emissions are high enough, the NO released into the atmosphere converts a large portion of ozone to nitrogen dioxide (Hashim et al., 2021). In addition, in all three cities, when the concentration of nitrogen dioxide increased, we saw a decrease in the amount of ozone concentration. In addition, during the Covid-19 era, many industries that produced primary pollutants, including carbon monoxide, nitrogen dioxide, and sulfur dioxide, were not on the closure list or were telecommuted. Despite the decline in the performance of some activities, important sectors such as manufacturing plants, industrial and mining centers, agriculture, and public transportation have continued to operate even during severe restrictions. The mean difference between the concentrations of nitrogen dioxide before and after the outbreak of Covid-19 was positive. However, this average difference is small. However, the concentration of nitrogen dioxide is slightly increased, especially in cold seasons; Therefore, it can be said that ozone concentration has decreased.

Keywords: Covid-19, Air Pollutants, Remote Sensing, Sentinel-5.


















 

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Pandemic Covid-19 (Corona); Tehran's resilience against it

Nader Shohani; Assistant Professor, Department of Geography and Urban Planning, Payame Noor University. Tehran Iran
Lotfali College Potter; Associate Professor, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran
Sajjad Darabi; PhD Student, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran
Saeed Yousefi Babadi; PhD student, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran

Abstract
One of the dangers that has caused cities to face a serious crisis is the outbreak of Covid-19 disease. The corona pandemic has taken cities out of their normal routine. Therefore, cities seek to return to their past conditions and urban resilience as soon as possible. Research Method In this descriptive-analytical study, using field survey, four economic, social, managerial-institutional and infrastructural dimensions in the form of 29 items have examined the resilience of Tehran against Corona pandemic. In research, support and advocacy for affected businesses, insurance coverage, support for affected manufacturing sectors, are in the most unfavorable situation. The results obtained from the final table of Vikor technique show that the economic index with a score of 1 is the most important component of resilience against coronavirus, which is lower than other components of resilience. After that, the managerial-institutional component with a score of 0.94 and the infrastructure component with a score of 0.92 in the next ranks are the most important components of Tehran's resilience against coronavirus. The results show that the metropolis of Tehran is not in a favorable position in relation to the corona virus and is not resilient to selected indicators and the economic index has the most impact and the social index has the least impact on the resilience of Tehran.

Keywords: Urban Resilience, Covid 19, Pandemic, Tehran



Pandemic Covid-19 (Corona);
Tehran's resilience against it

 

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Evaluation of the effect of particulate matter and vegetation on the formation of heat and cold islands in Tehran
Seyed Kamyar Mortazavi Asl: PhD Student in Urban Planning, Islamic Azad University, UAE
Dr. Navid Saeedi Rezvani: Assistant Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Qazvin, Iran
Dr. Mahmud Rezaei:  Associate Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Tehran, Iran

Abstract:
Global warming and the heat islands of cities are one of the biggest challenges in the world today. Cold islands is a word that stands in front of heat islands and refers to areas of the city that have lower temperatures than the surrounding areas. In this study, in order to investigate the factors affecting the formation of cool and heat islands of the city, it was first obtained by using Landsat image processing and using the single-channel surface temperature algorithm. Then to investigate the parameters affecting the land surface temperature changes; Criteria for changes in particulate matter and changes in vegetation were considered. The NDVI index was used for vegetation and the algorithm proposed by Saraswat et al. was used for the amount of particulate matter. According to the results, the highest-ranking neighborhood for heat islands were in Bustan, Shahid Bagheri township and the airport, respectively, and the lowest amount of cool islands were in Baharan, Niavaran and Darband, respectively. Pearson coefficient obtained from the relationship between surface temperature and vegetation was -21.29%, which indicates the inverse relationship between temperature and vegetation, as well as the amount of vegetation index in hot and cold regions. Regarding the relationship between land surface temperature and air pollution, the correlation between these two parameters was equal to 19.31% and comparing the pollution index in areas with cold and warm islands showed that there is a significant relationship between reducing air pollutants and cold islands but the opposite is not true.

Keywords: Cool Islands, Tehran, LST, Air Pollution

 

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Investigation of Construction Wastes Release in Roadside Using AHP

Introduction
Although construction waste is an integral part of municipal waste, due to the differences between this waste and waste and environmental issues, a suitable model should be designed for optimal productivity and acquisition of resources. The increasing volume of urban materials and rubbish, especially the rubbish from the destruction of their construction and worn-out urban textures, has created many problems in large cities, as well as environmental problems that have arisen due to unprincipled and unprofessional disposal of these materials. Has attracted these materials. Research shows that the amount of this waste is equal to 10 to 15% of the total materials used in construction operations. This amount is much higher than what is estimated by the estimators.

Data and research method
In Iran and other developing countries, construction and construction waste is a major part of municipal waste, which in addition to high costs for its disposal, also has adverse consequences on the environment. The volume of this garbage is so much that now this issue has become a social and environmental problem not only in Iran but also in developed countries due to the limitation of natural resources and preservation of national capital for future generations as well as environmental protection And it is necessary because with proper management and efficient planning and reducing the volume of construction waste, not only the waste of natural resources and national capital is prevented, but also additional and ancillary costs are reduced and it is economically beneficial.
In this study, first, the effective criteria in selecting the burial site in the study area are determined. These criteria are reviewed and used by various standards, including standards related to the Environmental Protection Organization, the Ministry of Interior and international standards, as well as by reviewing resources and studies on the process of locating landfills in the country and abroad and by examining the conditions of the region. The study and the influencing factors are compiled in the study area. The layers related to each criterion in the relevant table will be prepared, processed and converted from the relevant organizations. The method of this dissertation is applied-modeling in terms of purpose, because on the one hand, the concepts and rules related to the field of knowledge are carefully analyzed, and on the other hand, the relationships between these concepts and rules are evaluated and determined by experts. In this study, there is a need to use the decision theory method to evaluate and investigate the status of construction waste disposal along roads to increase trust and confidence in decision making.
The data analysis tools of this research are SPSS, Expert Choice and Matlab for conducting the research. In the research process, after data collection, the next step involves data analysis. Cronbach's alpha coefficient was used to evaluate the reliability of the localization tools of the research components. In order to describe the data, the mean and standard deviation of the research data have been used.

The four-step process of multi-criteria decision-making process and fuzzy logic calculations to investigate the dumping of construction debris along roadsides is as follows:
Step 1 - Modeling causal relationships based on similarity to the ideal solution
Step 2 - Parallel comparisons and determining the weight of causal relationships based on the evaluation of decision options between the criteria for assessing the status of construction debris on the sidewalks,
Step 3 - Prioritize Based on Causal Relationships Based on Evaluation of Decision Options
 Step 4 - Fuzzy Prioritization and Final Analysis Investigation of Construction Waste Disposal Status

Result and Discussion
The most important results of the study of the dumping of construction debris along the roadsides are that,
1- The most important criterion in the cluster "Environmental factors of construction waste disposal" with code (A), "Soil pollution in the city" with code (AB) with fuzzy network weight of 0.096; And
2- The most important criteria in the cluster "Applications of GIS in urban management of construction debris disposal" with code (B), "Urban green space management" with code (BA) with fuzzy network weight equal to 0.191; And "Urban management related to health" with code (BB) with fuzzy network weight equal to 0.120; Were calculated. on the other hand,
3- The most important criterion in the cluster "Economic factors of construction waste disposal" with code (C), "Construction waste management training cost" with code (CD) with fuzzy network weight equal to 0.123; Prioritized,

conclusion
The results of the present study can be said that, after reviewing the theoretical foundations of the research and reviewing the research background, it was found that due to research gaps in the fields of economic factors of construction waste disposal, GIS applications in urban management, construction waste disposal, environmental factors, Utilization of a combined fuzzy multi-criteria decision-making methodology to investigate the status of construction debris dumping along roadsides; It is possible to realize the innovation of the present research in filling the mentioned research gaps.

Key words: Construction Debris, Civil Waste Management, Multi-Criteria Decision Making, Karaj.

 

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Revealing surface reflection forcings of land cover in Lorestan province using MODIS sensor products

Introduction
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.   
                                                                                                                  
materials and Method                                                                                                                
 In this study, to reveal the relationship between land cover levels and different land use classes, cross-information matrix analysis was used in the ARC-GIS software platform. Since one of the main objectives of the study was to investigate and reveal the albedo inductions of land cover classes in Lorestan province, so the relationship between these two factors was investigated by cross-matrix analysis technique. In this regard, two sets of data were used. The first set of data was related to land cover classes of MODIS sensor composite product with a spatial resolution of 1 km and hierarchical data format (MCD      
   12(Q2 (MCD product) which was obtained from the database of this sensor

Conclusion
 Land cover classes or perhaps it can be said that land use is one of the most important shapers and determinants of climate near the earth. In this study, it was observed that in general, 5 major land cover classes in the province are separable, among which rangeland and forest lands account for 85% of the total land cover of the province. On the other hand, it was seen in this study that the average spatial albedo of the province in spring, autumn and winter is about 0.2, which is very close to the global value of this component, but in winter the average value of this index in the province reaches 0.3, which can be increased Shows attention. The five land cover classes in the province had their own unique albido induction in winter, which was separable and distinct from each other, but in spring, summer and autumn, no significant distinction of albido induction of these land cover was revealed.                                                                                                                                       

Keywords: Land cover changes, Land surface temperature, Cross-information analysis matrix, Lorestan province












 

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Space-based quantification of anthropogenic CO₂ emissions in an urban area using “bottom-up” method
(Case study: Isfahan Metropolitan)
Abstract
Increasing consumption of fossil fuels in urban areas emits enormous amounts of greenhouse gases into the atmosphere. Therefore, the study of carbon dioxide (CO₂) emissions from urban areas has become an important research topic. The main purpose of this study is space-based quantification of carbon dioxide emissions driving from fossil fuel combustion in different source sectors in Isfahan. To achieve it, in the present study, the "bottom-up" method was used to quantify the carbon dioxide gas emission based on its production sources sectors. In this method, the amount of emission was measured distinctly for different sources of energy consumption and consequently the spatial distribution map the CO₂ emission was generated. The results of this study revealed that the total amount of carbon dioxide emissions driving from fossil fuels is 13855525 tons per year in Isfahan. Separately stationary sectors of power plant, housing and commercial and mobile sources including road and railroad and existing agricultural machinery were responsible for emitting 50.61, 21.78, 17.18, 4.92, 4.37, and 1.14% of CO₂, respectively. In conclusion, through applying the bottom-up method and CO₂ emission distribution mapping based on different source sectors, mitigation measures can be applied more efficiently in urban planning.
Key words: Greenhouse gas (GHG), Fossil fuel combustion, Mobile and stationary source of energy consumption, climate change, Mitigation strategies

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 A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data

Kaveh Bapirzadeh¹, Hesam Seyed kaboli^*2, Leila Najafi^3
1 MSc student, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
^*2 Associate Professor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran. Corresponding Author: Email: hkaboli@jsu.ac.ir
³ Instructor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
Abstract
This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected synoptic stations in climates with different topographic characteristics were received daily from the European Centre for Medium-Range Weather Forecasts (ECMWF) website. Bias correction of these data was performed using 5 quantitative mapping methods based on observational data in R software environment. Two-part evaluation and Taylor diagram were used to compare the performance of different methods. The results showed that the performance of the quantification mapping method depends on the performance functions, set of parameters and climatic conditions. In general, non-parametric methods of multiple mapping have better performance than parametric methods, so that the best performance is related to QUANT and RQUANT methods, among which DIST method has the weakest performance.

Keywords: Quantitative mapping, Bias correction, ERA5, ECMWF
 

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Considering the increase in housing construction in developing societies such as Iran, it is necessary to address the issue of reducing construction accidents, especially in metropolises, and related safety measures with the help of emerging technologies. Therefore, the main goal of the current research is to investigate the use of Internet of Things to monitor and control high-risk points in order to reduce accidents and improve safety in the spaces of construction site in Tehran.
In this applied research, first, a library study was conducted regarding the concept and application of Internet of Things in the safety field of the construction industry. Then, high risk points and activities were identified. After that, in the field study phase, this list was corrected and completed by 52 competent building safety consultants. After that, ten semi-structured interviews were conducted with safety experts and knowledgebale in the field of IoT. Therefore, effective solutions based on Internet of Things were extracted to control and monitor high risk points. Also, in this regard, the current situation and required platforms were explained from the aspects of technology, organization, cost and outsourcing.
In fact, the main findings of this research, in the form of a conceptual model, show that paying attention to the stages of choosing the incident, choosing the desired point and activity, determining the appropriate solution for the determined situation (monitoring the amount of movement and health of the structure, monitoring the proximity of flammable materials with other materials, monitoring the proximity of people and machines and preventing the continuation of movement and determining the limits around the openings) and checking the required platforms (infrastructure, support, accreditation, culture, budget, employers and law), respectively, in order to design and implement IoT-based safety systems in the spaces of construction sites is vital.

 

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Synoptic analysis of the changes trend of the share of systems due to the Sudan low
In the cold period of the Persian Gulf coast during 1976-2017


 Introduction
In the Ethiopian-Sudan range forms the low pressure system without front in the cold and transition seasons that is affecting the climate of the adjacent regions by crossing the Red sea. Based on the evidence in the context of Iran, studying Sudan low was first begun by Olfat in 1968. Olfat refers to low pressures which are formed in northeastern Africa and the Red Sea and then pass Saudi Arabia and the Persian Gulf, enter Iran, and finally, cause rainfall. The most comprehensive research specifically examining Sudan low, was the work carried out by the Lashkari in 1996. While he studying the floods that occurred in southwestern of Iran, he was identified Sudan low by the most important cause of such flooding and he explained how they are formed, and how these low-pressure systems were deployed on the southwest of Iran.

 Materials and methods
The study period with long-term variations was considered from 9.5 to 11 years based on solar cycles. Precipitation data for 13 synoptic stations are considered above 5 mm in south and southwestern Iran. With three criteria were determined for the days of rainfall caused by each type of atmospheric system. The visual analysis of high and low altitude cores and geopotential height at 1000 hPa pressure level (El-Fandy, 1950a; Lashkari, 1996; 2002) were considered based on the aim of the study. Accordingly, the approximate locations of activity centers, as well as the range of the formation and displacement of the Sudan system were initially identified based on the location of the formation of low and high-pressure cores. Then, the rainy days due to the Sudan system in January were separated from the precipitation of the other atmospheric system.

 Results and discussion
According to the selected criteria in the forty-year statistical period, 507 precipitation systems were identified with different continuities that led to precipitation in the northern coast of the Persian Gulf. The pattern of independent Sudan low rainfall was responsible for 77% of the precipitation in the Persian Gulf. Decade frequency share of Sudan low was lower in the first decade (16%) compared to the next three decades. This system of rainfall was more activated during the second and third decades compared to the first decade. However, rainfall changes were not evident in the mid-decade. Independent Sudan low precipitation provide 25% and 27% of the cold season precipitation of the Persian Gulf during the second and third decades respectively. In accordance with the 24th solar cycle, at the end of the study period, the Sudan low was more effective on the Gulf coast than ever before. During this decade, 125 cases of Sudan low rainfall was recorded for the Persian Gulf. Thus, the frequency of Sudan low during the fourth decade was about 31%, which was higher than in the rest of the decade. Overall, the Sudan low rainfall was repeated 151 times for 2 days rainfall, during the statistical period studied. This Precipitation has increased over the last decades compared to other periods.

 Conclusion
The severe variability of rainfall along the timing and location of the permanent Persian Gulf coasts can have a significant impact on the economic and agricultural behavior of the Gulf population in the three provinces of Ahwaz, Bushehr and Hormozgan.The purpose of this study was to evaluate the precipitation changes due to Sudan low in the Persian Gulf coastal region during the cold period. The results of this study showed that the role of integration patterns in influencing the precipitation of the Persian Gulf coast has decreased with the strengthening and further activation of the Sudan low system during the last two decades. That way, about 77percent of the region's rainfall is provided by independent Sudan low. At the end of the course (in accordance with 24th solar cycle activity) the Sudan low system was more active than before. Although the Sudan low activity was different at each station during the period studied, but in the historical passage incremental and decade's positive behavior of Sudan low was common to all stations. Evaluation of changes in rainfall duration shows that the pattern of precipitation with 2days duration is more frequent than the patterns of one to several days.

Keywords: Sudan low- Solar cycle- Persian Gulf.





 

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Investigation of the effects of Covid-19 pandemic on UHI in residential, industrial and green spaces of Tehran

 Abstract
Rapid urbanization in recent decades has been a major driver of ecosystems and environmental degradation, including changes in agricultural land use and forests. Urbanization is rapidly transforming ecosystems into buildings that increase heat storage capacity. Loss of vegetation and increase in built-up areas may ultimately affect climate variability and lead to the creation of urban heat islands. The occurrence of natural disasters such as flood, earthquake … is one of the most effecting factors on the changes in intensity of urban heat islands. So far, a lot of research has been done on how it is affected by various types of natural disasters such as floods, earthquakes, droughts and tsunamis.
Two major environmental challenges for many cities are preventing flooding after heavy rains and minimizing urban temperature rise due to the effects of heat islands. There is a close relationship between these two phenomena, because with increasing air temperature, the intensity of precipitation increases. Drought is also a phenomenon that is affected by rainfall, temperature, evapotranspiration, water and soil conditions. One of the major differences between drought and other natural disasters is that they occur over a longer period of time and gradually than others that occur suddenly. Another natural disaster is the tsunami, which increases the area of water by turning wetlands into lakes, thereby increasing the index of normal water differences, which has a strong negative relationship with surface temperature. Ecosystems in urban areas play a role in reducing the impact of urban heat islands. This is because plants and trees regulate the temperature of their foliage by evaporation and transpiration, which leads to a decrease in air temperature.
Applying the locked down of the Covid-19 pandemic since the spring of 2020 has led to the global restoration of climatic elements such as air quality and temperature. In this study, the effects of Covid-19 locked down on the intensity of urban heat islands due to the limitations in industrial activities such as factories and power plants and the application of new laws to reduce traffic in Tehran were investigated. In this regard, the Landsat-8 satellite taken from a part of Tehran city has been used.

Materials and Methods
In order to investigate the effects of locked down in the spring of 2020 on the intensity of urban heat islands; the status of UHI maps in Tehran during the same period of locked down in three years before and one year after has been studied. The proposed method in this paper consists of two main steps. The first step is to generate UHI maps using land surface temperature (LST), normalized difference vegetation index (NDVI) and land use / land cover map analysis. In the second step, in order to analyze the behavioral changes in the intensity of urban heat islands during locked down and compare it with previous and subsequent years, changes in the intensity of UHIs are monitored.
UHI maps consist of three classes of high, medium and low intensities urban heat islands, which are based on performing the rule based analysis on land surface temperature characteristics and normal vegetation difference index derived from Landsat-8 satellite images as well as land use / land cover map. LULC maps are produced by support vector machine classification method consisting of three classes of soil, building and vegetation. In order to calculate the spectral features used in the rule based analysis, atmospheric and radiometric corrections must first be made on the red, near-infrared, and thermal spectral bands of the image captured by the Landsat-8 satellite. Then, vegetation spectral indices including NDVI and PV indices are generated.

Disscussion of Results
The capability of the proposed algorithm in this paper is first evaluated in the whole area covered by satellite images taken from the city of Tehran, and then in three areas including residential, industrial and green spaces. The data used in this article are images taken by the OLI sensor of Landsat-8 satellite in the spring of 2017-2021.
In the first step of the proposed method, maps of urban heat islands are generated based on multi-temporal satellite images of Landsat-8 taken in the years 2017to 2021 in the MATLAB programming software. Then, by comparing pairs of UHI maps in each of the residential, industrial and green space study areas, the trend of changes in the intensity of UHI is analyzed and the effects of locked down application in 2020 are evaluated.
The results of changes detection in urban heat islands in the period under consideration in this study showed that the percentage of areas that are in the class of high UHI in 2020 due to locked down of pandemic Covid-19 compared to the average of three years before that is 55.71%, has a decrease of 17.61%. The percentage of areas in the class of medium UHI intensity in 2020 due to locked down compared to the average of three years ago, which is 39%, increased by 4.8%, and in 2021 this amount again has decreased to less than the average. Also, the percentage of low intensity UHI class in 1399 compared to the average of three years ago, which is 5.3%, has increased by 12.8%.

Conclusion
In this study, the effect of locked down application due to the Covid-19 virus pandemic, which was applied in Iran in the spring of 2020 is investigated on the intensity of  urban heat islands in a part of Tehran city and three selected areas with residential, industrial and green space. Detection of changes in the intensity of urban heat islands was done based on the post-classification method and on the UHI classification maps related to the years 2017 to 2021. In order to produce UHI maps, in addition to the land surface temperature, the amount of vegetation index and the type of land use / land cover class were also used in the form of a set of classification rules.
Comparing the results of the study areas of residential, industrial and green spaces, it is important to note that the rate of reduction of the area of UHI with high intensity in the residential area is 5.25% more than the industrial area and 6.1% more than the green space. However, the reduction of locked down restrictions in 2021 had the greatest effect on the return of the area of ​​the high UHI class and caused the area of ​​this class to increase by 23% compared to 2020. These results indicate the fact that restrictions on the activities of industrial units such as factories and power plants and the application of new laws to reduce traffic, despite the same weather conditions in an area have been able to significantly reduce the severity of urban heat islands.

 Keywords: Urban Heat Islands, Land Surface Temperature, Vegetation Index, Change Detection, Covid-19

 

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Energy Information Administration (EIA). 2022.  Natural gas explained. https://www.eia.gov/energyexplained/natural-gas/use-of-natural-gas.php#:~:text=The%20United%20States%20used%20about,of%20U.S.%20total%20energy%20consumption
Energy Information Administration (EIA). 2022. Natural Gas Consumption by End Use. https://www.eia.gov/dnav/ng/ng_cons_sum_dcu_nus_a.html
IEA. 2020. Gas 2020. https://www.iea.org/reports/gas-2020/2021-2025-rebound-and-beyond
Cinq-Mars, TJ.; T. Kropotova, M. Morgunova, A. Tallipova, and S. Yunusov. 2020. Leak Detection and Repair in the Russian Federation and the United States: Possibilities for Convergence. Stanford US-Russia Forum Journal.
Weller, ZD.; DK. Yang, and JC. von Fischer. 2019. An open source algorithm to detect natural gas leaks from mobile methane survey data. PLoS One,14(2):e0212287.
SHAHEDI, AS.; MJ. ASSARIAN, O. KALATPOUR, E. ZAREI, and I. MOHAMMADFAM. 2016. Evaluation of consequence modeling of fire on methane storage tanks in a gas refinery.
Costello, KW. 2014. Lost and unaccounted-for gas: Challenges for public utility regulators. Util Policy,29:17–24.
Arpino, F.; M. Dell’Isola, G. Ficco, and P. Vigo. 2014. Unaccounted for gas in natural gas transmission networks: Prediction model and analysis of the solutions. Journal of Natural Gas Science and Engineering,17:58–70.
Weller, Z.D.; SP. Hamburg, and JC. von Fischer. 2020. A national estimate of methane leakage from pipeline mains in natural gas local distribution systems. Environmental science & technology, 54(14):8958-8967.
Meland, E.; NF. Thornhill, E. Lunde, and M. Rasmussen. 2012. Quantification of valve leakage rates. AIChE journal, 58(4):1181-1193.
Wagner, H. 2004. Innovative techniques to deal with leaking valves. Technical Papers of ISA, 454:105-117.
Kaewwaewnoi, W.; A. Prateepasen, and P. Kaewtrakulpong. 2010. Investigation of the relationship between internal fluid leakage through a valve and the acoustic emission generated from the leakage. Measurement, 43(2):274-282.
Zhu, SB.; ZL. Li, SM. Zhang, and HF. Zhang. 2019. Deep belief network-based internal valve leakage rate prediction approach. Measurement, 133:182-192.
Panahi, S.; A. Karimi, and R. Pourbabaki. 2020. Consequence modeling and analysis of explosion and fire hazards caused by methane emissions in a refinery in cold and hot seasons. Journal of Health in the Field.
Plant, G.; EA. Kort, C. Floerchinger, A. Gvakharia, I. Vimont, and C. Sweeney. 2019. Large fugitive methane emissions from urban centers along the US East Coast. Geophysical research letters, 46(14):8500–8507.
Akhondian, M.; S. MirHasanNia. 2017. Biodiversity of microalgae, a potential capacity in biological and environmental technologies. Journal of Human Environment and Health Promotion,41:39–70.
Defratyka, SM.; JD. Paris, C. Yver-Kwok, JM. Fernandez, P. Korben, and P. Bousquet. 2021. Mapping urban methane sources in Paris, France. Environmental Science & Technology,55(13):8583-8591.
Mohammadi Ashnani, M.; T. Miremadi, A. Danekar, M. Makhdoom Farkhonde, and V. Majed. 2020. The Policies of Learning Economy to Achieve Sustainable Development. Journal of Environmental Science and Technology,22(2):253–274.
Gioli, B.; P. Toscano, E. Lugato, A. Matese, F. Miglietta, A. Zaldei, and FP. Vaccari. 2012. Methane and carbon dioxide fluxes and source partitioning in urban areas: The case study of Florence, Italy. Environmental Pollution,164:125-131.
Moriizumi, J.; K. Nagamine, T. Iida, and Y. Ikebe. 1998. Carbon isotopic analysis of atmospheric methane in urban and suburban areas: fossil and non-fossil methane from local sources. Atmospheric Environment, 32(17):2947-2955.
Zazzeri, G.; D. Lowry, RE. Fisher, JL. France, M. Lanoisellé, CSB. Grimmond, and EG. Nisbet. 2017. Evaluating methane inventories by isotopic analysis in the London region. Scientific reports, 7(1):1-13.
Wever, JL.; GJL. Van Orizande, WB. Rademaker, and GJ. Van Schagen. 2002. Applicability of the Hi-Flow sampler in reducing methane emissions from a technical/economical point of view. Feasibility study; Toepasbaarheid Hi-Flow sampler bij reductie methaanemissie op technisch/economische gronden. Haalbaarheidsstudie.
Bacharach INC. 2015. Hi flowR sampler for natural gas leak rate measurement.
Connolly, JI.; RA. Robinson, and TD. Gardiner. 2019. Assessment of the Bacharach Hi Flow® Sampler characteristics and potential failure modes when measuring methane emissions. Measurement, 145:226–233.
Khorasan Razavi Gas Company. 2019. Determining the statistical population and sample size of field measurements to estimate normal emission inventory Greenhouse gases in the gas network of Khorasan Razavi province.



























Estimation of methane gas leakage from Mashhad urban landfills and evaluation of economic and environmental effects
Abstract
This study, which was conducted in 8 urban gas areas of Mashhad; At first, descriptive statistics of the state of Mashhad urban gas regulators and different leakage modes were presented; In order to analyze the collected data and investigate the causes of leakage, the relationship between 5 variables and the amount of leakage from gas regulators was tested with the Statistical Package for the Social Sciences (SPSS) V.26 software; These 5 variables are: regulator equipment/connections, regulator operation age, regulator service type (domestic, industrial and commercial), urban area and different seasons of the year.
The results of the analysis showed that there was a significant difference between the type of equipment/connections and leakage. (P-Value = 0.0001). Also, a significant difference was observed among other variables of the research (the operation age of the regulator, the type of regulator service (domestic, industrial and commercial), the urban area and different seasons of the year) with the leakage rate (P-Value=0.0001); The pressure drop due to the greater demand of gas consumption in the winter season has reduced the amount of leakage compared to other seasons; The influence of the age of distribution network equipment/connections due to wear and tear and longer life will aggravate the amount of methane gas leakage; Also, the amount of leakage in commercial places had a significant difference with other types of uses; Being in an urban area has also increased the amount of methane gas leakage compared to other areas; The type and quality of equipment and connections as the main and influential factor in methane gas leakage should be considered by managers and officials in this field of work.
Keyword: Methane, Riser, Urban area, Environmental effects, Economy Effects, Gas, Emission


 

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Explaining the spatial patterns of drought intensities in Iran

Abstract
Recognition of spatial patterns of drought plays an important role in monitoring, predicting, confronting, reducing vulnerability, and increasing adaptation to this hazard. This study aims to identify the spatial distribution and analyze the spatial patterns of annual, seasonal, and monthly drought intensities in Iran. For this purpose, the European center Medium-Range Weather Forecast (ECMWF) data for the period 1979-2021 and the ZSI index were used to extract the drought intensities. To achieve the research goal and explain the spatial pattern of the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran’s Index, and hot spots were used. The results of the global Moran’s I showed that with increasing intensity, the spatial distribution of drought events has become clustered. The spatial distribution of the local Moran’s Index and hot spots also confirms this. Very clear contrast was observed in the local clusters of high (low) occurrence as well as hot (cold) spots of severe (Extreme) yearly droughts in the south, southeast, and east. In autumn, weak to Extreme droughts show a southeast-northwest pattern. But in spring and winter, the spatial pattern of drought is very strong as opposed to severe and moderate drought. Despite the relatively high variability of maximum positive spatial Autocorrelation of severe and Extreme monthly droughts, their spatial pattern is almost similar. The spatial clusters of severe and very severe droughts in the northwest, northeast, and especially on the Caspian coast, are a serious warning for the management of water resources, especially for precipitation-based activities, such as agriculture.
Introduction
Drought or lack of precipitation over some time is the most widespread natural hazard on the earth compared to its long-term average. This risk negatively affects various sectors such as hydropower generation, health, industry, tourism, agriculture, livestock, environment, and economy. To reduce these negative or destructive effects, it must be determined how often drought occurs during the period and in which areas it is most severe. Doing so requires determining the characteristics of the drought. These characteristics include area, intensity, duration, and frequency of drought. Discovering the geographical focus, recognizing the pattern governing the frequency of occurrence and temporal-spatial distribution as well as changes in the dynamics of this hazard facilitate an important role in drought monitoring, early warning, forecasting, and dealing with these potential hazards; this information can be used to create a drought plan by providing analysts and decision-makers with ideas about drought, helping to reduce the negative and vulnerable effects and ultimately make it easier to protect or replace for greater adaptation. Many researchers have been led by these approaches to the use of statistical analysis. Numerous studies have been conducted in the study of climatic phenomena such as drought with space statistics techniques in various regions, including China, India, South Korea, and even Iran. Part of the domestic research on spatial patterns of drought is without the use of spatial statistics and a limited number of others who have used these analyzes have only studied the overall intensity of drought and have not studied the spatial patterns of different drought intensities. The main purpose of this study is to identify the distribution and spatial patterns of drought intensities in Iran using spatial analysis functions of spatial statistics based on the frequency of drought intensities (Extreme, severe, moderate, and weak) with yearly, seasonal and monthly multi-scale approach. Therefore, this study will answer the questions: a) What is the spatial distribution of drought intensity data in Iran? And b) What is the variability of spatial patterns of Iranian droughts at different time scales?
Material &Method
ERA5 monthly precipitation data for a period of 43 years from 1979 to 2021 were used for this study. an array of dimensions of 78×59×504 of data were formed in MATLAB software in which 78×59 is the number of nodes with a spatial resolution of 0.25 degrees and 504 represents the month. After creating the database, the ZSI index was used to calculate the severity of drought in annual, seasonal, and monthly comparisons. Finally, to achieve the research goal and explain the spatial pattern governing the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran I and hot spots was used.
Discussion of Results
Due to its ecological conditions, geographical location, and location in an arid and semi-arid region of the world, Iran is among the most vulnerable countries due to natural hazards, including drought. It has experienced many severe droughts in the last century. The occurrence of drought and its effects is one of the major challenges of water resources management in this century. The results of the Global Moran’s Index for all three annual, seasonal, and monthly scales showed a highly clustered pattern of drought events in the country. Spatial clustering of the occurrence of severe and Extreme yearly droughts in the eastern, southeastern, and southern regions is also an interesting result. These conditions are due to low precipitation and high spatial variation coefficient in these areas. This contrast of spatial clusters of drought intensities indicates the relationship between drought and temporal-spatial anomalies of precipitation so that with increasing precipitation, spatial variability of precipitation decreases, and consequently spatial homogeneity of precipitation increases. severe and moderate-intensity spots in the south-southeast in autumn and spring can be affected by fluctuations in the beginning and end of the monsoon season in South Asia due to the high variability of atmospheric circulation at the beginning and end of precipitation in these areas. Some studies have also shown the relationship between precipitation in these areas and the monsoon behavior of South Asia. Extreme drought events in winter and spring have had a positive spatial correlation pattern in the southwest, west, and northwest. However, precipitation at this time of year is concentrated in these areas. Warm clusters or concentrations of very severe drought events in the northern strip of the country, especially in the Caspian region, can be due to the high variability of precipitation at the beginning of the annual precipitation season (late summer and early autumn).  Observations of these conditions in the northern strip indicate that an event with a high frequency of severe droughts, even in rainy areas, should not be unexpected. Spatial clusters of Extreme, severe, moderate, and weak drought every month using both local Moran and hot spots statistics show the fact that in Iran, the most severe droughts have occurred in the western, northwestern, and coastal areas of the Caspian Sea. However, the absence of severe droughts or spatial clusters has been the occurrence of low drought in the southeast and to some extent in the south. On a yearly scale, the south, southeast, and east have played a significant role in the spatial cluster of severe and extreme droughts. So that these areas of the country have had positive spatial solidarity. However, in these areas, negative spatial correlation prevailed in the autumn for severe drought. This may indicate an anomaly and a tendency to concentrate more precipitation in Iran, as well as many changes in seasonal and local precipitation regimes. According to the research results, a high incidence of severe and extreme drought on all three scales (monthly, seasonal and annual) even in the wettest climate of the country (northern Iran, especially the southern shores of the Caspian Sea) shows that High-intensity droughts can occur in all parts of the country, regardless of the weather conditions.
Keywords: Natural hazards, spatial patterns, Moran statistics, spatial autocorrelation, hot spots


 

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One of the most important issues that has always affected the Iranian climate and has left many socio-economic consequences and financial losses climate change is. On the other hand  Sea level pressure is one of the most important climatic elements that can affect other climatic elements such as temperature, humidity and wind. The study aimed to evaluate CMIP5 models based on CORDEX and Verdai dynamics Seasonal pressure anomalies in Iran among CMIP5 models based on CORDEX project dynamic models BCC-CSM, HadGEM2-ES, GFDL and MIROC model HADGEM2-ES had a higher level of correlation and efficiency than other models.
The data of 36 synoptic milestones during the statistical period (1960-2005), the data of the HadGEM2-ES model were applied by using the CORDEX model and the RCPs scenarios for the two historical periods (1960-2005) and predicted during Three periods of near future (2040-2011), middle future (2070-2041) and distant future (2099-2071) were used. Six methods R2, MAE, MBE RMSE, t-Jacovides and t-Jacovides / R2 ratio were used to evaluate the model performance. The results showed that the model has good performance in low altitude areas. Seasonal anomalies in all seasons, scenarios and time periods studied are positive and winter shows the maximum pressure anomalies between seasons.
The maximum seasonal pressure anomaly of Iran in all seasons, scenarios and periods studied corresponds to the altitudes, including its epicenter in the Alborz and Zagros heights and high geographical offerings and the minimum pressure anomaly corresponding to low and low areas such as Khuzestan plain and The southern coast of the country.