جستجوی مقالات مرتبط با کلیدواژه « انرژی باد » در نشریات گروه « جغرافیا »

This study was conducted with the general purpose of developing strategies for the use of renewable energy in the agricultural sector in Bushehr province. In this study, first, using analytical studies and literature, the subject of the four SWOT points, namely strength, weakness, opportunity and threat, were identified and prioritized using the AHP technique. The statistical population of the study were subject-aware experts and specialists in relevant organizations who were purposefully selected for the study. Data analysis was performed using SWOT-AHP technique using Expert Choice software. Findings showed that in evaluating the criteria, strengths, weaknesses, threats, opportunities were the first to fourth priorities that the weights obtained from the results of these points indicate the dominance of risky space over space. useful. In addition, in prioritizing strategic areas, the results showed that the first SO strategy is aggressive strategy (maximum-maximum), the second strategy is ST strategy is contingent strategy (maximum-minimum), the third WO strategy is adaptive strategy (minimum-maximum strategy). And finally, the last strategy in the subject under consideration is the WT strategy, that is, the defense strategy (at least - at least). In general, the results of this research can provide new insights for energy and environmental policy makers.

The increasing importance of fossil fuels in the last century and the lack of non-renewable resources on earth has led to the extinction of human life. In recent years, there has been a shift towards cleaner methods where energy pollution from non-renewable sources is minimized. Each climate has its own conditions and characteristics, and this is the trend towards sustainable architecture in the traditional architecture of Iran. The importance of using energy to provide solutions increases at all levels. Due to its location on the sun belt, Iran is one of the suitable areas to benefit from the sunlight, and it is possible to increase the comfort function by taking advantage of the climatic features and the features of the traditional elements of sustainable architecture, taking into account efficiency and productivity. important indicators such as: orientation based on three institutionalized rune categories and models for city and house structure in Iran, walls in terms of materials and thickness, form of roofs, color and openings of external surfaces of traditional houses, etc. were used so that the amount of consumption It reduced the energy so as to be able to get rid of the environmental problems of the city.

The research method in this article is descriptive-analytical, and the library method was used to collect information and data.

By examining the theories of logical reasoning for the documentation of the texts, in this method it is tried to spread the qualitative and conceptual strategy issues in this research, and at the end of the research, the indicators of sustainability in the traditional houses of Iran were presented; As he got ideas and lessons from the energy efficiency of traditional Iranian houses to achieve a desirable design for today's modern architecture.

The construction industry has a significant contribution to energy consumption. Therefore, developed countries in this field have offered a strategic energy plan by voluntarily applying energy certificates approved by the Green Buildings Council. Since 2000, Iran has presented its energy audit program by voluntarily applying the building energy label. Unfortunately, this energy certificate has not been able to significantly contribute to maintaining energy in this industry. Therefore, the present study used a qualitative descriptive-analytical method to compare existing standards between the energy strategic plan of the Green Buildings Council and Iran's energy audit program. The three factors of saving based on human design, saving for all resources, and biogeochemical cycle were compared as the goals of both programs, and the reasons for the differences around them were analyzed. The results of these analyses showed shortcomings in the standardization of savings based on all resources and biogeochemical cycles in Iran's energy label certificate compared to the certificate approved by the Green Buildings Council. In such a way that in the rating of Iran's energy label, user education and saving of water resources and solutions for using alternative sources of energy such as geothermal energy and sun and wind and biogas fuel and the return of construction materials and materials to the material biogeochemical cycle are not considered, as well as supporting support. There has been no incentive such as tax exemptions in these sectors.

The study of energy geopolitics entails examining the role that energy plays in geopolitical dynamics and power competitions. The global economy and security place considerable importance and emphasis on energy, to the extent that it serves as an indicator of security levels. This significance applies to both oil-producing and oil-consuming countries, prompting them to carefully manage their situations to ensure they are not endangered by developments in global competition. The objective of this research is to investigate the geopolitical developments surrounding energy and their influence on Saudi Arabia's inclination to diversify its economic resources.

In the realm of energy geopolitics, nations reliant on fossil fuel consumption have shifted their focus towards substituting it with renewable sources as a means of mitigating the vulnerabilities stemming from their dependence on conventional fuels. However, the altered global energy consumption pattern and the emergence of renewable energy have introduced novel risks for fossil fuel producing countries within the domain of energy geopolitics, thereby jeopardizing their national interests. Consequently, countries with substantial crude oil production, such as Saudi Arabia, have initiated endeavors to align their economic strategies with these transformations through comprehensive analysis of prevailing circumstances and anticipation of future developments, ultimately safeguarding themselves against long-term perils.

The purpose of this study is to investigate the effect of renewable energy consumption, trade policy, economic growth and biological capacity on ecological footprint as an indicator of environmental degradation in Iran in the period 1986 to 2021. For this purpose, in this study, the autoregressive model with wide distribution interval (ARDL) has been used to obtain long-term and short-term dynamic coefficients. The Toda-Yamamoto causality test was also used to examine the causal path The Cholesky analysis test for innovative accounting has been used to validate the estimated models. The results show that in the long run, there is a positive relationship between the biological capacity variable and the ecological footprint, but it is not statistically significant. However, there is a positive and significant relationship between trade policy variables and GDP with ecological footprint, so that in the long run, with a one percent increase in these variables, the amount of ecological footprint increases by 64.9% and 80.7%, respectively (applying pressure Upward - negative effect on environmental quality), On the other hand, there is a negative and significant relationship between the variable of renewable energy consumption and ecological footprint and increasing one percent of this variable in the long run leads to a decrease in the amount of ecological footprint by 33.9% (applying downward pressure - a positive effect on Environmental quality). The error correction coefficient obtained in this model shows that in each period, 47% of the imbalance resulting from the occurrence of shock and deviation of the short-term model from the long-term trend is adjusted and returns to its long-term trend. There is a two-way causal relationship between trade policy and the ecological footprint. Also, one-way causality from trade policy to GDP is confirmed. The results of Cholesky analysis show that the innovative shocks generated in the variables for the next 10 periods, thus affecting the ecological footprint, so that in the second period the largest share of impact compared to other variables is related to renewable energy by 3.5% But over time and at the end of the tenth period, the largest share of impact is related to GDP of 19.60%, commercial policy of 9.54%, renewable energy consumption of 7.76% and bio-capacity of 1.28%, respectively. Therefore, country-specific energy policies that increase the share of renewable energy in the energy portfolio are recommended.

Regarding the geographical position and appropriate environmental situation, solar energy is regarded as one of the most efficient renewable energies in Iran. This study seeks to provide a model for identifying the optimal locations of the establishment of solar panels in the urban setting. High potential and appropriate space of the buildings' roofs with high altitude and their placement subject to direct sunlight and non-optimal use of these spaces has necessitates the optimal location of the establishment of solar panels for the production of easy and cheap energy. In this study, first, the feature of locations suitable for the establishment of solar panels in the urban environment and the source of production of required layers were identified. The required layers for access to the appropriate locations of the establishment of solar panels were prepared and were spatially modeled. The final objective of this paper is to provide a scientific and practical model for replacing renewable energies instead of fossil fuels in Iran. Based on the fuzzy Delphi method and its integration in the geographical information system in this study, a suitable method was provided for the evaluation and selection of the best place for the exploitation of renewable energies.

One of the most important natural processes in arid regions is semi-arid wind erosion. Sand dunes are one of the most important facies of wind erosion. Sand dunes in the field of wind process are among the most dynamic geomorphic features of the earth's surface, which, on the one hand, are affected by the characteristics of speed, direction, wind frequency and, on the other hand, are affected by the characteristics of the earth's surface and sedimentary materials. Probability-based wind prediction for sand transport phenomena is a key element for human activities in arid regions. Wind erosion and movement of quick sands, which is considered as one of the important processes of land degradation and a serious challenge in Iran, occurs due to the interaction between climatic and terrestrial processes. The phenomenon of dust and the movement of quick sands is considered one of the important processes of land degradation and a serious challenge in Iran, and on the other hand, coastal areas are sensitive lands that have been affected by both sea and land ecology. They are also unique in terms of ecosystem diversity. Therefore, knowing the status of wind erosion and the activity of wind sediments, especially in landforms sensitive to this destructive environmental phenomenon, as well as identifying climatic factors affecting it can be an effective step in reducing desertification and improving air quality, especially in arid and semi-arid areas.

According to the purpose of the study, data on wind (frequency and direction), rainfall, temperature and number of dust days related to the synoptic station located in Jask city during a 20-year statistical period (2001-2021) were obtained from the Meteorological Organization. WR-Plot View 7 software was used to analyze the anemometer data. Also, using the mentioned capabilities of the software and considering the basic speed equal to the threshold speed of wind erosion, annual and seasonal storm rose were prepared. Land use maps and sand maps of the study area were prepared using aerial photographs, Google Earth satellite images and field visits.

Statistical analysis of climatic data in Jask region during the period (2001-2021) showed that significant annual changes in annual rainfall, temperature and wind occurred, so that the annual rainfall trend decreased significantly. The trend of annual temperature changes has not been significant, but the temporal changes of wind have taken a relatively downward trend and have shown a significant decrease in recent years. According to the annual windfall of Jask station, it was observed that 7.7% of the total annual observation hours, the air is calm and without direction, 3.92% of the winds blow in different directions and the speed is more than 0.5 m/s. The prevailing wind direction is from the west in all seasons and from the east in summer. The results of classifying the percentage of wind speed frequency showed that about 80% of winds have a speed of less than 6 m/s. The trend of changes in erosive winds during the statistical period under study has an upward trend until 2014 and in recent years has a decreasing trend so that in 2021 the lowest frequency of erosive winds was observed. The results of the portability calculation showed that the annual average of DP is 257 units. The final direction of movement of the sand is at an angle of 280 degrees to the north and the UDI index (RDP / DP) is 0.3, which indicates the variability of low wind directions. The Golmaseh diagram also showed that the wind sediments were moving to the northwest. The highest sand carrying capacity was seen in 2014 and the lowest in 2021. Considering the average of 257 vector units for Jask, the capacity of the amount of sand that can be moved annually is estimated to be about 18 cubic meters per unit width. In terms of land use, most of the area covers the rangeland. Also, sand zones cover about 5.7% of the area, which is mainly located in the south and southeast. The results of the interpretation of aerial photographs, satellite images, as well as field visits to the sand dunes of the southern regions of Iran, indicate the existence of sand dunes of the type of transverse hills, Barkhan and Seif, which are the result of two-way winds from one sector is blowing.

80% of winds have a speed of less than 6m/s, 20% of winds have a speed of more than 6 m/s. The monthly distribution of wind speeds below the threshold indicates that the highest number of erosive winds was observed in summer and the lowest frequency was observed in autumn. The wind direction is dominant throughout the year and all seasons except summer from the west. The amount of sand carrying capacity based on the threshold speed of 6.5 m/s is about 257 vector units moving from the southeast (coastal lands) to the northwest (coastal lands), which indicates that the direction of transfer of most sands from relatively arid and saline coastal areas (coastal grasses) are towards the plains and mountainous lands along the southern coasts of Iran. The ratio of vector to annual algebraic output (UDI) of this station is 0.3, which indicates composite multi-directional winds with sharp angles of variability of wind directions at low levels. Existence of sand dunes of longitudinal hills, seifs and silks is the result of two-way winds blowing from one segment. In the southern coasts of Iran, most of the main winds from the southwest and sub-southeast winds from the coast to the sea are effective in the formation of sand dunes. The strongest winds of the study area blow in summer and the weakest in autumn. The trend of changes in sand transport potential also showed the trend of wind energy in Jask station, which for most years has the ability to carry wind sediments in the middle class (DP> 200> 400), but a significant decrease was seen in 2018 to 2021; the highest sand carrying capacity was seen in 2014 and lowest in 2021. Also in the study station, the RDP/DP ratio has a range of changes between 0.022 to 0.8 in almost all seasons and throughout the year. The area of sandy regions has increased from 72.260 to 82.925 km2 between 2013 and 2021, which shows an increase of 10.66 m2.

rchitecture is always influenced by various indicators, the most important of which are climatic and physical-spatial indicators. These indicators are well observed in traditional homes and have played an important role in the use of clean energy. In this study, the aim is to study the climatic and spatial indicators of traditional architecture of Shiraz houses in order to provide a suitable model for housing design in order to use clean energy. The research method is descriptive-analytical and based on data collection through a questionnaire. The validity of the instrument was confirmed by elite and the reliability was confirmed by Cronbach's alpha above 0.70. The statistical population of the research consists of 27089 experts, specialists and people familiar with the architecture of the building and a member of the Engineering System Organization of Fars Province. The number of samples according to Morgan table is 384 people. The result of one-sample t-test showed that all studied climatic and spatial variables including green space, proportions and composition of architectural elements, materials, sustainable architectural design of spaces, building orientation, organizing spaces, water use, maximum use of wind , The use of light and providing coolness with shade at a level less than 0.05 were significant and in terms of the statistical population, were in a good condition. Among the spatial and climatic variables of architecture, the most impact was related to the orientation variable with a value of 4.03 and then green space with an average of 3.85. The regression result showed that the most effective variables in the design of modern houses are related to the variable of proportions and composition of architectural elements with a value of 0.151 units, ie 15%.

Recent scientific and technological development have provided comfort and well-being for communities while also resulting in new challenges such as environmental pollution. As a source of environmental pollution, fossil fuels emit toxic gases into the air while burning and thus trap heat in atmosphere, increase air temperature and result in wide-ranging climate changes. As the most significant source of energy, the sun can provide us with a proper alternative to fossil fuels. Related information can be collected through direct measurement of solar energy using devices such as a pyrometer. So far, various approaches such as remote sensing have been adopted to universalize solar irradiance maps. Due to their high accuracy and speed in estimating net radiation, remote sensing techniques can be an appropriate alternative to old experimental methods. Having access to precise information on the amount and intensity of solar radiation at low latitudes, including Iran is essential for the development of solar sites. The present study assesses solar energy and the feasibility of generating solar power or a photovoltaic (PV) system in rural areas of Joveyn County.

Elevation and related maps, sunshine hours, direct and indirect radiation, and total radiation were first collected and calculated. GIS-based solar radiation analysis was conducted in the present study and a zoning map was generated showing total solar radiation in 113 villages of Joveyn County. Atmospheric transmittance and diffuse radiation were extracted from the total radiation and extraterrestrial radiation of the studied stations. Then the annual radiation received in 2017 was estimated using the radiation analysis method and 30-meter resolution Digital Elevation Model (DEM) of the study area. Finally, the feasibility was assessed based on the consumption requirements of the villages and solar energy production capacity in the study area.

GIS radiation analysis sub-program was used to zone the total solar radiation in Joveyn County. Atmospheric transmittance and diffuse radiation were then estimated separately using the radiation recorded in each station and entered the model to determine the radiation. Elevation and related maps, sunshine hours, direct and indirect radiation, and total radiation were first collected and calculated in the present study. The highest altitude was recorded in the southern parts of the study area including Jalambadan, Ramshin, and Bid rural areas.Sunshine duration was the most important climatic parameter in the present study. Except for the southern elevations, the study area generally experienced long sunshine hours. The longest sunshine duration was observed in spring with an average of 1177.81 W/m², while the shortest was in winter with an average of 904.269 W/m². Tarsak village and Ghaem town have experienced the longest sunshine hours. The highest direct solar radiation was observed in the southern elevations of Joveyn County. Results indicate that the highest amount of direct solar radiation is observed in spring in rural areas of Karimabad, Rahmatabad, and Beyhagh, while the lowest is received in autumn.The highest amount of total radiation was observed in Jalambadan and Rahravi Bidkhor villages in spring, while the lowest was observed in autumn. Observed differences in radiation and altitude show that both parameters were affected by topographic conditions such as degree and aspect of slope and obstacles blocking direct radiation. Results indicated that Rahravi Bidkhor, Kalateh Fazel, and Bidkhor have received the highest total radiation throughout the study area.Finally, the total radiation potential was calculated. Accordingly, the highest solar radiation energy potential was recorded in Helamabad and Qale-e-Now villages. Results indicated that solar energy can be utilized in scattered and sparsely populated rural areas. Potential measurement map showed that 89.07% of the study area had an excellent potential, 8.58% had very good potential, and 2.33% had good potential. Finally, wind speed and direction were also evaluated. The highest wind speed was observed in the western and northwestern regions of the study area which results in a high potential for wind energy harvesting. Moving from east toward the study area, the potential decreases.

The present study has measured solar radiation reaching the Earth’s surface using the solar energy analyzer function of remote sensing and GIS with the aim of assessing the feasibility of using photovoltaic systems in the study area. Results indicated that solar radiation of the study area is between 27605 and 383675. Since a 1000 watts per square solar radiation is needed for photovoltaic cells, solar radiation in the study area has the necessary potential for solar photovoltaic systems. The wind speed potential in the study area decreases from west to east. Therefore, construction of wind power plants in the western parts of the study area is possible and economical. Moreover, environmental conditions show that solar panels can be installed and solar energy can be utilized in the mentioned region.Consistent with the present study, Sherbafian (2008) has assessed the feasibility of using solar energy in four provinces of Khorasan, Gilan, Qazvin, and East Azerbaijan, and concluded that Iran enjoys a high potential for solar energy generation. Findings are also consistent with Safaei et al. (2015) who have studied the potential of clean energy production in Esfarayen city.

Recently, Mazandaran Province has needed more energy. Considering the capabilities of this province in generating renewable energy, recognizing the potentials of clean energy generation and consumption, especially wind energy, should be a priority in the plans of managers and researchers. Current study has been done with the aim of spatial capability of wind energy in Mazandaran Province with emphasis on its topography. In order to initially estimate the energy that can be obtained from wind flow in the province, the necessary calculations were performed on wind direction and velocity data over a period of 12 years. Statistic data of 15 synoptic meteorological stations in the province at a height of 10 meters were used to collect daily wind speed and direction data. After calculating the average wind speed, wind speed continuity and wind power density in the meteorological stations, layers of each were prepared at heights of 10, 30 and 50 m using interpolation in ArcGIS software environment. The 50-meter-high wind speed zoning map in Mazandaran Province shows that among the study stations, Baladeh station with an average monthly wind speed of 5.98 meters per second at a height of 50 meters, has a maximum wind speed of 7.78 meters per second in July. This station experiences wind speeds of more than 6 meters per second for about 7 months of the year (April to October), especially during the warmer months of the year. This station also has the highest wind power density (WPD) with 51, 142 and 228 watts per square meter respectively at a height of 10, 30 and 50 meters above the ground. Also, the station has the highest amount of electrical energy output in Mazandaran Province with an average annual wind power of 58.4 kW, amount of electricity generated annually about 511452 kWh per year and network capacity of 17.7%. Therefore, this area is a suitable place in Mazandaran province for installing wind turbines and constructing wind power plant to generate electricity.

Latent energy is the energy used to produce and transport materials, build, maintain and demolish buildings. Exploitation energy is the energy that residents consume during the operation of the building. Past research has shown that the latent energy of buildings in developing countries is twice that of developed countries. As operating energy optimization increases, the share of latent energy in total life cycle energy will increase. Therefore, the importance of optimizing latent energy is becoming more apparent. Meanwhile, the construction industry is the largest consumer of natural resources and global energy reserves, which emit carbon dioxide and environmental pollution. This research has been done with the aim of optimizing the latent energy of the building by considering the architecture of the structural structure of the building. To calculate the latent energy of the building skeleton, the effect of various factors such as cross-sectional dimensions of structural members, materials used in concrete and the type of steel used has been investigated. How and to what extent is the latent energy of the building? The research method was descriptive-analytical with the help of ETABS software. The results show that by comparing the latent energy in the roofs in the table below, it can be concluded that chromite roofing has less latent energy than other roofs. Also, concrete buildings have less latent energy and much less environmental damage than steel buildings.

IntroductionEnergy is considered to be one of the most important factors affecting the development of human societies and also an essential parameter in economic and social development along with the quality of life. Population growth, rising living standards, the risk of global warming caused by greenhouse gas, acid rain, environmental problems and threats to human health, lack of fossil energy sources and rising energy consumption have increased interests in renewable energies. Solar energy has been used as a source of renewable energy for a long time. As one of the safest, most efficient and most economical sources of energy, it has the potential to become the main energy source in the near future (Dincer, 2000: 157). Due to the high number of sunny days, Iran is among the countries receiving the highest level of solar radiation in the world. With 240 to 250 sunny days per year, approximately 80 percent of the country receives an average annual solar radiation of 4.5 - 5.4 kWh / m² (Moghadam et al, 2011: 107). In this regard, the present study seeks to evaluate and monitor radiant energy reaching the surface of Sirjan basin. Materials & MethodsThe study area, Sirjan Basin, is located between 28 degrees and 46 minutes and 50 seconds to 29 degrees and 58 minutes and 1 second northern latitude, and 55 degrees and 11 minutes and 20 seconds to 56 degrees and 32 minutes and 40 seconds eastern longitude. It includes 18481 square kilometers with an average altitude of 1710 meters above sea level. Descriptive-analytical method has been used in the present applied research. Data are collected using library and documentary research methods (from information and statistics offered by different organizations) or extracted from satellite images. Solar radiation energy reaching to the surface of the study area has been evaluated using three methods including Angstrom experimental model, Solar Analyst method in GIS and Remote Sensing. Results & DiscussionAngstrom experimental model indicates that the maximum amount of energy directly received by the basin at low latitudes (28 degrees and 50 minutes) is 73370-73436 watts per square meter. This decreases as we move toward higher latitudes reaching 72836-72903 watts per square meter in the northern parts of the basin (latitude 29 degrees and 50 minutes). Monitoring solar radiation energy reaching the surface with GIS Solar Analyst (solar radiation analysis method) shows that the lowest amount of radiant energy reached the surface in January (between 14000 to 144039 watts per square meter). Also, the maximum amount of radiant energy reached the surface in July (between 111000 to 252000 watts per square meter). Remote sensing technique also shows that the amount of instantaneous radiation received in Sirjan basin reaches its minimum during winters and only a limited part in the west of the study area receives 4.498 to 8.436 watts per square meter. The maximum amount of instantaneous radiation received in summers is 597.6 to 845.6 watts per square meter, which is received in a large part of the west, northwest and southwest of the basin. ConclusionMonitoring radiant energy reaching the surface of Sirjan basin using experimental Angstrom model shows that the highest level of energy received in the southern parts of the basin is around 733370 to 73436 watts per square meter. This is reduced moving toward the northern parts of the basin. Moreover, solar radiation analysis method (Solar Analyst in GIS) shows that the highest amount of solar energy in Sirjan Basin is received in July with 200000 to 252000 watt-hours per square meter , June with 170000 to 248341 watt-hours per square meter, May with 190000 to 247627 watt-hours per square meter and August with 190000 to 234500 watt-hours per square meter, respectively. These values are recorded in eastern, northeastern and southeastern parts of the basin. Results indicate that the eastern half of the basin in which the cities of Balvard, Tekiye, Saadatabad and Pariz are located, receives the highest amount of solar radiation energy especially in summer. Remote sensing technique shows that the highest amount of instantaneous radiation received in summer is 597.6to 845.6 watts per square meter which is recorded in the western, northern, northwestern, southern and southern parts of the region including the villages of Pariz, Saadatabad, Balvard in the central strip and Khatunabad, Mahmoudabad, Najafabad, Malekabad and Golestan. The same is also recorded in other seasons, though with a decreasing trend. The highest level of instantaneous radiation is received in these parts of the basin.

Today, transportation is associated with all aspects of life in cities. Having a sustainable approach in this basin requires coordination between human activities with a vibrant environment and pollution-free along with supporting dynamism and economic justice along with vitality and social justice, which are the main dimensions of sustainable development. The purpose of this article is to present the optimal model of urban transportation in Tehran with emphasis on clean localized energy. In this research, SPSS and GIS software will be used to analyze the information in testing hypotheses. In other words, because the research is qualitative, to analyze it, first quality is converted into quantity using a questionnaire and non-parametric statistics analysis in SPSS environment and its visual expression in GIS environment. In this study, in order to find clean fuel and localize it according to the situation of Tehran metropolis and the country, first 5 car fuels consumed in Iran, including: gasoline; Gasoline, compressed gas, liquefied petroleum gas and electricity from 5 different directions analyzed by 40 experts using AHP hierarchical analysis process method and in Expert Choice software. Finally, according to the 5 factors raised, experts have been asked to introduce the final fuel with the lowest pollution and the highest production in the country; The results were tested in the form of a 5-point Likert spectrum using t-test that compressed gas (CNG) fuel is introduced as the most suitable fuel that has a high localization capability in Tehran and the country.

Solar energy is receiving lots of attention because it is one of the cleanest, cheapest and most available energies in the world.but solar radiation in different parts is changing, thus, identifying appropriate locations for implementation of solar energy is necessary. Accordingly the aim of this study was to analyze the potential of solar radiation and land surface temperature on the Loot desert using remote sensing and geo statistical technique. Results show that Earth's surface temperature fluctuates between 29 and 79 degrees Celsius in the Lut Plain. So that Earth's temperature increases to the east and north-east of the region. Also, the radiation energy reaching the surface in the Lut plain varies from 232.77 to 237.61w/m² in different parts of the Lut plain. So that the maximum amount of energy is related to the south of the plain, and the further we move to the north reduces the amount of energy.

Energy is one of the primary human needs to pursue its goals. Traditional energy sources such as fossil fuels are exhausted and cannot be accessed everywhere. They also pollute the environment and cause irreparable damage. Decision-makers and planners should replace traditional energy sources with non-harmful environmental sources. Renewable energy sources such as solar energy, wind energy and Biomass can be a potential alternative to traditional energy sources. Solar energy is converted into electricity using solar panels. but one of the most important things to be considered in this case is finding an optimal location for the deployment of solar panels. Geographical information system (GIS) enables researchers to perform various spatial analyses in a graphical environment and allow appropriate visualization of the results. There are various important factors and criteria that affect the efficiency and cost-effectiveness of solar panels so it is necessary to compare these factors together. Multi-criteria decision-making methods are one of the ways that allow researchers to make a preferential comparison at the same time on different criteria affecting a decision. The best-worst approach is one of the multi-criteria decision-making techniques. B-W is a new and efficient method and can effectively determine the priority of criteria on each other. Also Artificial Neural Network (ANN) capabilities can be used to solve site selection problems because it has been proven that ANN is capable of solving many decision-making problems.

East Azarbaijan province in northwest of Iran which is a mountainous region with no oil and gas reserves was selected as the study. The fuel needed for domestic and industrial uses of the province is supplied by pipelines of oil and gas extending from southern Iran. In this study eight climatic, orographic and economic criteria including GHI, distance from cities, distance from main roads, altitude, slope, slope direction, mean annual precipitation and mean annual sunshine hours were used. The GHI Criterion Layer for East Azerbaijan Province was extracted from the Iran Layer. Height, slope and aspect layers were also produced using the DEM product of ASTER sensor. The layers of sunshine hours and mean precipitation were also interpolated using the values of synoptic stations for the entire province using IDW algorithm. The values for the distance from the cities and the distance from main roads raster layers were also obtained using the Euclidean distance function. Since the defined criteria had different units and nature the criteria values were normalized between 0 and 1 using different functions. The best-worst method was used for weighting the criteria and determining the relative priority of the criteria. After calculating the weight of each criterion, the initial suitability values were obtained by multiplying the criteria by the weight obtained. Then, 751 samples were taken from the whole study area for ANN training. The values of each sample in the criterion layer as “input” and the values obtained by multiplying the layers in their weight as “Target” entered the ANN. Also, according to the laws and regulations, some lands such as rivers and their margins, cities and their suburbs, protected areas and fault lines are places where solar power plants cannot be installed. Hence, in this study, these places were identified as restricted sites.

The BW results showed that the “GHI” criteria and the “distance from city” have the highest weight and the “average precipitation” criterion has the lowest weight. Levenberg–Marquardt algorithm was used to train the network. 75% of the samples were allocated to network training and 15% to testing and 15% to validation. The number of hidden layers was set to 15. After 344 iterations mean squared error value for the network training data reached its optimum. Also, the regression value between the network inputs and the Targets was 1, indicating that the network training was performed best. After the network training was completed, the output values were obtained for the entire study area using the “net(y)” function. The results of ANN showed that 2,622,975 hectares of the province have a suitability of less than 0.5 for solar power plant deployment while only 92075 hectares of land in the province have a suitability rate of over 0.75. To make the results more accurate, the binary constraint layer was applied to the results obtained from the neural network. The results showed that this time the proportion of lands that have suitability of less than 0.5 reached 3,315,093.75 hectares and the proportion of land suitability rate of over 0.75 included only 69762 hectares of land area. This indicates that some of the initially high suitability locations for solar panels were located in areas where it is not reasonably possible to deploy solar power. So relying on the values obtained for "land suitability" without regard to the constraints in the areas may be misleading.

In this study, suitable locations for installation of solar panels were identified using a combination of multi-criteria decision making methods and artificial neural network. The best-worst method that is a novel and efficient MCDM technique was used for weighting the criteria. The results showed that the areas that are located in the proper distance with the cities and the main roads, provided they have a high GHI value, are more suitable for other solar plant deployments. In order to improve the results, constraints including rivers, cities, protected area and fault lines were defined and applied to the land suitability layer. In general, the western regions of the province were more suitable than the eastern regions, due to the proximity of the cities to each other, the high density of the main roads, the suitability of elevation and slope and aspect, as well as the high amount of GHI and sunshine hours and low amount of mean precipitation. Due to the high accuracy of the results, we can say The procedure used in this study can also be used in other mountainous regions of Iran to produce reliable results.KeywordsArtificial Neural Network (ANN), Multi-Criteria Decision Making (MCDM), solar energy, Renewable Energy (RE), Geographical information system (GIS)

Increasing consumption of the earthchr('39')s primary resources (materials and energy) in addition to the production of environmental and atmospheric pollutants (especially CO2), poses a serious threat to sustainable human life. The aim of this study was to evaluate the effect of using concrete, brick and wood in traditional construction in northwestern Iran on energy consumption and carbon emissions.

This quantitative experimental study was conducted during 2015-2020 in two provinces of West- and East Azerbaijan (northwest of Iran). Concrete, brick and wood were selected as the materials studied. For each of the selected materials, 3 factories were selected. Preliminary information on the number of employees, gas input and electricity consumption was obtained from the HSE center of each plant. Data obtained from the survey of industrial units, quantities related to the amount of electricity consumption, the amount of gas consumption, the amount of manpower employed in the production line and in the transportation sector and the amount of diesel fuel used in rail and road transport. Using Revit software for modeling and Energyplus for energy analysis, the average of different industrial units was calculated for each material. Daily energy consumption of manpower was determined according to BMR and PAL according to the type of activity, height and weight dimensions and age.

The average consumption of electrical energy to produce each ton of cement was 110kw.h, each ton of brick was 35kw.h and each ton of wood was 900kw.h. The total latent energy for the production of each ton of ready-mixed concrete was 559290kw and released 92t of CO2, each ton of produced brick was 283220kw and released 47.5t of CO2 and each ton of timber produced was 7213kw and the released 675kg of CO2.

Despite the long distances due to the lack of gas in the production line, wood is the greenest material and concrete is the most polluting material due to the high dependence of the production line on gas consumption.

Borders and especially the development of border settlements in each country are important in different dimensions and are considered as factors of durability and consistency of each country. This is important considering the geopolitical position and geoculture of Iran and especially despite the natural resources in most border provinces. Increases the geo-economic and strategic importance of these regions and emphasizes the responsibility of the Iranian government and system to reflect more and more to pay attention to comprehensive development in these provinces. For example, we can mention the provinces of Kermanshah, Ilam, Khuzestan, Bushehr, Hormozgan, etc., which include a wide area from the west to the south of the country. Ilam province, which is one of the provinces with the highest fossil energy reserves in the country, is affected by its geographical position as a deprived, underdeveloped and underdeveloped province, while one of the ways out of this province from economic crises and Lack of development, management and use of fossil fuels. In this regard, the present study has investigated and evaluated the effectiveness of the use of fossil fuels in the development of cities in Ilam province using descriptive-analytical and applied methods. The results showed that in this field, Malekshahi city with 17.16%, Dehloran city with 74.12%, Sirvan city with 3.11% and Ilam and Ivan cities each with 8.10% are among the cities that The development of fossil fuels in their area and province can have the greatest impact on the development of these cities.

As technology evolves in many countries around the world, the need for energy is increasing, which is especially important in developing countries such as Iran, because sustainable energy is needed to develop the process of sustainable development. Due to the geographical location of Iran and having a large number of sunny days, using solar power at the scale of the power plant helps provide sustainable energy. According to the radiation map provided by the Iranian New Energy Organization in East Azerbaijan province, there is enough potential to build a solar power plant. Due to the ability of neural networks to solve complex problems, the present study has used a combination of spatial decision-making system, GIS environment, and artificial neural networks to identify potential areas for solar power generation. The data used in the study include solar radiation, precipitation, sunshine hours, temperature, altitude, slope, LULC, distance from roads, and distance from cities. Based on these criteria, training data were obtained and trained using the Levenberg-Marquardt training algorithm of FFB, CFB, and MLP networks.According to the results, the CFB network, with form 9,6,1 and RMSE values 0.084 and 0.061 for training and test data, was selected as the most suitable network and with the results obtained from this network, the location was determined. The results were classified into five classes, with about 15% identified as very favorable for the construction of photovoltaic solar power plants in East Azerbaijan Province.

In this research, we are looking for zoning of photovoltaic solar power plants using an artificial neural network in East Azarbaijan province. Since artificial neural networks need training data to perform the calculations, the criteria are weighted first through ANP, and then by using the weights obtained for the criteria, the training layer for network training is created. Using the training layer, all three FFB, CFB, and MLP neural networks have been trained to obtain the appropriate network and optimal structure.Environmental criteria are selected based on the parameters of the construction of photovoltaic solar power plants. Given that the locating process is a multi-criteria decision problem between different parameters and criteria, therefore, the software must be selected that supports both the vector model and the raster model. It also can implement multi-criteria decision-making rules. Based on this, ArcGIS 10.6 software was used for data preparation, layer preparation, and integration. Super decision and Matlab software have also been applied to the process of analyzing network decision making and artificial neural networks.

The structure of neural networks is such that by changing the number of hidden layers and its neurons, the change of the stimulus function and training algorithm of the network structure is changed and affects the output of the model. Therefore, determining the optimal structure of the network is based on trial and error, and using the evaluation criteria and comparing the results, the optimal model is modeled with the least error. However, we should be careful that if the error rate is very close to zero in the evaluation of the training results, there is a possibility of over-fitting, which means that the network created will only be suitable for the training set and adding new data will not yield a satisfactory answer.Matlab software was used to simulate the structures of different artificial neural networks and determine the optimal structure. For the present study, three FFB, CFB, and MLP neural networks with different structures have been created so that all three networksemploy the Lonberg-Marquardt training algorithm with back-propagation error (trainlm). The number of neurons ranged from 1 to 15 and the number of repeats between 10 and 700. For the FFB and CFB networks, the tansig and purelin transfer functions and for the MLP network, the hardlim and hardlims transfer functions are investigated.According to the simulations, the optimal CFB network structure is 9,6,1 with 9 input neurons and 6 middle neurons, with MSE and RMSE values for the training data 0.006, 0.084 and for the test data 0.004, 0.061, the optimal FFB network structure as 9,5,1 with 9 input neurons and 5 middle neurons, with MSE and RMSE values for training data 0.11, 0.107 and for test data 0.012, 0.111 and the optimal structure of the MLP network as 9,9,1 with 9 input neurons and 9 middle neurons, with MSE and RMSE values for the training data 0.007, 0.085 and for the test data 0.006, 0.079 have been selected. Based on these results, the CFB neural network with the structure of 9,6,1 has the best performance among the networks. For this reason, the photovoltaic solar power plants in East Azarbaijan province have been located with this network.The final map was classified into five descriptive classes using the results obtained. According to the classification, about 7.7% were in the very undesirable class, 28.4% in the undesirable class, 27.6% in the middle class, 20.6% in the desirable class, and 15.5% were in the very desirable class.

With the advancement of industry and the development of new technologies, population growth in many countries of the world has increased the consumption of electricity. Also, all developed and developing countries have realized the fact that to maintain their international status, they need to provide sustainable energy, especially electricity, from non-fossil energy sources. As societies become more aware, the limitations and harms of using fossil fuels have become more apparent, forcing countries to source some of their electricity needs from other energy sources, such as renewable energy sources. Iran, like all developing countries, is no exception. Due to the geographical location of Iran and having 300 sunny days, the use of solar energy in both large and small sectors contributes to sustainable energy supply.In this study, the authors have tried to combine the existing methods for location namely the use of spatial decision-making systems and GIS, to use new methods such as artificial neural networks to identify potential areas for the construction of photovoltaic solar power plants in East Azarbaijan province. To accomplish this, based on the criteria for the construction and location of photovoltaic solar power plants, environmental factors include solar radiation, precipitation, sundial and temperature as climate criteria, elevation and slope as physical and land use criteria, distance from roads, and distance from cities are considered as economic criteria. Based on these criteria, training data was obtained through ANP, and along with this data, and LM training algorithm was performed to train FFB, CFB, and MLP networks.Based on the MSE and RMSE evaluation criteria, the CFB network with the structure of 9,6,1 was selected as the most appropriate network and the results were obtained from this network. After preparing the final map, it was determined that solar photovoltaic power plants could be built in the province.