جستجوی مقالات مرتبط با کلیدواژه « global warming » در نشریات گروه « علوم انسانی »

The rate of disproportionate temperature increases in the Arctic relative to the global average is called Arctic amplification. The purpose of this study is to investigate these effects in Southwest and West Asia, longitude 20-70 degrees east and latitude 20-60 degrees north. To this end, the reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF), version ERA-5, with a horizontal resolution of 0.25 × 0.25 degrees in the period 1959-2021 was used. The periods before and after the rapid warming of the Arctic were considered to be 1959-1985 and 1995-2021, respectively. The analysis of weather temperature variance indicated that the variability of temperature near the earth surface in the Arctic has decreased in the period after the rapid warming of the Arctic in the all seasons, which can be due to the increased volume of ocean water due to the loss of the sea ice extent in this region. The impact of the rapid warming of the Arctic on the weather patterns in Southwest and West Asia was also investigated. The results showed that due to the rapid warming of the Arctic, the meridional range of the lines of equal value in the geopotential height of 500 Hectopascal in the studied area has increased by 4 degrees in the summer season and in other seasons other than winter, an increase in the amplitude of the waves and a change in the location of the waves to higher heights were observed. It was also observed that the jet stream speed in the period after the rapid warming of the Arctic has decreased the most in the summer season, except for the autumn season. It has almost decreased in the other seasons. These changes can result in an increased frequency of extreme weather events, especially in the summer season.

Due to its location in low latitudes, Iran is among the countries that has not been spared from the security consequences of climate change. The present study seeks to answer two questions: 1) What are the security consequences of climate change on Iran and which components have the greatest impact on Iran? 2) Which of the pillars of good governance as a solution has the greatest impact on reducing the effects of climate change on Iran? 
In this study, the study population is elites and experts familiar with the subject of the study, 100 of whom were selected for snowball sampling and a researcher-developed questionnaire was used to collect data. Data were evaluated using SPSS and MINITAB software. The results of the studies according to the obtained P-value which is equal to 0.000 and is less than 0.05 alpha, indicate the difference between the natural and human consequences of climate change in Iran. The results of the Tukey test indicate that the natural consequences of climate change with an average of 4.0584 are in group A and the human consequences with an average of 3.4460 are in group B. Also, the results of Friedman test on the effect of good governance in controlling and reducing the security consequences of climate change in Iran show that accountability with an average of 5.79 in the first place, rule of law with an average of 5.62 in the second place. and accountability of officials with an average rating of 5.32 are in third place.

In this study, for statistical studies to determine days whit temperature above 50°c, the reanalyzed data of the nineteenth, twentieth and twenty-first centuries for the West Asia region (12 to 42.5 degrees north latitude and 36 to 63.5 degrees east longitude) have been used. Also, for synoptic analysis of extreme temperatures, HGT, AIR, UWND, VWND and SLP data were used. To conduct this research, first, extreme temperature data above 50° during the last 185 years were extracted for the study area in the hot season (June, July, August and September). After identifying days whit above 50° c, HGT data at the level of 500 hp were extracted and WARD clustering was applied. Finally, after identifying the clusters, the days whit the highest temperature that occurred in each cluster were selected for synoptic analysis. It can be said that all altitude patterns of geopotential meters (HGT) at the level of 500 hp show that the main cause of occurrence and distribution of temperatures above 50°c in West Asia are high-altitude (high-pressure) subtropical West Asia, which due to the location of its high-pressure core on the Zagros and sometimes the Arabian Peninsula, it has been referred to as the Zagros or Saudi high-pressure in terms of interest and taste. What is certain, however, is the high-pressure independent identity of the subtropical Azores, which has been mentioned in numerous articles and is known to be the main cause of the heat in the West Asian region, especially Iran.

The greatest environmental threat today is global warming and Climate Change. Climate Change deined as dramatic and long-term change in the distribution of Atmospheric patterns in the long-term periods. What distinguishes the current Climate Change is that humans have played an important role in the global warming process. The issue is that human activities increase the amount of greenhouse gases in the atmosphere. This will increase the amount of intense absorbed radiation, and the amount that is emitted again to the Earth causes the Earth to warm up. The weather model forecasts in the summary report showed that during the 21st century, global temperatures increased from 0/3 to 1/7 degrees Celsius to 2/6 to 4/8 degrees Celsius (4/7 to 8/6 degrees Fahrenheit), and its amount depends on the amount of greenhouse gases and the effects of Climate feedback. (NASA, 2017)The main effect of Climate Change is the increase of global average temperature. The average surface temperature could increase from (approximately 1/67 to 5/56 degrees Celsius) by the end of the 21st. This causes a variety of secondary effects, namely, changes in patterns of precipitation, rising sea levels, agriculture pattern changes, extreme increase of weather events, the expansion of the range of tropical diseases, and the opening of new marine trade routes. Potential effects include sea level rise from 110 to 770 mm between 1990 to 2100, agriculture consequences, possible slowing of the ocean heat circulation, reductions in the ozone layer, increases of intensity and frequency of extreme weather events, lowering of ocean pH, and the spread of tropical diseases such as malaria and dengue fever (IPPC,2013). The country Iran, which is a spatial political unit in Southwest Asia, is not excluded from the Climate Change impacts. Undoubtedly, Iran will face the consequences of the Global Climate Change today or in the very near future. Environmental impacts of Climate Change in Iran, considering that 90% of Iran's land are dry and semi-arid lands, leads to destruction of the agricultural industry. For this purpose, the following questions have been asked: Which indices of sustainable development in Iran are subjected to and how is the status of these indices validated by the country? What are the indicators of the effects of Climate Change on the sustainable development of the country and what is the status of these indicators in the provinces of the country?

Historically, Iran has always been exposed to the consequences of Climate Change, given its Geographical location. Iran's location in the Earth's desert belt and the availability of a quarter of its water resources (precipitation and surface water) have revealed the need to pay attention to the various dimensions of Climate Change in Iran. The purpose of this study is to zoning the country's regions based on Sustainable Development indicators, the effects of Climate Change, and to provide a model in different regions of the country. The present study is descriptive-analytical in terms of purpose, application and method. Data collection and documentary and survey information have been done with questionnaire tools. Data collection and documentary and survey information have been done with questionnaire tools. The statistical population of the research is purposeful and includes experts and specialists in the field of Climate Change working in meteorological, environmental and passive defense organizations. To ensure the validity of the questionnaire, the opinions of 3 professors of Climatology and Political Geography of Tehran University and Research Sciences were used and after making corrections and adjustments, 48 questions were compiled for the final questionnaire. To measure the reliability of the questionnaires, Cronbach's alpha test scored 0/8 out of 16 questionnaires as a pretest. The questionnaire was designed based on the indicators of the effects of climate change and after distribution, 60 questionnaires were collected. The data were then entered into the SPSS software and Friedman's comparative test was used to prioritize the Sustainable Development indicators of the effects of Climate Change.

Then, Friedman's comparison test in SPSS software prioritizes the effective parameters of Climate Change on Sustainable Development, which arerespectively, they are: 1- Vulnerability to livelihood, poverty and weak government 2- Sustainable Agriculture and combating desertification and drought. 3- Health, Public Health 4- Maintaining the balance of the natural ecosystem.5- Justice and social security and citizenship will have the greatest impact on the sustainabledevelopment of the country. Then, using GIS software, the country's zoning was drawn based on the effects of Climate Change in the country's regions.Country zoning based on poverty and social anomalies (misery index), Sustainable Agriculture (Strategic Products), drought and agricultural destruction, public health indicator, ecosystem balance, Social Justice (Distributive Justice)

The results of this study show that the provinces of Sistan and Baluchestan, Hormozgan, Qom and Alborz are in line with the highest percentage of weakness and fragility against the effects of Climate Change in the country, which will have the greatest challenge with drought and agricultural degradation These challenges will increase the process of importing agricultural products to Iran, and Iran will become an importer of these products, and on the other hand, will cause migration, unemployment, poverty and increase social anomalies in Kermanshah, Sistan and Baluchestan provinces. The government is also authorized to use educational services and the ability to reconsider using the revision and change in re-status using the revision in the library of Sistan and Baluchestan, Bushehr, South Khorasan, Alborz and Qom. To this end, the government can use a well-written plan to reduce the challenges posed by the effects of climate change in these areas. Finally, the need to implement effective methods such as watershed management and clean energy use to reduce greenhouse gas emissions to adapt to Climate Change impacts is emphasized.

Sensible heat flux and latent heat flux are among the variables that are closely related to temperature and humidity and show heat transfer on a surface. So, their changes can be considered related to changes in temperature and humidity. In this regard, the current research aims to analyze and reveal the climatic changes of Iran by examining the course of changes in sensible heat flux and latent heat and the ratio between the two. For this purpose, NCEP/NCAR reanalysis data including sensible and latent heat flux during the period 1948-2020 was used in Iran. Bowen coefficient was calculated from the ratio of these two heat fluxes. Interpolation methods were used for their spatio-temporal analysis. In addition, by using the non-parametric methods of Mann-Kendall and Shibsen, spatial and temporal changes were also investigated. The first part of the results showed that, spatially, the Bowen coefficient is a function of latitude and roughness. And in terms of time, the lowest value corresponds to the month of January and the highest value corresponds to the month of July. The results of the second part show that the Bowen coefficient has a positive trend over time. Its upward trend indicates an increase in the dryness coefficient of the country. So that this situation can be seen in the positive trend and increase in temperature.

In recent years, land use changes in Isfahan city and its surroundings have been increasing, and these changes have been caused by factors such as population growth, economic interests, and changes in society's needs. The current research was conducted with the aim of investigating the temperature changes of Isfahan city and its surroundings in a forty-year period (1979-2018). The current research is based on the purpose of applied research and its method is descriptive-analytical according to the subject of the research and its nature, and to investigate the temperature changes affected by the changes in land use and urban development of Isfahan city, temperature data from The city of Isfahan and the area of ​​50 kilometers around the city of Isfahan have been collected from the database of the European Center for Medium-Range Weather Forecasts (ECMWF). To verify the accuracy, the data of meteorological stations of Isfahan, Isfahan Airport and Najaf-Abad have been compared and evaluated. became. The results of the research show that in this 40-year period, we have seen a significant increase in the average annual temperature from 0.06 degrees in the eastern area of ​​Isfahan city to 0.11 degrees in the western area. This means that the average temperature of Isfahan city and its surrounding areas has increased between 2.5 degrees and 4 degrees during a period of 40 years.

Land Surface Temperature (LST) is one of the most important parameters of environmental and climatic conditions. Therefore, this study is to investigate the trend change of day and nighttime LST in ​​Iran at a monthly and annual scale. To achieve this goal, the monthly products of MODIS sensor, Aqua satellite for day and nighttime with a spatial resolution of 5 km were obtained from USGS from 2020 through 2003. Then a three-dimensional matrix with dimensions of 216 × 297 × 388, in which 297 × 388, the number of cells and 216 months, was created. Finally, the monthly and annual changes of these two parameters were performed using Mann-Kendall test. Although the average annual trend of day and nighttime LST is increasing, on a monthly basis, different patterns are observed. The LST at nighttime increased significantly in May and September and during the daytime in December, but in June, July and January both day and nighttime temperatures increased. In contrast, both in March and October had a decreased trend. There was also a decreasing trend in nighttime LST in February and daytime in April and November. The results showed that the nighttime LST increased more than the daytime temperature, which led to a decrease in the 24h temperature range. In the spatial dimension, the highest increasing trend was observed in the western and southwestern regions and the highest decreasing trend was observed in the central plateaus and southeastern. Another point is that the water areas undergoing change, such as Lake Urmia and the lakes of Fars province, have experienced a significant increase (decrease) in LST during the day (night). In addition to decreasing the range of 24h temperatures, due to the fact that in the northern and western half of the country the upward trend was more and in the center, east and southeast the decreasing trend of temperature was predominant, the amplitude of spatial temperature gradient also decreased.

The impact of climate change on tourism has been the subject of many research studies. It is for this reason that tourism researchers have continued to explore the relationship between tourism and climate change and further explored response strategies among tourism stakeholders. The aim of this research is the evaluation of climate change and its impacts on thermal comfort and tourism climate of Iran. For this purpose daily maximum and minimum temperature, wind speed and relative humidity data of 91 synoptic stations during a period of 30 years (1987-2017) were used. In this research the (CDFt)[1] model is used to downscaling the GCMs data. ERA5 data was used to evaluate the performance of the downscaling model. The CanESM2 and GFDL_ESM2G daily data were used to draw future landscape changes of thermal comfort (based on the 2.6, 4.5, 8.5 RCPs). Then the thermal comfort for tourists was calculated using PET[2]. The thermal comfort results compared between the present and future. Thermal comfort of Iran was predicted for 2 periods (2021-2040) & (2041-2060). The results are displayed in ten-day classes. The number of stations that have optimal thermal comfort conditions in observation period indicates 0.83% increase compared to the futures perspective. The best conditions of climate comfort is predicted in the 24s and 25s decades and the most undesirable conditions are in the first to fifth and 34 to 36 decades. The most PET decrease is predicted in the northeast of Iran and the least increase of PET are occurred in the northwest. The results indicate an increasing on PET (between 0.06 to 1.56%) at future due to the increase in average temperature.

The daily variables of maximum and minimum temperature, wind speed and relative humidity of Synoptic stations as well as the ERA5 database in a 30-year period (1987-2017) and GCMs data were used to simulate the PET from 2021 to 2060. The CDFt model was validated using the Pearson correlation coefficient and the Kolmogorov-Smirnov tests along with a climatic RMSE. There are often abrupt changes in the climate time series. The homogeneity of observed data evaluated using the RhtestV4 software package based on the maximal penalized T and F (MPF, MPT) tests.  Data imputation was performed using Sequential K-Nearest Neighbor Method.Then, the research process was done as follows:The variables of maximum and minimum temperature, relative humidity and wind speed was simulated by CDFt statistical downscaling. The CDFt can be considered as an approach to the Quintile Mapping (QM) method by providing cumulative distribution functions (CDFs). Assuming that the ERA5 data are converted to the cumulative distribution function of the local climate variable as predictand at the desired station. In this study the CDFt software package has been used in R software. Validation of the simulated data was performed by Pearson correlation coefficient, Kolmogorov-Smirnov test and tidal error of the mean square squares.The RayMan model was used to calculate the thermal comfort based on PET index using both the observed and the GCMs downscaled data (CanESM2 & GFDL_ESM2G). This model is able to calculate the effect of short and long wave radiation flux on the human body, which is required in the human energy balance model.

After making sure that the CDFt, in general, showed a good performance in downscaling of the variable applied to calculation of climate comfort in the study area. Therefore, it is reliable to project the future thermal comfort of the region under the climate change conditions.Then  the historical period of CanESM2 & GFDL_ESM2G Models were used to show a comparison between PET observations and PET simulations. The results of the thermal comfort verification calculated based on the historical period simulated values ​​in comparison to the observed values ​​are as follows:There is a high correlation between the time series of the PET observed and PET simulated the historical period of GCM Models. However, a linear and positive relationship was observed for all-time series. According to the Kolmogorov-Smirnov test, the simulated values ​​of all PET time series showed good fit with the observed data at the 0.01 significance level. The calculated value of RMSE test for PET indicates the high performance of the downscaling method in simulation of historical period of GCM Models. The results showed that the CanESM2 model with minor differences performed better than the GFDL_ESM2G model. Incremental changes of physiological equivalent temperature haveoccurred in higher latitudes and in the high places like Alborz and Zagros. Also the PET decreasing changes are in low latitudes and central parts of Iran.Therefore, it is expected that more area of Iran will be at the desired threshold of thermal comfort at the future.The results showed that in the rest of the year, the largest utilitys are in the 24 and 25 th decades. Regardless of the model type towards the Rcp4.5 and Rcp8.5 and the 2041 to 2060 period increasing the values of the Physiological Equivalent Temperature will proceed. Also, the length of comfort decades is increasing in future periods.

This study was performed in order to provide infrastructure for tourism in future periods from 2021 to 2060. For this purpose, the climate comfort of Iran was predicted by GCMs data. Currently, most parts of the Iran are in the range of mild to severe cold stress. It is predicted that wider parts of study area will have optimal comfort conditions in future. Also, the number of optimal comfort decades is increasing compared to the observation period. The results of the climate comfort study showed that mild to severe cold stress conditions are predicted in More than half of this country at different decades of the year. So it will create opportunities and constraints in the future which requires long-term planning and strategies in this area.

Projection of summer monsoon rains in Southeast Iran based on Ensemble model the precipitation factor has a variable and random nature and has a different behavior in terms of space and time. Therefore, the prediction of precipitation has more uncertainty compared to other meteorological variables. In the current study, the data output of Cordex database and CMIP5 models were used using the neural network method to reduce the uncertainty and estimate precipitation properly. The results showed that due to the high correlation of temperature, humidity and air pressure with precipitation, the use of these variables is beneficial in reducing the uncertainty of precipitation forecast. In addition, the non-linear method of artificial neural networks can be used to bias the rainfall data of Cordex database and CMIP5 to forecast the rainfall in the southeast of the country. Another result of this research is the increasing trend of rainfall in the southeast of Iran, especially in the coastal areas. This can be considered as a result of the increase in the level under the influence of rains affected or simultaneous with the southwest monsoon of India. The increasing trend of precipitation in the southern coasts is also related to the increase in the storage capacity of moisture content. The interannual variability of India's monsoon rainfall also shows a steady positive trend under continued global warming. Since both the increase in the duration of monsoon rains and the increase in interannual variability in the future are seen in most models, we can be confident in these predicted trends. Indian summer monsoon rainfall is also predicted to be higher under global warming in the 2050s compared to the baseline.

The continuous and expanding process of global warming, especially in the Asian region, has provided the conditions for increasing drought and the spread of desertification. Many deserts had ecologically balanced soil conservation conditions that until recently have become new sources of dust generation now. Numerous examples have occurred in Iran due to its special geographical location among some of the most important deserts in the world. Temperature anomaly (about 8º C) last winter in the Caspian Sea basin has created new dust sources for the southern coastal of the Caspian Sea. On 30-31 May 1400, dust emission was recorded in meteorological stations of Gilan province in terms of area and concentration. The implementation of HYSPLIT chemical backward models shows the emission of dust from the northwestern region of the Caspian Sea to the southern coastal of the Caspian Sea (Guilan province) for the first time with such intensity. The source and origin of this dust was identified in the Rhine desert in the northwest of the Caspian Sea. Continuous and unprecedented warming in the region and accompanied by strong north-south currents provided the conditions for the emission of this dust. Due to the origin of the emitted dust as well as the geographical and topographical conditions of the Caspian Sea basin, the level of this dust was assessed from the ground level to an altitude of less than 1500 meters. Analysis of synoptic conditions using NCEP / NCAR analysis data with 1 degree horizontal resolution indicates the establishment of high pressure air mass with a center of 1018 hPa on the northwestern parts of the Caspian Sea and the penetration of high pressure to the southern coastal areas of the Caspian Sea. Due to the appropriate pressure gradient and increasing wind speed, dust-producing springs are formed on the desert areas of the Rhine and with the dominance of the northern currents (south-south), the dust mass is sent to Gilan province.

Improper waste management threatens the sustainability of the environment. Defining an optimal and sustainable system for waste disposal requires the examination of all processes within the system, their impact on the environment, economic aspects, implementation, and energy consumption in each part. The present study was conducted with the goal of modeling the municipal solid waste management system of Rasht County based on the life cycle assessment approach. In this regard, two existing disposal scenarios and the development plan for the future were compared. The first scenario (existing disposal) includes the sale of recycled waste, biological processing (compost production), and landfilling. The second scenario (development plan) involves the use of an incinerator in addition to previous disposal methods. After collecting data using the IWM-2 model, the environmental impacts of each scenario were assessed. The results show that if the second scenario assumptions are applied, the amount of energy consumption, pollutants, and global warming will decrease relative to the first scenario. Total energy consumption in the first and second scenarios is respectively +3891 and -1683234 Gj. In addition, the global warming potential is reduced due to the reduction of landfills, reduced transportation and fuel consumption, improved equipment, and energy recovery in the second scenario. In general, environmental performance in the second scenario will be improved if appropriate action is taken. Reducing landfill and greenhouse gases, increasing recycling, etc., are the main reasons. Although incineration reduces landfilling in Saravan, it is still the proper design of the landfill, and energy utilization from it provides a favorable life cycle of waste management based on the second scenario. Moreover, the use of waste incineration is justified only if pollution and energy recovery standards are respected. Modifying the components and capacity of each disposal option produces new results. In this context, it is suggested to use alternative models.

Today, the consequences of climate change inevitably affect various aspects of human life and other living things, and their effects are increasing day by day. Such consequences, which of course have a "physical" nature in their early stages (such as temperature increase, floods, severe climate changes, soil erosion and desertification) towards social and economic dimensions and in the form of migration, loss of resources, change of location, cultural displacement, confusion, social unrest and other cases occur. Basically, policy-making in criminal prosecution should be done with regard to the characteristics of climate change, and on the other hand, this response should be focused on behaviors and crimes that have a significant effect on climate change and intensifying the climate situation or speeding up its process. The criminal response to climate change should be done with a specific mechanism and it cannot be limited to a specific country. This is why global legal responses through relevant conventions and strengthening the functioning of social institutions and the establishment of specialized climate police will achieve better results. It seems that the state of response of criminal law to climate change in Iran is not future-oriented and the type of response is based on looking at the past and not reviving the climate situation or strengthening preventive response regarding such criminal behaviors. In addition, in Iran, in some cases, such as ecocide, fraud in carbon emissions, etc., there are no regulations for punishing and prosecuting them.

By assessing the trend of air temperature changes, it is possible to explore traces of climatic changes in the area of Iran. Climate change and temperature increase are important human-environmental issues. Based on the change point method, it is possible to identify the onset time of changes in basic variables such as minimum and maximum temperature. Therefore, the present research aims to analyze the change point of temperature thresholds of heat and cold waves in Iran. The temperature threshold means the 95th percentile for maximum temperature values and the 5th percentile for minimum values. For this purpose, the temperature data (minimum and maximum) of 43 synoptic stations in Iran, which have a long statistical period (1966-2018) and suitable distribution, were used. To identify the temperature threshold change time, three change point methods - Pettitt, SNHT, and Buishand's Range Test were used. The results showed that the temperature threshold of heat and cold waves has been increasing over the past few decades. The rising growth rate is equal to 0.019 and 0.052 degrees Celsius per year, respectively. Therefore, in the current study, it was found that the increasing trend of the temperature threshold led to an increase in the frequency of maximum temperatures, and on the other hand, it will lead to an increase in hot days and a decrease in cold nights, in addition to the higher frequency of events, it can be stated that the frequencies will move towards higher values. Based on the results of the spatial-temporal analysis of the thresholds, the increasing trend of the minimum temperature in the northwest, Zagros, and southeast regions of Iran is quite evident. And from the other results of this study, we can emphasize the time of the change point or jump of the temperature threshold of cold and heat waves around 1991. The mentioned year is in line with global studies

The zero-carbon or low-carbon city is a new approach, which is rooted in sustainable urban planning. The main goal of this model is to reduce greenhouse gas emissions and carbon dioxide in urban areas. Sari, which is the capital of Mazandaran, contains natural resources and is located in an especial geographical location. As a consequence of recent years' development, the city has gone out of the way of harmonious development with nature. This study aims to compile indicators and criteria of the zero-carbon model for Sari city. Thus, the document study method is used as the tool to review the general condition of the city and basic indicators and criteria. Then, the depth interviews were conducted with the experts and the analysis has done by MXQDA to find out the indigenous criteria and indicators. After that, the indicators and criteria were scored and prioritized by experts. As a result, this study would place applied and descriptive-analytical in terms of purpose. The final result has shown that land use, management, and policymaking are the top three indicators, respectively. The means of sustainable transportation, reusable energy sources for neighborhoods, and green infrastructure are the main three indicators. In conclusion, the physical variables are not the only effective elements in planning a zero-carbon city, raising awareness and making suitable policies for encouraging citizens' participation are also efficient.

Media determine for public opinion or politicians that should think about what topics and the amount of importance of issues by using agenda-setting theory. There has been a lot of scientific researches on how to cover climate change news in different media in other countries, but in Iran as one of the top ten emitters of greenhouse gases that is also one of the world's most vulnerable countries to climate change due to its geographical location, such researches have rarely been done. This study is one of the first scientific researches that attempt to understand precisely how climate change news has highlighted in Iranian dailies.The theory of agenda-setting and quantitative content analysis has been used to achieve this goal, and fifteen well-known Iranian dailies reviewed from two weeks before to two weeks after holding the United Nations climate change conferences of Bonn 2017, Paris 2015, Copenhagen 2009 and Montreal 2005). Finally, have been gathered 3905 environmental articles that 388 articles were about climate change issues.The findings showed that the Iranian dailies had got a poor performance in highlighting climate change subjects. The news coverage of the conferences has decreased from Copenhagen to Bonn, indicating that as global warming and its consequences increased, the Iranian press's attention to the issue has diminished. As well as the political perspectives of dailies have been evaluated influential on how to highlight climate change news, and there were significant differences between them in the ways of covering climate change news too.

Cloud seeding has been used in many countries in recent decades to combat drought, reduce pollution, and mitigate global warming, among other things. Local and state laws govern the process in the United States. Due to differences in state laws, the broad extent of the land covered each time has perplexed seeders, affected people, and courts of law. Due to the sheer lack of federal laws and inconsistencies in state laws, those affected by the negative effects are legally helpless, while the offenders escape punishment. This research seeks to answer the following questions: “How well do existing laws meet current legal needs in this regard?” and “Is there a way to eliminate the potential shortcoming?” A descriptive-analytical approach is used to investigate issues arising from the lack of a federal law and the state jurisdiction of current laws. The goal is to demonstrate the inadequacy of existing laws and the need for comprehensive federal legislation. Giving the benefits and drawbacks of federal law regulation, presenting solutions to eliminate the drawbacks, and demonstrating the ineffectiveness of general responsibility laws, the benefits of developing such a law that governs state laws outweigh the drawbacks. The inadequacy of current laws in terms of their enforcement serves as further evidence of the necessity of establishing an organization to control, manage, and monitor cloud seeding.

The planet Earth is experiencing the increasing effects of climate change. The consequences of climate change, such as extreme heat, water shortage, drought, floods, desertification, micro dusts, are also rapidly becoming apparent in Iran. This article answers this question that “Are the consequences of climate change a threat to the existence and national security of Iran?” The hypothesis of the article is formulated in such a way that “climate change is a super-crisis and immediate security threat that can face the country from the inside with economic instability, social tensions, displacement of the population and a decrease in government legitimacy. From the external aspect, it can also be the basis of alliances and coalitions and conflicts between Iran and its neighbors over common watersheds.”The results of the research show that Iran's government should overcome the strategy of indecision in the issue of climate change consequences. Because the widespread and unforeseen of climate change can be second only to a global nuclear war. The theoretical framework of this article is Copenhagen security theory and the research method is descriptive-analytical.

One of the consequences of the increase and accumulation of greenhouse gases in the atmosphere is kown as global warming, which is undoubtedly one of the most important environmental challenges in the world, especially in the Middle East. Given the scarcity of water resources in recent years, the consequences of global warming and climate change in various countries have reached a very worrying level. Carbon dioxide and Methane are known as two of the most important human greenhouse gases in the atmosphere, accounting for 64% and 18%, respectively, of long-lived radiation induction (LLGHGs) (Forster et al, 2007). Methane is considered as the second most important anthropogenic greenhouse gas after Carbon Dioxide.The most important sources of Methane emissions include: biomass incineration, artificial human emissions, wetland emissions, and wastes. Despite the importance of Methane for physical and atmospheric conditions, the spatial distribution of global resources and Methane sinks is not well understood. With the launch of Methane measurement from satellites, knowledge about the global distribution of Methane in the atmosphere greatly increased.The Japanese Greenhouse Gas Satellite (GOSAT) is the only satellite that measures the column mixing ratio of atmospheric Methane. Since the 1990, various global models have been used to simulate CH4 concentrations. High-resolution simulation of CH4 at hourly intervals on Earth, with diverse ecosystems, due to the lack of intensive spatial and temporal measurements and the impossibility of reliable validations for chemical simulations are known as a serious challenge. The main purpose of this study is to understand the performance of the WRF-GHG model in simulation of Methane concentration and validation the results of medium-scale modeling output in total Methane concentration in comparison with GOSAT satellite observations over Iran.

Iran and some area of its surroundings is considered as a study area. This study focuses on two case periods of hot and dry (August 31-2010) and cold and wet (February 1-28, 2010). In order to provide the initial and boundary conditions of meteorological fields, ERA5 reanalysis data were used with a horizontal resolution of 0.25 ° with a time resolution of 6 hours. Different emission input data from three different global greenhouse gas emission databases EDGAR_v5.0 (anthropogenic emissions), GFAS emissions (fire emissions), and datasets (CMS_V01) (wetland emissions) have been used.Preliminary and boundary conditions for the chemical fields taken from atmospheric monitoring service data (CAMS) with a spatial resolution of 0.8º with 137 vertical levels and with 6 hours time resolution. To investigate and quantify the validity of meteorological fields simulated by the WRF-Chem numerical model, a set of observations of selective synoptic stations is used. For validation of CH4 WRF_Chem column concentration and statistical analysis, in the points that include remote sensing data (GOSAT sensor data), is used the set of level 2 products generated by the NIES algorithm. The local transit time of the GOSAT satellite Is approximated around 13: 00_9: 00, so the simulated concentration for this time is applied in the analysis. The first 15 days of the simulation are omitted to take into account the spin-up time. Statistical parameters of mean bias error (MBE), mean absolute error value (MAE), root mean square error (RMSE), and Pearson correlation coefficient (R) in meteorological and chemical variables are studied for validation of numerical simulations and quantification of error levels.

The model has been able to calculate temporal changes in surface temperature, relative humidity, and wind speed to some extent correctly. The general tendency of the model to simulate the observed temperature and relative humidity for the selected time period is evaluated. In general, model values are closer to summer observations than all thirty days in two selective months. The wind speed forecast is often consistent with the wind speed values obtained from the measurements, and in most cases, the wind speed is overestimated at around 1.2 m/s.Statistical evaluations of the WRF-Chem model, together with the GHG gas-phase chemistry mechanism, show the simulation of Methane concentration versus observations by the GOSAT satellite, and the estimation of the average monthly concentration in February and August 2010. The values of MAE, RMSE, RMSE_u, RMSE_s, BIAS and R are calculated equal to 42.92, 46.05, 7.82, 44.60, -24.99 and 0.63, for hot and equal to 12.01, 13.94, 7.09, 11.68, 7.50 and 0.76 ppb, for cold periods respectively. It can be seen that the WRF-Chem model performed better in Methane simulation in cold and wet periods (January) compared to the hot and dry seasons (August).

In this study, the WRF-Chem model was used to simulate meteorological variables and air pollutants (methane greenhouse gas) concentrations in the Middle East-Iran region during the study period of February and August 2010. The sensitivity of the model is considered using the GHG gas-phase chemistry scheme. The main findings of this study are: The model is able to reproduce temporal changes in surface temperature, relative humidity, and wind. The model underestimates the air temperature and relative humidity respectively around, 1/05 ⸰C -5% in the study area (Iran).In simulating of Methane concentration, and examining the results with related GOSAT satellite observations, the model overestimates around15 ppb of the Methane concentrations. The evaluation results show that the WRF-Chem model performs better in the cold season (January) than in the warm season (August). This uncertainty in CH4 simulation can be attributed to a deficiency in various input components of the CH4 emission in different categories. Improving the simulation for the various parameters reported to the model as the primary CH4 emission can generally help to improve the CH4 simulations.

Increasing global warming is one of the major global issues of the current century. For this reason, it is important for humans to study and evaluate its trend, so simulating this climatic variable can be a way to understand the human future. There are several methods for simulating and predicting heat waves, the most valid of which is the use of the general circulation model of the atmosphere and GCM. One of the most widely used models for GCM data miniaturization is the LARS WG statistical model. In the present study, the efficiency of this model for exponential micro-scale of heat waves in Julfa station was evaluated. To achieve this goal, daily statistical average maximum temperature above 35 ° C in a given statistical period has been used. Also, to predict the heat waves in the coming years, the maximum temperature data of the models (CESM CAM, CMCC CMS, CAN ESM, MPI ESM) under the RCP8.5 scenario for the next period 2011-2016 were performed. The results showed that heat waves in the future period (2011 2065) have a normal distribution compared to the base period. . Therefore, these results show the very good performance of the LARS WG model in simulating heat waves. Jolfa station heat waves in the base periods (1990-2020), with severe irregularity and variability of annual heat wave events, indicate a strong variability of the average annual temperature and a variety of factors affecting the temperature of the region. On the other hand, according to the forecast of MPI ESM, CESM CAM and CMCC CAM climate models, the temperature of the annual heat waves that go towards more heat in the warm period;

Increasing the global population requires food security, especially in developing countries. In this regard, greenhouse systems have significantly increased efficiency due to resource constraints and advantages such as the possibility of more than one harvest per year. This issue is vital in arid and low rainfall areas such as Iran. These systems require higher energy consumption than traditional methods due to their greater sensitivity to environmental conditions such as temperature and humidity. It is predicted that in the next 50 years, energy shortages and how to supply them will be one of the most fundamental issues and one of the ten most important challenges in the world. As a result, energy supply is considered an essential indicator for the development and progress of industrial greenhouses. On the other hand, urban development includes economic, social, and environmental approaches that must align with sustainable development. Management problems in this process always exist between the urban space, stakeholders, and urban infrastructure. This complexity requires multidimensional approaches and specific quantitative or qualitative methods for analyzing and combining different aspects. In this study, by modeling grid-connected renewable power generation systems in Homer software, an optimal hybrid system has been introduced to reduce greenhouse gas emissions. In addition to examining environmental and technical parameters, economic parameters have received much attention in this research. The crop under cultivation in the greenhouse was cucumber; the main reason for choosing it was the significant number of cucumber greenhouses in this city and easy access to the data of the cucumber greenhouses. Of course, the data related to other agricultural products were also generalized, and even regardless of the type of product, each greenhouse can obtain the current net cost of its greenhouse only by estimating its bioelectricity. This can be a good guide for all greenhouses in the same climate with any product. Sensitivity analysis on inflation and interest rates also helps farmers and the government work with full awareness in this area, thus providing the necessary conditions for sustainable urban development.

This research includes studying energy systems in greenhouses located in Robat Karim city. Based on this, the renewable energy sources in the area have been studied and evaluated. According to that, the corresponding components in Homer software have been designed and modeled as connected to the network. Homer software is used to power many items such as buildings, hotels, and villages, by simulating energy consumption and performing economic and technical analysis on hybrid systems. In addition to analyzing economic parameters, it Analyzes and examines environmental parameters and how to generate optimal power.

After examining different scenarios in Homer software, each of which includes two or more primary components, three scenarios have been selected as the top scenario, the optimal scenario including solar panel, wind turbine, and battery. In this scenario, the net present cost is $ 215,626, and the energy cost in this scenario is $ 0.084 kWh. Then the second scenario includes a solar panel, diesel generator, and battery, with a net present cost of $ 238,135 and a cost of energy of $ 0.094 kWh. Finally, the solar panel, wind turbine, and diesel generator scenarios were considered the last, with a net present cost of $ 240,626 and an energy cost of $ 0.094 kWh. The share of the renewable sector in the first to third scenarios is equal to 6.59, 6.47, and 4.59 percent, respectively. As mentioned, the primary purpose of this modeling is to reduce the emission of pollutants, which in the optimal scenario to prevent the emission of 66 tons of carbon dioxide, 18 tons of unburned hydrocarbons, and 200 kg of sulfur dioxide per year. These values are for a greenhouse with an area of 0.2 hectares. Meanwhile, the area under cultivation of greenhouses in Tehran province is about four thousand hectares. If only ten percent of the area of greenhouses in the province uses a combined system, it can prevent 132,000 tons of carbon dioxide. That is equivalent to the amount of carbon dioxide absorbed by 6,300 trees.

Tehran province is one of the most strategic parts of Iran in the greenhouse industry. The construction of new greenhouses is considered an urban development, which must be in line with sustainable development to be considered a suitable solution. In this way, renewable energy is considered an inevitable action. The inexhaustibility and non-production of pollutants are two crucial factors for the global acceptance of the use of renewable energy. In this research, an attempt has been made to model an optimal system by reducing the emission of greenhouse gases, especially carbon dioxide, by modeling renewable power generation systems connected to the grid in Homer software. Furthermore, to consider the project’s future possibilities, inflation and interest rates have been examined using the sensitivity analysis of Homer software. The investigation’s most significant findings include the following: • The best scenario includes a solar panel, wind turbine, and battery with a net present cost of $ 215,626 and an energy cost of $ 0.084 kWh. By providing subsidies and guaranteeing the purchase of renewable electricity, the government can encourage the use of hybrid systems and the grid connection, thereby providing part of the goal of reducing emissions. Solar and wind energy are the most suitable renewable sources due to easy access throughout the country, which play an influential role in reducing energy costs. • Using a hybrid system of solar panels, wind turbines, and batteries in grid mode can reduce carbon dioxide emissions by about 61درصد. In this way, we can take action to combat climate change for sustainable development and commitment to international treaties. • It is possible to increase the share of the renewable sector by increasing the capacity of solar panels, allocating more space, and in some cases, even supplying greenhouse energy without connection to the grid. Of course, it is recommended to use a network-connected system as much as possible to reduce costs. Finally, according to the studies conducted and the problems facing the use of renewable resources, it is recommended to create a significant change in the agricultural industry and control the emission of greenhouse gases in the country. Maximum government support should be provided through loans and facilities, appropriate policy-making, raising farmers’ awareness, encouraging the private sector.