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Introduction: Today, the food-energy nexus is a vital issue. Energy in the food production chain is an essential feature of agricultural development and a critical factor in achieving food security. Energy use in the agricultural sector has increased to respond to the growing demand of the population, as well the limited supply of cultivated lands, and the desire for high standards of living. Therefore, the agricultural sector is heavily dependent on energy that affects agricultural prices. Agricultural price fluctuations are one of the most critical challenges for policymakers. The rapid rise in food prices has a significant negative impact on social welfare, especially the poor in developing countries, which is an issue that is more critical in developing countries than in developed countries. According to the Food and Agriculture Organization (FAO) report in 2018, the food world price index increased from 89.6 to 229.9 during the period from 2002 to 2011. Our literature review shows a distinct lack of research on modeling and analyzing the linkage between agricultural input price shock, especially energy and agricultural commodity prices in Iran. Materials and Methods: The Markov Switching model is a popular non-linear time-series model that involves multiple equations and can characterize the time-series behaviors in different regimes. This model is suitable for describing correlated data that exhibit distinct dynamic patterns during different periods. So, considering the sensitivity of food security and the impact of agricultural input, the main objective of this paper is to develop an econometric model to gain reliable insight into the impact of energy consumption on agricultural inflation, using the Markov Switching approach. To estimate this equation, we will run a MS-AR model, some preliminary tests, such as unit root test and stability test, are employed to ensure the reliability of MS-AR estimation results. Results and Discussion: Due to use of time series data, it is necessary to check the stationary status of variables. We performed a common non-linear unit root test (Kapetanios, Shin and Shell (KSS), Zivot and Andrews, Lee and Strazicich). These results reveal that we can significantly reject the null hypothesis of unit root for API, PPI, FPI, and EC, implying that all four variables considered in this study are stationary with structural breaks at levels. The Markov-Switching model has the various types that each of these is a particular component of the regime-dependent equation. Therefore, to choose the best type, the Akaike information criterion was used, and the model with the minimum value was selected as the optimal one. After model estimation and selection, the LR test indicated that the hypothesis of linearity could be rejected in favor of a Markov switching model. According to this model, the period of the Markov switching model estimation is classified into two regimes. Approximately, all the estimated coefficients of the MSIAH (2) - AR (5) model are found to be significant at the conventional level. Conclusion: The estimation results are consistent with theoretical foundations illustrating the importance of input prices and energy consumption on agricultural commodity prices. As with most experimental studies reviewed, this study has also shown energy consumption has a negative impact on agricultural commodity prices. In other words, it can be contended that during the study period, agricultural input prices have been influential factors on agricultural commodity prices. The findings revealed that the low inflation rate and high inflation rate regimes are stable and that only extreme events can switch regimes. The results of the MS model showed that the effect of input prices on agricultural inflation is different in regimes. In the case of energy, the impact of energy consumption on agricultural commodity prices in the high inflation rate regime is less than the low inflation rate regime because the elimination of energy subsidies policy has been applied in the second regime (high inflation rate). Thus, the results indicate the asymmetric impact of energy consumption shocks on agricultural commodity prices. The effect of agricultural input prices on agricultural commodity prices indicates that Iranian agriculture is significantly affected by changes in input prices. In this study, changes in input prices were caused by various shocks, such as the elimination of energy subsidies and drought. Therefore, it can be concluded that the elimination of energy subsidies and drought were, directly and indirectly, able to affect agricultural inflations through the price of inputs. In conclusion, planners and policymakers must pay attention to this asymmetry in agricultural commodity prices volatility to increase the price stability in agriculture as much as possible by appropriate policy tools.

Background and Aim: Among the medical wastes, dental wastes have a high diversity and due to its high contents of hazardous, toxic, and pathogenic agents, therefore these wastes are of great importance. The aim of this study was to investigate and analyze the amount of waste produced in dentistry offices in Birjand. Materials and Methods: In this descriptive cross-sectional study, 48 dental offices in the city of Birjand were studied. Sampling was carried out by environmental health experts in three consecutive working days (Monday, Tuesday, and Wednesday) from every center. The Samples were divided into 5 categories such as semi-domestic, infectious, chemical-pharmaceutical, toxic and sharp material, Separated and weighed using a laboratory scale. Information was expressed as percentage by weight. Results: Based on the results, the total amount of waste produced in dental offices in Birjand was 7848.02 kg / year. percentages of semi-domestic, infectious, chemical-pharmaceutical, sharp material, and toxic wastes were 54.3%, 29.7%, 11.8%, 3.9% and 0.11% respectively. Conclusion: Considering the high volume of dental waste, especially infectious and hazardous materials, the need for separation and recycling in the office is evident. It is necessary to manage the wastes and their separation and recycling in source place.

Background and aims: Providing the adequate flow and water pressure in the firefighting network of the power plants requires the proper design and analysis of the firefighting system. This study aimed to model and hydraulic analysis the fire network in a combined cycle power plant to determine the network efficiency in the extinguishing of the possible fire. Methods: In the present study, the amount of water needed for firefighting network was estimated for different sections of the power plant according to NFPA standard. Then, based on general piping maps, isometric, and technical specifications of the site, network modeling was done using WaterGEMS software. Finally, the network efficiency was analyzed to provide flow and water pressure in three possible scenarios. Results: The results of this study showed that the network and pumping station could provide pressure and water flow for cooling and foam production to extinguish the small and medium-sized fire. In special circumstances and with the occurrence of extensive fire, such as the advent of fire in all fuel tanks, the pressure in the network is reduced to 3.6 bar and the pressure to extinguish, spray water, and the foam is not supplied. In other words, the system will not have acceptable performance in large fire extinguishing. Conclusion: Hydraulic modeling of the fire network using WaterGEMS software, in addition to identifying the defects of the fire extinguishing system, it can provide the ability to analyze and design the network to deal with the consequences of fire in industrial environments during crisis situations properly.

The energy management of ships to improve the efficiency of ships and reduce greenhouse gas emissions is among the most important issues that have been considered as a milestone in designing and constructing of vessels in recent years. The study of energy trends and attention to technological changes and the importance of more stringent environmental standards in recent years have led to a major challenge in relation to air pollution, energy management, and exposure to end-of-life sources of fossil fuels. In recent years, focus on current fuels and technologies in vehicles has led to a major challenge regarding air pollution, greenhouse gas emissions, energy security, and also exposure to exhausting sources of fossil fuels. Now days, Hybrid propulsion systems are one of the solutions that are being followed in many countries to solve this problem. In this paper, after introducing the hybrid system; conceptual design and determination of a suitable hybrid system for vessels have been investigated. Then the calculations and relations dominating the hybrid parallel system of vessel are presented. The modeling is also done using the ADVISOR software run in the Simulink platform of the MATLAB for both conventional and hybrid systems. The results show that parallel hybrid vessel has improved by 7% in total efficiency and 7.1% for consumption. In addition, HC and CO emissions have been decreased by 0.44% and 0.39%, respectively.

Due to the increasing cost and environmental impacts of fossil fuel consumption, using the renewable energies in data center has become an important and essential priority. Although using renewable energies has less environmental harmful effects, but the high investment needed for their installations as well as their fluctuating power production characteristic, restricts their usage such that most of data centers' managers prefer to use brown energy instead. In this paper, the power management and cost reduction techniques, with the aim of reducing break-even time, like using the electricity pricing models' opportunity and distributed Uninterruptable Power Supply (UPS) has been considered. In each time slot, the proposed Smart Power Manager Unit (SPMU) specifies the optimized distribution of power between available power supplies based on available solar energy, the price of electricity and the status of distributed UPS batteries; it also manages batteries charging and discharging. Results show that proposed method reduces the break-even time of investment cost on solar power installation to 0/8- 1/2 years that is 36% shorter than conventional method on average.

The rural community in Mazandaran is characterized by agricultural traits and rice cultivation. Indeed, agriculture plays an important role in the social, cultural, economic and environmental relations of rural communities in this province. Considering two types of agriculture, this study aims at the relationship between them and a sustainable system which farmers believe can be achieved in farming. The research method was both quantitative and qualitative. In the quantitative part, a questionnaire was used to collect the data. The farmers that were selected were those who had experience with modern agriculture under the influence of agricultural development programs. In the qualitative part, interviews were conducted with a sample of 20 farmers until data saturation. In this research, a sample of three villages around the city of Amol was selected where the farmers had experience with both traditional and modern agricultural systems. The findings show that, in terms of sustainability, there is a fundamental difference between traditional and modern agricultural practices. Based on the results of the analysis, traditional agriculture has a direct impact on sustainability, and farmers are aware of this. However, where the economy is prevailed by profit attitudes and the other sectors are not involved in agriculture, circumstances are not in line with sustainability.

Nowadays, greenhouse gas emissions and consumption of fossil fuels has led to environmental problems such as global warming which result in using low carbon energy sources and renewable energy as a potential substitute for fossil fuels and nonrenewable energy. This study is going to investigate Environmental Kuznets curve (EKC) for 11 elected OPEC countries, from 1980 to 2013 by using nonlinear quadratic model. The consumption of renewable and nonrenewable energy are considered together in this model which has been carried out by PMG (Pooled Mean Group). According to the outcomes of the research the Environmental Kuznets curve hypothesis is confirmed in these selected countries and studied period. The coefficient of nonrenewable energy consumption is statistically significant at the 0.01 significance level. Its estimated coefficient is 0.67 and states a 1% increase in nonrenewable energy consumption which leads to CO2 emission rise by 0.67%. It indicates that overusing of nonrenewable energy and fossil fuels increases environmental and air pollution. Also, the coefficient of renewable energy consumption is -0.005 that it is not statistically significant.

Introduction:Today, environmental issues have affected human life in the world, including Iran. Environmental problems are mainly the result of human use of natural resources and improper treatment of the environment, including the inappropriate use of fossil fuels. To achieve sustainable development, specifically in the field of energy, the knowledge of the correct ways of using natural resources and non-profit behaviors towards the environment, as well as proper ways to protect it must be considered. Given that new development approaches emphasize the need for the participation of all individuals and different groups in society, the role of environmental non-governmental organizations in achieving these goals, protecting the environment, and reducing vulnerability is very important. The purpose of the present study was to analyze the strategies of environmental non-governmental organizations in climate change and energy adaptation programs with a focus on an urban area. Materials and Methods:The approach of this research was interpretive. This study was conducted using contextual theory. Participants in this study were selected using purposive sampling in the form of snowball sampling, based on which 16 members of environmental non-governmental organizations in Tehran in 2019 were selected. Sampling in this study continued until it reached theoretical saturation. Accordingly, at the end of 16 interviews, data saturation was obtained. The data were collected using semi-structured interviews and analyzed using open, axial, and selective coding steps. In open coding, the data were first grouped into separate lines and categories, and a code or concept was attached to them. In the axial coding stage, the related raw codes were subdivided in terms of features and concepts. At this stage, the categories were connected as a network, and finally, the main categories and the core category emerged in addition to a paradigm model were extracted. The extracted paradigm model was divided into four parts: causal conditions, intervening conditions, strategies, and consequences. The four parts were formed around the central phenomenon. Discussion of Results and Conclusions:Data analysis showed that the causal conditions affecting the ways of attracting the participation of non-governmental organizations and the causes of the phenomenon of persuasion and related strategies were a sense of responsibility for the environment, scientific and executive ability of members, self-efficacy, and belief in the effect of individual action (effectiveness). Also, the intervening conditions affecting the phenomenon of persuasion were the weakness of society in the field of awareness (about individual duties, environmental knowledge, and status quo), lack of appropriate contexts in the society, weakness in group interactions, lack of proper infrastructure in buildings, and restrictions on laws. Besides, the results showed that the strategies adopted by non-governmental organizations were training and promotion of environmental knowledge at both intra-organizational and extra-organizational levels, improving local knowledge, fear and hope (the promise of a better future and fear of potential risks), sustainable local change (empowerment, alternative jobs, the formation of a local organization), profit and creating consensus between policymakers and active energy actors for legitimacy, division at the government, industry and university levels.The consequences of adopting these strategies were raising the level of awareness, responsibility, empowerment and independence of local communities, earning money, and prosperity of ecotourism. In general, the results of the present study showed that the main method of members of environmental groups to attract the participation of target groups was persuasion. To achieve this, the members of the non-governmental organizations have focused their efforts on educating and benefiting various groups. The results of this study can help other environmental agencies and government organizations to use the various capacities of environmental agencies.

This research investigates the existence and direction of Granger causality between economic growth, energy consumption, and carbon emissions in Iran. A multivariate model including economic growth, energy consumption, carbon emissions, capital stock, labor force, and urban population is used to determine eventual causality between variables according to Toda-Yamamoto Approach. Results indicate that there is a bi-directional causality relationship between gross domestic product and CO2 emissions. Also, there is a uni-direction causality relationship from energy consumption to CO2 emissions. Finally, the results maintain that the EKC hypothesis for GDP and CO2 emissions is relevant in the period of study.

Estimation of forest aboveground biomass is important in regional carbon policies and sustainable forest management. Since forests are the largest carbon store, it is important to evaluate the forest biomass to estimate carbon storage and its impacts on climate change in global scale. Optical and active microwave remote sensing data both play important roles in forest biomass monitoring. Our aims in this research are biomass modeling and estimation using multilayer perceptron neural network in Gorazbon district, Kheyroud Forest in Mazandaran province. Estimation was performed using the Landsat and ALOS PALSAR dataset and also 201 ground sample plots in two years of 2007 and 2012. The capability of the ALOS PALSAR Global Mosaic product with 25 m resolution was also evaluated in biomass estimation. The effects of environmental factors such as slope and aspect were specifically evaluated on the accuracy of biomass estimation. Finally, the best model was presented in 2012 by ALOS PALSAR Global Mosaic product with R2= 0.83 and RMSE = 108.99 which has very little difference from other optical and radar images. According to the research results, newer sensors using up-to-date technology will deliver much better results compared to the previous generations. Of course, to ensure these results, it is necessary to conduct additional studies in this field as well.