جستجوی مقالات مرتبط با کلیدواژه "عدم قطعیت" در نشریات گروه "محیط زیست"

Climate change will change climate variables in the future. In order to reduce the negative effects of climate, it is required to project future climate variables. The purpose of this study is to simulate most realistic daily rainfall and temperature series for Tehran and Yazd, with arid climatic, in period of 2036-2065 with considering uncertainty.

the outputs of the CANESM2 under RCP scenarios were downscaled using LARS-WG. In downscaling, various characteristics of the large-scale scenarios were transferred to the downscaled scenarios. In most of the previous studies, only changes in averages have been considered. The uncertainties of emission scenarios and climatic variabilities were investigated using three emission scenarios and generating 100 series of 30-year variables for each scenario. So, a wide range of probable future scenarios is predicted and more reliable results are obtained.

The results show in the future, for both Tehran and Yazd, temperature will rise in most months of the year, while in some months it will decrease. Average maximum temperature in April will increase between 6.1 to 9.9 ºC in Tehran, and between 7.1 to 8.2 in Yazd, while it will decreases in September by 2.4 degrees in Tehran, and by 0.7 degrees in Yazd. Future annual rainfall will increase between 20% to 40% in Tehran and between 43% to 49% in Yazd. However, changes vary in different months.

Climate regime of both Tehran and Yazd can considerably change in the future. Therefore, adaptation strategies with climate change are necessary.

With the expansion and intensification of competitive environment in today's world, supply chain management has become one of the key issues facing businesses. It has influenced all the activities of organizations to produce products, improve quality, reduce costs and provide the services required by customers. On the other hand, as the volume of pollutants increased, the researchers sought to design networks that, in addition to economic optimization, focused on environmental factors in all sectors. Supply chain network design is a strategic and critical issue that provides an optimal framework for effective and efficient supply chain management. One of the most suitable areas for integration in supply chain networks is the design of closed-loop supply chain networks, which can prevent the overlap caused by the design of separate direct and reverse networks. In this paper, a mixed integer linear programming model for closed loop supply chain network design is presented. The latter model seeks to minimize costs, minimize environmental impact, maximize the amount of worn-out product collected, and maximize supply chain social responsiveness. The proposed model is implemented by Saba Battery Company, which produces various types of batteries. Since the proposed model belongs to the NP-hard category, an exact solution method and two multi-objective genetic algorithms and a multicomponent particle swarm were used to solve the model. Based on the research results, the cost objective function tends to create a supply chain network with a centralized structure in order to achieve a lower cost. The environmental objective function tends to create a network with a decentralized structure to reduce environmental impacts. The proposed models are able to provide a range of Pareto optimal solutions according to the different levels of applying fuzzy constraints to determine the final decision. The two algorithms differ in terms of time; NSGA-II is superior to MOPSO. Also, two algorithms are different in the MID criterion, MOPSO is superior to NSGA-II, and in the rest of the criteria, they are not significantly superior to each other. The proposed model was determined with Jimenez's deterministic approach and a deterministic auxiliary model was proposed. This model was solved using the epsilon constraint method and two multi-objective genetic algorithms and multi-objective particle swarm

NAIADE (Novel Approach to Imprecise Assessment and Decision Environments) is a new multi criteria evaluation method which performs the comparison of alternatives on the basis of a set of criteria. It allows the use of information with different types and degrees of uncertainty. The values assigned to the criteria for each alternative may be expressed in the form of crisp, stochastic, fuzzy numbers or linguistic expressions. NAIADE does not use traditional weighting of criteria, rather it applies a pairwise comparison technique, and generates a ranking of alternatives (e.g. problem formulation). NAIADE allows for two types of evaluations. The first is based on the score assigned to the criteria of each alternative using an impact matrix (alternatives vs. criteria). The second analyses conflict among the different interest groups and the possible formation of coalitions according to the proposed alternatives (equity matrix: linguistic evaluation of alternatives by each group). NAIADE is considered as an efficient technique in various managerial investigations and environmental studies and has been utilized frequently in recent years. Unfortunately, there is no report on this method in Iran; therefore, the current study aimed to evaluate and introduce the method in Iran. It is hoped that the method acts as a step towards elevating the awareness and knowledge in different levels of society, authorities, and executives as well as improving quality of the environment.

By intensifing environment degradation as a result of increasing demand for ecosystem services, ecosystems will not be able to provide essential services for human communities in the near future. Therefore, it is essential to predict the effects of ecosystem change on service supply through modeling process. Hydrological models such as Soil and Water Assessment Tool (SWAT) have been proposed as robust tools for quantifying the ecosystem services in watersheds. Gorganrood watershed is one of the most important watersheds in the North of Iran which is highly affected by agricultural activities. In recent years, climate change, drought and human activities such as landuse change and deforestation have affected the potential of ecosystems in soil retention in Gorganroud watershed. Therefore, this study aimed to quantify soil erosion regulation ecosystem service under climate change using SWAT hydrological model. To achieve this purpose, after simulating monthly discharge and sediment in Arc SWAT, SUFI-2 algorithm was used to perform the combined calibration and uncertainty analysis process for 1976-1990. The model was then validated for 1991-1994. Values of NS= 0.7 and NS=0.64 indicate the satisfactory and good performance of SWAT model in simulating monthly discharge and sediment, respectively. Finally, the Erosion Control Index (ECI) was spatially quantified and mapped. The results show that the delivery level of erosion control service is severely affected by climate change. This research also shows that SWAT model can be used as a valueable tool for quantification of hydrological ecosystem services. However, further analysis is required after simulation.

In this paper climate change impacts on daily precipitation, daily maximum, and daily minimum temperature are estimated, while joint uncertainties due to natural climate variability and emission scenarios are estimated. By considering these uncertainties, the results incorporate a wide range of future possible situations which is a great importance in increasing the reliability of the results.

For downscaling of future GCM scenarios, Weather Generator method is used using LARS-WG model. CGCM3 outputs for based on three emissions scenarios, medium (A1B) and high (A2), low (B1), are downscaled for Zanjan. Uncertainty due to natural climate variability is estimated by comparison of 90% limits of 100 LARS-WG generated series for historic and for each future climate scenarios.

The results of this research show that the daily minimum and maximum temperature will increase in the future. Despite the Uncertainty due to natural climate variability, if is expected that the monthly means of daily minimum and maximum temperature will increase for the entire calendar months. Moreover, the uncertainty of emission scenarios is low in comparison with the future increase in temperature. It is expected that the average of monthly precipitation will decrease for the most of the calendar months; although, there is a little possibility for increase in precipitation due to natural climate variability.

In result of climate change, temperature and precipitation of the Zanjan will change in the future and uncertainties due to natural climate variability and emission scenarios are important in climate change impact assessment on precipitation and temperature.

Most of industries in terms of production rules, environmental concerns and economic interests are under pressure. A supply chain model is a network of facilities and activities which involve processes related to procurement of materials from suppliers, production and product development in production centers and distribution of consumer products in final destination. Long-term strategic decisions such as construction of facilities in the network need financial assets and optimal program. Issue of designing a supply chain network has attracted lots of attention of many researchers during the recent years. The main objective of this paper is to present a mathematical programming model that seeks to minimize the environmental impact in a closed-loop supply chain.

Researcher through library research and preparing a questionnaire to estimate parameters and data associated with the uncertainty of parameters and then through interviews, expert opinions about the limits and changes to the decision-making parameters have been collected. Then a fuzzy multi-objective mixed integer programming model is presented that model to minimize costs, minimize environmental impact and minimize the time of delivery of product.

After running the model, increasing objective function is to minimize the total cost, minimize environmental impact and minimizing the time the product reaches the customer contact temperature limits for different values were obtained. These values using Epsilon limitations in the software GAMS obtained.

In this study, the proposed mathematical programming model is solved with an exact solution. The results showed the location and facility capacity and output in the manufacturing centers are determined.