جستجوی مقالات مرتبط با کلیدواژه « ارزیابی اثرات محیط زیستی » در نشریات گروه « جغرافیا »

The purpose of this research is to evaluate the positive and negative effects of the implementation of the steel project in joveyn city on the environment around it using the rapid impact assessment matrix of RIAM, and it has been done by separating the project and its environment into constituent factors.

The present research is analytical and applied in terms of method (quantitative and qualitative) and type, respectively. The environmental impact assessment method is suitable for achieving sustainable development goals. In this study, the important effects related to the construction of Joveyn Sabzevar steel plant were investigated using the RIAM matrix method in order to analyze the effects due the construction  of the unit in the construction and operation phase.

The findings show that the effect of project activities on physical and chemical factors, in the final summation in the physical and chemical environments related to soil erosion and sound effects (insignificant negative effects and changes), ground shaking, drainage, air quality and climate changes (significant negative effects) and in biological-ecological environments, it is related to the change of agricultural and garden land use (insignificant negative effect) and the effect on vegetation changes (significant negative effects). Cultural, social, economic, and technical environments showed positive effects and changes.

The results of this research showed that the construction project of the Jovin Sabzevar steel plant has 18 negative effects and changes and 10 positive effects and changes on different environments. Also, according to the results, compliance with environmental requirements should be considered.

application of the results evaluation and implementation of the steel project with the matrix method can determine the possibility or impossibility of implementing the project with less cost and time.

Development projects with their positive effects always have potential direct and indirect negative effects on the human and natural environment, and if the negative effects are not thought of in advance and are not strengthened in terms of positive effects, they will have adverse results and consequences. The purpose of the research is to evaluate the biological environment of the irrigation and drainage network of Khodaafrin dam in East Azarbaijan province and Ardabil in Khodaafrin and Parsabad cities. In order to investigate environmental parameters, three physical-pollution, ecological-biological and economic-social and cultural environments were used. Then, using the Icold matrix method, the effect of each of the micro-activities of the project on the environmental factors of the study area was measured in the exploitation phase, separately from the three mentioned environments. The findings showed that the implementation of the plan is preferable to its non-implementation in such a way that the total consequences of the implementation of the plan on the surrounding environment are positive 274 points. Among the consequences of the implementation of the socio-economic and cultural environment plan, it has the most positive effects of 186 points, physical environment and pollution with 46 positive points, and ecological and biological environment with 42 positive points. According to the findings, the implementation of the irrigation and drainage network plan of the main KhodaAfarin canal is justified by complying with the standards. In order to reduce the negative effects on the three environments, it is suggested to consider continuous and stable monitoring and compliance with the correct principles of irrigation during the operation of the project.

Landfill development in a place can potentially affect the physical, biological, economic and social factors of the place. This study aims to identify the appropriate landfill in Bardaskan city located in the west of Khorasan Razavi province and also to investigate the suitability of existing landfill for this use. To do this, first, environmental criteria affecting the selection of suitable landfill development site were identified, mapped, and weighed using the AHP process. Weighing results showed that geological criteria, distance from drinking wells, and distance from Bardaskan city with weights of 0.173, 0.172, and 0.124, respectively, are the most important in identifying suitable site. Aftertaht, landfill site selection was performed using Multi-Criteria Evaluation by WLC method. The WLC suitability map was classified into five categories, including very low to very high suitability, and based on this, potential landfill sites were identified. According to the results, 5% of the basin had very high suitability and 32% had high suitability for developing landfill site. Also, the existing landfill site based on the suitability map indicates that it is in a good category. In the next step, in order to choose the best site for the landfill, the Iranian Leopold matrix was prepared and completed for each of the selected zones. The evaluation results showed that among the investigated areas, the current landfill - with remedial measures - is the best place for landfill site in this basin. The proximity of water resources (rivers and aqueducts), a long distance to the city of Bardaskan, and unsuitable soil were the most important reasons for removing of other areas.

The purpose of this study is to evaluate the positive and negative consequences of the project construction of the Sabzevar antenna railway to Mashhad-Tehran railway on the surrounding environment using the Pastakia matrix and by breaking down the project and its environment into constituent factors (acceptable environmental factor - project micro-activity) has taken place.

The present research is analytical and applied in terms of method (quantitative and qualitative) and type, respectively. By implementing this environmental impact assessment method, a suitable tool is obtained to ensure the proper implementation of the project. This evaluation method can be considered a method for determining, predicting, and interpreting the railway project's environmental effects on the region's environment and the ecological health of its systems.

The findings show that the effect of the project's activities on physical and chemical factors, in the final summary, only in the case of the effect of drilling on the shape of the earth, had negative effects and changes. Biological-ecological factors have created The most negative effects on vegetation and agricultural and garden lands. The socio-cultural environment showed positive effects and changes. In examining the economic and technical factors of implementing the railway construction project on the environment, the only factor with negative effects is the cost of change of use.

The results of this study showed that the railway construction project has a total of 10 negative effects and changes and 5 positive effects and changes on different environments. Also, according to these results, it is recommended to comply with environmental requirements.

Innovation: 

Evaluation and implementation of the railway project with the Rapid Matrix method can determine the appropriateness or inappropriateness of the project at a lower cost and in a shorter time.

Nowadays, the problems of solid waste, which is the natural output of human daily activities, have become one of the most important issues. The amount of solid waste generated has increased significantly over the past three decades, and the characteristics of the waste have changed due to changes in people's lifestyles, developments in the environmental industry, and significant population growth. In many developing countries, inappropriate management of hospital and health care waste has direct adverse effects on community health and the environment. Solid and hospital wastes are mixed and complex subjects and at the same time critical for cities. It is predicted that waste production will increase from 1.3 billion tons per year to 2.2 billion tons by 2020. As a result, many cities in developing countries face many problems in landfill management. The city of Kerman, like other cities in the third world, has experienced population growth in different periods of time and this growth and development of urban planning in most developing countries has become an uncontrollable process. Hospital waste disposal machines in Kerman are operating with limited capacity and identifying a suitable location for the establishment of the main hospital waste disposal center of medical, medical and laboratory centers seems necessary. The main purpose of this research is to find the safest place and the most efficient scenario for disposing of hospital waste in Kerman.

In this research, information has collected through library, field studies and descriptive-analytical methods. Scope of the study is the political border of Kerman city. In the first step, the most effective criteria and data identified; Data related to communication routes, waterways, rural urban areas have removed from the 1: 25000 topographic map as the main research tool. The slope layer also has extracted from the Aluss-Palsar. The geological layer extracted from the 1: 100000 scale geological map. Land use maps and protected areas extracted from Landsat 2020 satellite imagery. After classifying the available indicators, valuable questionnaires 1 to 9 provided to experts to prioritize the indicators. At this stage, each layer evaluated and prepared based on how it affects the determination of suitable land for sanitary burial. Then, using GIS software and AHP-Fuzzy model, the optimal location was determined to determine the landfill of hospital waste in Kerman. In order to evaluate the scenarios of hospital waste management in Kerman, Fuzzy- RIAM method used. In the fuzzy Riam method,first the activities of each project are identified and then their effects on each of the environmental components, including physical / chemical, biological / ecological, social / cultural, economic / technical parameters, are determined.

In the AHP model, the slope criterion with a score of 0.218 has the highest weight among the studied indicators, followed by lithology and distance from the waterway. The location of landfills due to issues such as water pollution, air pollution, pests, dust, fire, traffic and noise, as well as the economic cost of the surrounding areas cause dissatisfaction of urban and rural residents. Accordingly, in the distance index from the city, the distance of 35-45 km has gained the most weight. The most desirable distance for rural areas according to the obtained weights is 5-10 km. According to Figure 10, the density of villages in the western and southwestern parts of the city has reached a maximum. Waterways and rivers are very sensitive to the entry of pollutants into their systems. According to the results, the distance from the waterways should be at least 3 km. Figure 12 shows the distance of waterways at the city level. The Protected Area is located in the southwest of the region, which is of great ecological importance. According to the results, the most appropriate distance from protected areas is more than 4 km. Among all the land uses in Kerman city, the highest weight related to barren lands and then poor pastures. The most unsuitable places for landfilling are located in the western and southern parts of the region, which mainly include agriculture and orchards. The most suitable slope for landfilling is less than 5 degrees and the aftermath is 5 to 10 degrees. Geologically, in the city of Kerman, the western and northwestern parts are in an unfavorable situation, because these parts are the location of young bed alluvium and alluvial fans, which provide agricultural land. The density of the fault in the western part of the region and parallel to the eastern heights of Kerman has made this area unsuitable for locating landfills. According to the criteria studied in this study, waste landfills are located more than 35 km from the city of Kerman and more than 5 km from the surrounding villages. In the study area, suitable places for disposal of hospital waste cover an area of about 17,000 square kilometers, which covers 37% of the area. Evaluation of waste management scenarios showed that plasma method in hospital waste management has the least negative environmental impact in terms of physical-chemical components and in terms of biological-ecological components and the most negative effect in terms of economic-technical components is related to plasma.

The results of the AHP-Fuzzy model showed that the most unsuitable places for landfilling of hospital waste in Kerman city for reasons such as location on permeable formations, proximity to fault lines, high groundwater level, proximity to protected areas and proximity to residential centers in the western parts of the region and the central part of the region is studied. In case of financing the plasma method, this method recommended for hospital waste management in Kerman. The least negative effect in terms of economic-technical (operational) components related to the landfill.

Increased waste production due to population growth and improper landfilling is one of the most significant problems in urban communities. Environmental impact assessment is one of the tools that has been introduced to predict and reduce the destructive and harmful effects of construction projects. Therefore, in the present study, the impacts of unprincipled exploitation of Quchan’s landfill on the environment (EIA) was assessed using existing reports and satellite images, field studies, and considering the influential factors of environmental geotechnics in Iranian matrix. Analyzing the Iranian matrix shows that the number of effects and consequences of the negative algebraic mean is equal to 3 and 5, respectively. However, the negative effect and consequence less than -3.1 in the column and row are related to leveling and ground preparation, bed rupture and wall stability, respectively. More investigation on geotechnical parameters indicated that the factor of safety (FS) of gravel walls needs improvement. It was shown that in Quchan’s landfill, in case of excavation with a slope of less than 35 degrees and excavation height of about 4 meters, the existing trenches will not slip. Therefore, the necessary modification and improvement is necessary for the wall retaining and appropriate results and solutions have been provided to improve the conditions.

Nowadays, environmental risk assessment has been defined as one of the effective in environmental planning and policy making. Considering the position and structure of vegetation on the forest floor, the main role of forest under canopy vegetation cover can be noted in attracting and preventing runoff in the forest floor and reducing subsequent environmental risks. The purpose of this article is forest under canopy vegetation density changes modeling considering forest ecosystem structure and forest management activities as an environmental risk. The main objectives of this study were to: (1) model forest under canopy vegetation density in forest ecosystem to elucidate the ecological and management factors affecting on under canopy vegetation density; (2) prioritize the impacts of model inputs (ecological and management factors) on under canopy vegetation density using model sensitivity analysis and (3) determining the trend model output changes in respond to model variables changes. In this study, Land Management Units (LMUs) were formed in the region considering ecological characteristics of land. LMUs were mapped out based on Ian McHarg’s overlay technique by ARC GIS 9.3 software. Ecological factor classes of an LMU differ from ecological factor classes of adjacent LMUs (at least in one ecological factor class). The following types of data were solicited for each LMU:(1) Ecological variables: Altitude or elevation (El), Slope (Sl), Aspect (As), soil depth (SD), Soil Drainage (SDr),Soil Erosion (SE), Precitipation (Pr), Temprature (Te), trees Diameter at Breast Height (DBH), Canopy Cover (CC), and forest Regeneration Cover (RC). (2) Management variables: Cattle Density (CD), Animal husbandry Dsitance (AD), Road Dsitance (RD), Trail Dsitance (TD), logs Depot Dsitance (DD), Soil Compaction (SC), Torist impacts (To), Skidding impacts (Sk), Logging impacts (Lo), Harvested trees volume (Ha), artificial Regeneration (Re) and Seed Planting (SP). (3) Forest under canopy vegetation density: The percentage of under canopy vegetation density in each LMU was estimated by systematic random sampling method. In each LMU, a one square meter sample was taken. The average percentage of under canopy vegetation density in sample units of each LMU was calculated and used in the modeling process. ANN learns by examples and it can combine a large number of variables. In this study, an ANN is considered as a computer program capable of learning from samples, without requiring a prior knowledge of the relationships between parameters. To objectively evaluate the performance of the network, four different statistical indicators were used. These indicators are Mean-Squared Error (MSE), Root Mean-Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R2). Various MLFNs were designed and trained as one and two layers to find an optimal model prediction for the under canopy vegetation density and variables. Training procedure of the networks was as follows: different hidden layer neurons and arrangements were adapted to select the best production results. Altogether, many configurations with different number of hidden layers (varied between one and two), different number of neurons for each of the hidden layers, and different inter-unit connection mechanisms were designed and tested. In this research, 129 LMUs were totally selected, then ecological and management variables were recorded in them. In the structure of artificial neural network, ecological and management variables were tagged as inputs of artificial neural network and the percentage of under canopy vegetation density was tagged as output layer. Considering trained networks (the structure of optimum artificial neural network has been summarized in Table1), Multilayer Perceptron network with one hidden layer and 4 neurons in each hidden layer created the best function of topology optimization with higher coefficient of determination of test data (which equals 0.857) and the lowest MSE and MAE (which are 0.866 and 0.736 respectively). Considering the results of sensitivity analysis, ecological and management variables like the forest canopy density, cattle density in forest, soil erosion and soil compaction respectively show the highest impact on forest under canopy vegetation density changes (Fig1). Table1. The structure of optimum artificial neural network in forest under canopy vegetation density Output Layer First Hidden Layer Network features Linear Hyperbolic tangent Transmission Layer Gradient descent Gradient descent Optimization Algorithm 0.7 0.7 Momentum 1 4 Number of Neurons -0.9 up to 0.9 -0.9 up to 0.9 Normalization Table2. The structure of optimum artificial neural network in test data MSE MAE RMSE R2 Data The structure of network( the number of neurons)-epoch 0.716 0.678 0.846 0.931 Trainning Tanh(4)-160 0.793 0.703 0.891 0.894 Validation 0.866 0.736 0.931 0.857 Test Fig1. The results of sensitivity analysis of artificial neural network model Nowadays, artificial neural network modeling in natural environments has been applied successfully in many researches such as water resources management, forest sciences and environment assessment. The results of research declared that designed neural network shows high capability in forest under canopy vegetation density modeling which is applicable in forest management of studied area. Sensitivity analysis identified the most effective variables which are influencing under canopy vegetation density. So, to identify hazardous LMUs in study area, we should pay attention to the canopy density of LMUs as the variable with high priority in determination of under canopy vegetation density. We believe that, in hazardous LMUs in forests, we should pay attention to some modifiable factors of LMU, which is cattle density in forest, by timely plan for livestock elimination. The forest under canopy vegetation density assessment model, in forest projects impact assessment, could be a solution in decision making about forest plan structure and implementation of similar projects in similar locations.