Original Article
Hashem Sadeghzadeh; Bijan Yeganeh
Abstract
Introduction: The study aims to select the optimal model to estimate the emissions from vehicles withcompressed natural gas (CNG) powertrain systems in Tehran to identify, evaluate and plan for controllingemissions through CNG vehicles, and determining the pollution level of passenger cars produced by ...
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Introduction: The study aims to select the optimal model to estimate the emissions from vehicles withcompressed natural gas (CNG) powertrain systems in Tehran to identify, evaluate and plan for controllingemissions through CNG vehicles, and determining the pollution level of passenger cars produced by the Iranianautomotive industries and compare it with pollution standards.Material and methods: In this study, locally-produced CNG vehicles' information was used to estimate thepollutants emitted from domestic CNG vehicles using IVE and COPERT modeling software. Finally, themodeling outputs were compared with the results of the ISQI emission test.Result and discussion: Results showed that contrary to the initial assumption, supposing IVE software wassuitable for advancing the research objectives, the performance of IVE software was not reliable for CNGvehicles, and the outputs of COPERT software were much closer to the values measured in the ISQI emissiontest. The COPERT estimated values were more accurate by 65 and 78 percent for carbon monoxide and NOX,respectively, but 13% worse for carbon dioxide.Conclusion: Based on the findings, the COPERT model is more accurate than IVE for modeling CNG vehicles'emissions, especially for CO and NOX. According to the findings, it is necessary to reconsider the superiorityand application of IVE software for determining the emission inventory and estimating the air pollutantsemitted from the CNG fleet in the country.
Original Article
Hamid Reza Rahmani; Zahra Khanmohammadi
Abstract
Introduction: Vegetables are the main food of the world's population, especially in developing countries. Currently, many vegetables, especially leafy vegetables, have a high percentage of nitrate due to the overuse of nitrogen fertilizers to accelerate vegetative growth. Many researches have been done ...
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Introduction: Vegetables are the main food of the world's population, especially in developing countries. Currently, many vegetables, especially leafy vegetables, have a high percentage of nitrate due to the overuse of nitrogen fertilizers to accelerate vegetative growth. Many researches have been done on nitrate accumulation in crops worldwide, because of the harmful effects of excess nitrate in edible plants for humans and live stocks. Due to the necessity of such studies in country as well as the control of nitrate concentration in leafy vegetable and cucurbits, this study was done to investigate and monitor the nitrate concentration in some leafy vegetables and cucurbits (cucumber, tomato, potato, eggplant, pepper, onion, scallion and leafy vegetables) produced in some greenhouse and farms of Isfahan province. Materials and Methods: In this study 142 different leafy vegetables (coriander, basil, chives, parsley, garden cress, dill, tarragon, mint, fenugreek) and cucurbits (fruit vegetables) including (cucumber, tomato, eggplant, pepper, onion, scallion and potato in coarse and fine sizes) collected from greenhouses and agricultural fields of Isfahan, Dorcheh, Falavarjan, Tiran, Dastgerd, Dehaghan and their surroundings. Nitrate content of plant samples was measured by spectrophotometer based on colorimetric method after reduction and production of aminoazo color complex. Then the nitrate concentration in the samples was compared with the maximum allowable nitrate concentration in agricultural products provided by the National Standard Organization of Iran.Results and discussion: The results showed that the mean concentration of nitrate in cucumber samples was 1.48 times more than the Iranian National Standardization Organization (90 mg kg-1 of fresh weight); whereas the mean concentration of nitrate in potato, tomato and pepper samples was lower than the standard limits provided by National Iranian Standards Organization (170., 150 and 200 mg kg-1 of fresh weight respectively). The mean concentration of nitrate in fine sizes of potato, tomato and pepper was more than nitrate concentration in coarse sizes. Between the studied cucurbits, the highest and lowest average nitrate concentration were observed in cucumber and tomato respectively. Also the average nitrate concentration in cucumber skin was 16.7 times more than the mean nitrate concentration of its fruit. In general, the mean concentration of nitrate in leafy vegetables was more than the Iranian National Standardization Organization (1000 mg kg-1 of fresh weight). Between the studied leafy vegetables, the average concentration of nitrate in mint (457 mg kg-1 of fresh weight), fenugreek (262 mg kg-1 of fresh weight) and tarragon (695 mg kg-1 of fresh weight) was just lower than the Iranian National Standardization Organization. The others leafy vegetables probably have nitrate limitation for consumption. Conclusion: According to the results, it seems that fruit size is not a suitable criterion for plant nitrate content and the management aspects of farms play a major role in plant nitrate content. On the other hand, the changes of nitrate content in the farms are very high, so it cannot be clearly stated that the consumption of vegetables is restricted in terms of nitrate content. However, it seems that the consumption of vegetables produced in the studied areas may be restricted for consumers’ health in some cases.
Original Article
Mohamad Reza Gili; Davoud Ashourloo; Hosein Aghighi; Ali Akbar Matkan; Alireza SHakiba
Abstract
Introduction:Given that agriculture has the most important role in ensuring food security (Johnston & Kilby,1989), it is necessary to prepare a map that shows the spatial distribution, land area, and type of crops cultivated with high accuracy (Cai et al., 2018). Agricultural land cover is relatively ...
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Introduction:Given that agriculture has the most important role in ensuring food security (Johnston & Kilby,1989), it is necessary to prepare a map that shows the spatial distribution, land area, and type of crops cultivated with high accuracy (Cai et al., 2018). Agricultural land cover is relatively dynamic and variable at relatively short intervals. This makes it difficult to classify crops on satellite imagery (Bargiel, 2017). The lack or absence of ground truth data is another cause. Therefore, methods that are less dependent on ground samples and use phenological features derived from time series of bands and vegetation indices to classify crops will be more appropriate (Ashourloo et al., 2020). The purpose of this study is to use a deep learning method based on convolutional networks to classify the crop types and improve the performance of this network by using feature channels as an input image to the network and increasing the classification accuracy. Materials and methods:In this study, the visible and near-infrared bands of Sentinel-2 satellite on 10 different dates from 2019 for an area in Idaho, USA, as an important agricultural area, and the cropland data layer for extracting the crop types ground labels was used (Han et al., 2012). Then, in MATLAB software, the time series of spectral bands were constructed and using them, temporal profiles of NDVI for any crop were extracted to identify the unique phenological features of crops. Then, the functions developed based on the phenological characteristics of crops were applied to the time series of the bands and a feature channel was obtained for each crop that in two separate processes, once bands and once again feature channels were used as input to the CNN and the network was trained and the results of network performance on crop classification in the test site, were compared.Results and discussion:In the first stage, the time series of bands formed the input of the deep convectional neural network and the network was trained in the training area, using the tempo-spectral information of bands as the input channels and crops ground samples as the related labels. Due to the spectral overlap of the crops in some time periods, network training was associated with a relatively high loss and therefore, for the test area, the overall classification accuracy was 69% (percent) and the kappa coefficient was 0.55. In the next step, the functions that were developed as phenological features for crops were applied on the time series of the bands, and for each crop, a feature channel was obtained as the special feature of that crop. Then the algorithm was implemented using these feature channels in the test area and the overall accuracy was upgraded to 86% and the kappa coefficient to 0.82 compared to which indicated a significant improvement in the results compared to the previous case.Conclusion:The deep convolutional neural network is very sensitive to the type of input channels for detecting agricultural crops and selecting the channels with suitable tempo-spectral characteristics for different types of crops, has a great impact on the accuracy of network training and can reduce the loss of training network and increase its efficiency in the classification of various crops.
Original Article
Razieh Pilehvaran; Zahra Rastgu; Sara Karami; Behrooz Moradpour
Abstract
Introduction: Natural hazards such as floods, earthquakes, landslides, etc. frequently occur in Iran and other parts of the world, causing considerable economic, social, and environmental problems. In recent years, dust outbreaks in the west and southwest of Iran have been rising, becoming one of the ...
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Introduction: Natural hazards such as floods, earthquakes, landslides, etc. frequently occur in Iran and other parts of the world, causing considerable economic, social, and environmental problems. In recent years, dust outbreaks in the west and southwest of Iran have been rising, becoming one of the most important environmental challenges in the region.Material and methods: In this research, a number of intense dust episodes have been selected out of 15 years (2004-2018) of the statistical period, in the warm and cold seasons over the western and southwestern parts of the country. At the first step, in order to detect and observe the intensity of the dust concentration over the study area, the MODIS AOD product from the Deep blue and Dark target algorithms has been analyzed using the ENVI software, and the generated images have been displayed in the ArcGIS software. In the second step, dust source detection has been carried out by the WRF/Chem simulation of the dust concentration and tracking the dust path using the HYSPLIT Lagrangian model.Results and discussion: The results of the simultaneous study of dust detection using satellite imagery, the simulation of dust concentration using the WRF-Chem coupled model, and the particle movement pattern with the HYSPLIT model showed that East of Syria and northern Iraq in the case studies of the warm season and the west and center of Iraq in the case studies of the cold season are the main sources of dust episodes in the west and southwest of Iran.Conclusion: Studying the source and transport of dust with the aid of WRF-Chem simulations and the HYSPLIT Lagrangian model provided a complementary decision making to predict the direction of dust motions and using the results in the air quality prediction and management.
Original Article
Balal Oroji
Abstract
Introduction: Implementing control plans, monitoring, and formulating traffic and management laws requires obtaining basic information about the origin of particles, physicochemical properties, and their behavior in the atmosphere. Gathering this information requires studying the various dimensions of ...
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Introduction: Implementing control plans, monitoring, and formulating traffic and management laws requires obtaining basic information about the origin of particles, physicochemical properties, and their behavior in the atmosphere. Gathering this information requires studying the various dimensions of the nature of particles, most of which will not be directly possible. The challenge of air pollution in the metropolis of Tehran requires fundamental studies, and in this study, we tried to present new dimensions of physicochemical and fundamental properties of atmospheric particles in Tehran. Material and methods: The particle collection process to evaluate their concentration and chemical composition was performed by a high-volume sampler for 1 to 24 hours and an average flow of 1.7 m3/min on fiberglass filters. Also, to determine the aerodynamic diameter distribution of the particles, a cascade sampler (Anderson impactor) with a flow of 28.3.3 L/min was used for 72 hours to 7 days. After sampling, the samples were prepared to determine the total concentration and aerodynamic distribution in the laboratory. Results and discussion: The results showed that the mean particle concentration during the sampling period was 118.6 ± 11.9 µg/m3. During the sampling period, the highest concentration of collected particles was 154.61 ± 22.1 and the lowest was 129/12 ± 23.15 µg/m3. The results of SEM analysis of the collected samples showed that the particles were present in a spherical, irregular, fibrous shape as well as crystalline shape. The predominant elements in these samples are K, Ca, Cl and Fe, which are found in combination with Ti, Zn. Cluster-like and amorphous structures rich in O, Zn, Mg, Fe, K, Si, and Na were observed in particles with dimensions of 2 to 7 micrometers. Conclusion: According to the results and comparison with other work done in this field, more particulate matter is emitted during fuel combustion processes by industry and urban transportation. Larger particles are also produced and emitted by vehicles, construction, and industry during human activities such as road dust.
Original Article
Masoud Ghaderian; Koroush Golkar; Pantea Hakimian
Abstract
Introduction: Following the discovery, development, and maturation of green infrastructures, researchers have defined them as an integrated network of natural and semi-natural elements, providing a wide range of features and ecosystem services including ecological, economic, and social benefits for humans ...
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Introduction: Following the discovery, development, and maturation of green infrastructures, researchers have defined them as an integrated network of natural and semi-natural elements, providing a wide range of features and ecosystem services including ecological, economic, and social benefits for humans and other species. Today, green infrastructures are considered a part of novel water management paradigms in urban form and water studies. Regarding the management of water in cities in Iran, particularly those located on the fringe of Dasht-e Kavir, it is necessary to outline the operational definition of green infrastructures as networks in the ecosystem on the fringe of Dasht-e Kavir. Moreover, it is important to explain green infrastructures in arid and semi-arid regions, detailing the features. Accordingly, this study aimed to identify green infrastructures in Iranian desert cities. To achieve this goal, two main steps were specified: 1. Operational investigation and definition of green infrastructures in the mature urban and water discourses and 2. Proving green infrastructures applicable in desert-fringe cities through cases.Material and methods: As the first step was determining the operational definition of green infrastructures, the content of literature related to the development and establishment of the concept of green infrastructures published between 2005 and 2020 was qualitatively analyzed. Consequently, a conceptual framework was developed for the operational definition of green infrastructures. In this study, content analysis used in qualitative studies was selected for examining the literature on environmental design with an inductive approach in order to identify the existing themes in the definition of green infrastructures. This method was selected to systematically analyze, summarize, categorize, and induce the literature including the definition of green infrastructures in order to shed light on the hidden meanings and pave the way for comparison with the infrastructures of historical cities located on the fringe of Dasht-e Kavir. In this study, the stages were in six steps: 1. Stating the problem, 2. Developing questions and aims, 3. Defining and determining variables, 4. Sampling and selecting analysis and background units, 5. Coding and categorizing, and 6. Analyzing, inducing, and reporting.Results and discussion: The results of the qualitative content analysis yielded seven categories as follows: 1. The morphology of green infrastructures is influenced by the systemic nature of urban networks which consist of natural and artificial elements in the form of patches, corridors, and matrices to ultimately connect water and ground. 2. The establishment of macro or microgreen infrastructures, both inside and outside the cities and villages, have an extensive geographic dispersion. 3. Green infrastructures are multi-functional. 4. Green infrastructures develop in natural (animate or inanimate), artificial, and human backgrounds. 5. Green infrastructures create values through economic, social, and physical benefits. 6. Green infrastructures provide ecosystem services. 7. Green infrastructures will ultimately lead to sustainable management of resources.The green infrastructure network is available in the cities located on the fringe of Dasht-e Kavir in Iran as a multi-functional value-creating system for providing ecosystem services and with the aim of sustainable management of resources. In operational terms, from the qanats, gardens, and floodways to urban and architectural spaces all form a multi-functional network of natural components such as gardens and artificial components such as qanats in linear form (corridors), spots, and arena such as the flexible seasonal green network between upstream and downstream hamlets for the two-way connection of water and ground in hot and arid climate. Conclusion: Green infrastructure not only refers to urban organs which are a part of a natural and human-made ecological network but also applies to a scientific approach and method of environmental design and planning in which the best type of connection between water and urban form is available for supporting both natural and artificial processes in the management of water resources in the historical cities located on the fringe of the Dasht-e Kavir in Iran. Even in such hot and arid regions, green infrastructures are available as a multi-functional value-creating system for providing ecosystem services with the aim of sustainable management of resources. This network includes a wide range of natural and human-made water-based elements such as qanats, gardens, floodways, and urban spaces and architecture.
Original Article
Hossein Azhdari Bajestani; Saeed Alimohammadi
Abstract
Introduction: Dense Nonaqueous Phase Liquids (DNAPL) are the most common types of groundwater pollution. Surfectant Enhanced Aquifer Remediation (SEAR) is one of the most common methods of DNAPL-contaminated aquifer remediation. Due to the high cost of the chemicals used in this method (surfectants or ...
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Introduction: Dense Nonaqueous Phase Liquids (DNAPL) are the most common types of groundwater pollution. Surfectant Enhanced Aquifer Remediation (SEAR) is one of the most common methods of DNAPL-contaminated aquifer remediation. Due to the high cost of the chemicals used in this method (surfectants or cosolvents), it is necessary to choose the appropriate wells pattern, and the optimal pumping rates. UTCHEM simulation software has the ability to model the fate and transport of DNAPL and the application of the SEAR method. The main problem with this software is the long time required to run multiple senarioes when using optimization algorithms. The purpose of this study is to use two machine learning methods (Artificial Neural Network and K nearest neighbor) as sorrugate simulation model and imbedding the best one into the LINGO software to optimize the SEAR method. Material and methods: in the implementation of The SEAR method, the quantitative and qualitative aquifer data are required to model how to diffuse, transmit and delete DNAPLs in UTCHEM software. For this purpose information from the Camp Lejeune site in North Carolina, USA were used. In this study, by examining a variety of alternative models based on machine learning methods and implementing 250 different scenarios in UTCHEM software, two models, Artificial Neural Network (ANN) method, and k-nearest neighbors (KNN) were used to simulate the SEAR method and developing alternative model. In order to validate the two alternative models, 50 new scenarios were implemented in UTCHEM software and their percentage of removal was obtained. Also, using two alternative models, the percentage of removal of 50 scenarios were determined. in order to evaluate the performance of alternative models , the root mean square error (RMSE) was used and was compared with the results of other researchs. Finally an alternative model with more accuracy was used in LINGO software to optimize the Surfactant Enhanced Aquifer Remediation method (SEAR).Results and discussion: RMSE values in the results obtained from alternative models ANN and KNN in the validation stage were 0.67 and 1.66 respectively, which indicates the high accuracy of both alternative models, especially ANN. The average run time of each UTCHEM software in this study was 45 minutes, while in the alternative model it was reduced to a few seconds; LINGO software also examined about 21,500 different scenarios in 30 minutes to determine the optimal scenario, while the time required for this task is more than 16,000 hours if the alternative model is not used. Based on the position and discharge of active wells in the optimum scenario, it was found that firstly the existing wells upstream and downstream of the Pollution have the most impact on the remediation and secondly, the time factor is more effective than the wells pumping discharge in the remediation. The optimized scenario obtained in this study remediates the DNAPL-contaminated area by up to 95% at a lower cost than the costs reported in the Camp Lejeune project over a period of 30 days.Conclusion: Based on the results obtained in this study, it was found that the use of machine learning algorithms such as ANN and KNN, along with LINGO optimization software, which is one of the most powerful software for solving linear and nonlinear optimization problems, in addition to having the right accuracy, significantly reduces the time required to find the optimal scenario.
Original Article
Zahra Sadrazamnouri; Jafar Nouri; Farah Habib; Mojtaba Rafieian
Abstract
Background and Objectives: Urban river valleys are natural corridors and aquatic habitats which provide an enlivening landscape for the cities and also they play an important role towards environmental, social, and cultural issues for urban residents and development in urban resident's life and development ...
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Background and Objectives: Urban river valleys are natural corridors and aquatic habitats which provide an enlivening landscape for the cities and also they play an important role towards environmental, social, and cultural issues for urban residents and development in urban resident's life and development in their area. At the present time, structure and function of these valuable elements have been ruined due to non-planning growth and regardless to environmental subjects in municipal management and landscape planning that they have been converted to the runoff canal network or effluent. Several projects including restoration and rehabilitation of urban rivers have been defined to enhance environment of the city in Tehran. One of the weaknesses of urban management is distinguished just one dimension view towards development and even restoration. There are some solutions that can almost provide an ecologically sustainable condition for the river although the ability to return to the original state has been deprived. Implementation of engineering and managerial methods in compound and consideration of various dimensions of management are the main targets of this study, so land-use planning for the area around the river is applying as a suitable tool to restore and return it from a flooding area to a precious natural resource and servicing system. Of course, the objectives will obviously be reached if the key elements comprising ecology, economic, socio-culture, land-use, and executive and their subset indices have been considered in an integrating manner. In order to apply compound methods and presenting subjective results, Farahzad River Valley was selected as a case study. Methodology: Geographic Information System (GIS) and Urban River Survey (URS) were used to illustrate and classify sustainable ecological indices, respectively. At first, river area divided to 8 stretch in 50 meters then initial environmental indices including materials, habitat features, and flora were combined together and the features of each stretch were identified. Using cluster analysis, the values of initial indices were classified and entered in SPSS software. Therefore, the stretches were ranked from very good to poor in the various classes. Results and discussion: In overall, Farahzad River area were zoned in 4 qualitative classes, very good, good, moderate, and under moderate for landscape design. In the northern section of Farahzad River which is in the Kan Basin, about 32 percent of Farahzad River was situated in the very good class in terms of environmental indices. The very good class area was located in the mountain region. Because of the green spaces and gardens, approximately 11 percent was distinguished in good class. Both very good and good areas showed the potential for restoration and management of the river in these sectors. Nearly 12 percent of river stretch was classified in moderate level and other parts belong to moderate level. In the southern section of Farahzad River area which is located in the central catchment, the whole area was assessed in the under moderate level. That means probably it is possible for to define suitable land-uses gradually and design future landscape, with low changes. Conclusion: Ultimately, sustainable recreation with river rehabilitation approach was distinguished as the best land-use of Farahzad River Valley Stretch that can considerably be implemented in the northern parts of the river and green space areas. Then, a thorough planning based on the holistic and integrated approach is required an account of river protection and rehabilitation if it is possible for the downstream parts, after Western Flood Control Canal where is under pressure by urban development.
Original Article
Zhaleh Amini; Reza Anvaripour; masoud Hatami-manesh; Jaber Aazami
Abstract
Introduction; Due to the potential toxicity and ecological risk of heavy metals in aquatic ecosystems, measuring and evaluating their concentration in different parts of aquatic environments is very necessary. Therefore, the present study measures the concentrations of Cd, Cr, Pb, Ni, As and Zn and evaluates ...
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Introduction; Due to the potential toxicity and ecological risk of heavy metals in aquatic ecosystems, measuring and evaluating their concentration in different parts of aquatic environments is very necessary. Therefore, the present study measures the concentrations of Cd, Cr, Pb, Ni, As and Zn and evaluates the spatial distribution of their ecological risk in the surface sediments of Anzali International Wetland.Materials and methods; 50 stations in different parts of the wetland were selected for sampling. After preparation and acid digestion of samples, the concentrations of these metals were determined by an atomic absorption spectrometer. In order to zoning the toxicity and ecological risk of metals, the inverse distance weighting (IDW) method was used.Results and discussion; The total mean concentrations of metals were Zn (79.24 71 6.71), Cr (19.4 21 21.04), Ni (18.96 62 5.62), Pb (13.3 72 72.50), As (7.62 96 4.96) and Cd (1.12 ± 3.16) mg/kg, respectively. Investigation of potential acute toxicity, RI, mHQ and PLI indicated low pollution status in wetland sediments. The environmental risk of the metals in the sediments were evaluated as (Cd> As> Pb> Ni> Zn> Cr). In addition, the distribution of toxicity and ecological risk of metals in different parts of the wetland does not follow the same pattern and the western parts of the wetland have more risks. Conclusion; According to the results, Potential acute toxicity, PLI, mHQ and ecological risk of heavy metals in the sediments of the region are assessed as low and medium. The intense expansion of human activities in the areas around the wetland, along with the deposition and entry of various pollutants in this ecosystem, confirms the need for continuous monitoring of the wetland and assessment of its ecological health risk.
Original Article
Maryam Rabiee Abyaneh; Gholamreza Nabi Bidhendi; Ali Daryabeigi Zand
Abstract
Introduction: Landfill leachate is a highly toxic and hazardous form of wastewater due to its complex composition characteristics. Effective removal of heavy metals from landfill leachate is of great concern due to the fact that toxic metals can seriously threaten the food chain, and therefore the human ...
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Introduction: Landfill leachate is a highly toxic and hazardous form of wastewater due to its complex composition characteristics. Effective removal of heavy metals from landfill leachate is of great concern due to the fact that toxic metals can seriously threaten the food chain, and therefore the human health. The main objective of this work was to study the utilizing of low-cost pruning residues in the production of biochar and its application in removal of lead (Pb) from landfill leachate.Material and methods: Leachate produced in Babol municipal solid waste landfill was used as an adsorbent solution. Pruning residues were collected and used for biochar preparation. Biochar produced under the pyrolytic temperature of 700°C with a 1-hour retention time. The adsorption mechanism of pruning waste biochar to Pb was analyzed through BET surface area and scanning electron microscope (SEM) tests. Batch experiments were performed to study the effects of adsorption parameters on Pb removal. The influence of contact time (30-300 min), adsorbent dosage (1-50 g/L), as well as particle size (1-2 mm and 63-75 µm) was investigated. Moreover, the kinetic and isotherm models were applied to the experimental data to predict the adsorption parameters.Results and discussion: The results obtained from the analysis of the untreated Babol landfill leachate was revealed that the Pb concentration was about 4.94 mg L-1. The surface area of the produced biochar was determined to be 292.44 m2 g-1. SEM microstructure of the biochar showed the developed surface area with visible pores. All of these data seem to suggest a great potential for pruning residues biochar to Pb removal. The adsorption of Pb was mainly affected by contact time, adsorbent dose, and biochar particle size. Higher contact time and adsorbent dosage showed higher uptake of Pb. Whereas, the uptake of Pb ions onto pruning residues biochar was substantially reduced with increase the biochar particle size. Maximum Pb percentage removal was observed at a contact time of 90 min and with an optimum biochar dosage of 20 g L-1 (89.06% removal) for biochar with 1-2 mm particle size. While, biochar with particle size of 64-75 µm can removed Pb to almost 100% at a contact time of 120 min and with an optimum biochar dosage of 20 g L-1. The kinetic study showed that adsorption can be well described by the pseudo-second order kinetic model. This supports the chemisorption theory behind the pseudo-second order kinetic model for the adsorption system. The results of isotherm models implied that the behaviors of the isotherms are more appropriate for the Langmuir model, showing a monolayer adsorption capacity for Pb.Conclusion: Findings of this research demonstrated the applicability of pruning residues biochar as an economic adsorbent for the removal of the Pb from landfill leachate. On the other hand, the crop residue burning poses a threat to the environment and human health due to the emission of toxic gasses and particulate matter. So, conversion of pruning residues to biochar and its application to heavy metal removal is a useful and environment-friendly alternative to crop residue and biomass burning.
Original Article
Shahla Lajmorak Rameh chari; Abdol Majid Mahdavi Damghani; Hooman Liaghati
Abstract
IntroductionWheat is one of the most important crops used in the country and forms the basis of food security of Iranians. Wheat cultivation in Iran has a long history over 8,000 years. On the other hand, with the growth of the population of countries, the issue of food security has become more important ...
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IntroductionWheat is one of the most important crops used in the country and forms the basis of food security of Iranians. Wheat cultivation in Iran has a long history over 8,000 years. On the other hand, with the growth of the population of countries, the issue of food security has become more important every day to the extent that it has become one of the most important issues of the country and efforts are being made to achieve self-sufficiency in the production of this strategic crop. The area under cultivation has always been one of the most important factors limiting production in the world, and today in all countries, officials and researchers have paid attention to this issue in order to increase production without relying on increasing the area under cultivation. The history of compression of cultivation and the consequences of green agriculture in the form of conventional agriculture show that the way to supply crop production is not through this, inevitably the importance of studying the agricultural history of each country becomes more important every day which by analyzing events find the reason for the success or failure of programs over time.Materials and MethodsTherefore, a study has been conducted in the form of a time series analysis study and quantitative content study to analysis and examine changes in area under cultivation, wheat production and population changes in a period of 60 years. To do this, the Mini-tab software has been used.Results and DiscussionThe results of the study show the linear population growth from 1961 to 2020. During the same period, the country's total wheat production has increased from 3.5 million tons per hectare to 11.7 million tons per hectare, which shows a growth of 234 percent in this sector. The area under wheat cultivation in these years has had less changes compared to the amount of production and population growth and has increased from 4.5 million hectares in 1961 to 6.4 million hectares in 2020.ConclusionIt seems that the events of 1961 to 1971 in the social structure and industrialization of the country, changes between the two revolutions in 1971 to 1981, the occurrence of imposed war in 1981 to 1991 are all of special importance in changing the agriculture of Iran. This phenomenon is called social metabolism, which reflects the effects that the natural environment (agroecosystem) receives from its social environment, and in contrast to the effects that changes in the structure and function of agroecosystems on the availability of food in society.
Original Article
Farid Salmanpour; Faraham Ahmadzadeh; Romina Sayyahnia; Bahram Hasanzade Kiabi
Abstract
Introduction: Climate change along with human development created additional pressure on ecosystems, so in many cases it has caused a decrease in biodiversity. Global climate change continues as a global crisis. Climate change does not affect all habitats and species equally. Rather, large species are ...
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Introduction: Climate change along with human development created additional pressure on ecosystems, so in many cases it has caused a decrease in biodiversity. Global climate change continues as a global crisis. Climate change does not affect all habitats and species equally. Rather, large species are more affected by climate change and habitat change and are more vulnerable than other species. Also, studies show that the countries of the Middle East have been severely affected by the effects of climate change. Large herbivores, especially red deer (Cervus elaphus), are not only affected by habitat changes resulting from climate change, but also the increase in temperature has reduced the survival rate of calves and impaired reproduction. The Caspian red deer in Iran has lost a lot of its population under the influence of habitat destruction and illegal hunting, and today the remaining population tolerate additional pressure from climate change. Central Alborz Protected Area is considered as a main breeding habitat of Caspian red deer, which is affected by human development and climate change today.Material and methods: In this study, in order to investigate the impact of climate change on the red deer population, temperature and precipitation data of two meteorological stations, Nowshahr in the lower elevations, and Baladeh in the southern elevations, were used. Also, presence and non-presence points of the species were collected random transects direct observation, as well as pictures of camera traps.Results and discussion: Using 19 climate parameters to evaluate habitat suitability in the future, it revealed that continuation of the climate change process in four optimistic to pessimistic scenarios using five MaxEnt, RF, ANN, GLM, MARS algorithms, the suitability of low altitude areas in the sectors of north and east will be reduced, and will be increased towards to highlands in southwest. The results showed that the parameters of average annual temperature, average daily temperature, average temperature of the dry season, average temperature of the hottest season, annual rainfall, rainfall in the wettest season, and rainfall in the hottest season have an effective role in determination of the habitat suitability of the species. The results of the climate data showed that the altitude plays an effective role in reducing the effects of climate change, so that the climate change in the downstream areas has a significant intensity compared to the high areas. According to the change of habitat suitability resulting from the continuation of the climate change, Kojoor forest zone shows the relative stability of desirability for the studied species in the present and future, but the Kheyrud forest road with a total length of more than 50 km is located in the depth of this area, where the traffic of vehicles of herders, ecotourists and especially illegal hunters have facilitated access to this habitat, which is the most main threat to survival of red deer in this habitat.Conclusion: With the continuation of climate change and its effects on the habitat in the future, it is expected that female deers will be observed in unsafe parts of the habitat. Therefore, for conservation of the Caspian red deer population in the central Alborz Protected Area, robust management measures are needed based on created habitat changes in the future.
Original Article
Mohammad Hossein Jahangir; Seyed Mohammad Ehsan Azimi
Abstract
Introduction: Long and short term weather forecasting have been as two of the most important challenges to water and climate researchers. In order to overcome this challenge, several tools, including atmospheric-ocean general circulation model forecasting scenarios, and downscaling models have been developed ...
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Introduction: Long and short term weather forecasting have been as two of the most important challenges to water and climate researchers. In order to overcome this challenge, several tools, including atmospheric-ocean general circulation model forecasting scenarios, and downscaling models have been developed and used. These tools downscale forecasting scenarios by creating relationship between parameters of synoptic stations and Large-scale data of general circulation models.Material and methods: In this study large-scale predictor parameters from 1961 to 2003 from the database of National Centers for Environmental Prediction (NCEP), large-scale data for the A1B and A2 forecast scenarios of the HadCM3 model from 2001 to 2100 from the Canadian Centre for Climate Modelling and Analysis (CCCMA), and the meteorological synoptic data of Ardabil stations from the Meteorological Organization were gathered. To this end, three downscaling models such as Statistical Downscaling Model (SDSM), least squares support vector machine (LS-SVM) and multi-layer perceptron (MLP) were determined for downscaling; and correlation coefficient (CC), Mean Squared Error (MSE), Root Mean Square Error (RMSE), Normalized mean square error (NMSE), Nash-Sutcliffe, Mean Absolute Error (MAE), and Taylor diagram were used to evaluate the efficiency of the models.Results and discussion: The results showed that the MLP obtained the best results based on the average of the stations with the values of (CC=0.85), (NMSE=0.63), (NSH=0.73) and (MAE=0.52), and LS-SVM and SDSM are ranked second and third, respectively. Taylor's diagram also identified the SDSM as the weakest and the LS-SVM and MLP as superior models with a slight difference. Based on downscaling results of all forecasting scenarios, an increase in average daily temperature is also predicted by 2100 in all studied stations.Conclusion: Based on the results of the study, all forecasting scenarios and all methods of downscaling show increasing the daily average temperature by 2100. Hence, it is necessary to be taken this issue account for making environmental and developing policies in this area.
Original Article
Hossein Vahidi; Majid Ramezani Mehrian; Hossein Khosravi; Azadeh Ali Hosseini; Amin Jalayer
Abstract
Introduction: The development of the necessary infrastructure to enhance the walkability in urban areas has an important role in sustainable urban development and from various aspects of the environment, public health and social justice can improve the quality of life. This study aimed to investigate ...
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Introduction: The development of the necessary infrastructure to enhance the walkability in urban areas has an important role in sustainable urban development and from various aspects of the environment, public health and social justice can improve the quality of life. This study aimed to investigate the pedestrian capability approach for the development of a sustainable city in District 16 of Tehran Municipality as one of the greenest urban areas in Tehran.Material and methods: In this research, the criteria, qualities, characteristics and physical, functional and spatial variables of the man-made environment that affect the amount of walking in the D16 of Tehran Municipality have been studied and collected. Then, using GIS spatial analysis and prioritization of indicators using Analytical Hierarchical Process, the pedestrianization of different parts of the region has been investigated.Results and discussion: Criteria affecting the location of sidewalks and greenways in the D16 in 9 main categories and 30 sub-criteria were collected in a hierarchical structure and their spatial information was collected. The diversity and wide range of indicators evaluated results in a comprehensive analysis of the current situation can be considered as one of the strengths of this study. Each of these indicators was analyzed for the study area and the situation of walking potential in the D16 was studied based on each of the indicators. Using the preference of criteria based on the opinion of experts and the overlap of different layers, finally, the map of the degree of walkability and the map of the degree of the walkability of the road network in the 16th district of Tehran Municipality was obtained. According to the results, the spatial value shows the highest values in Khazaneh, Naziabad and Bagh Azari neighborhoods, respectively. In addition, Bukharai Street, Madaen Street, Rajaei Street and Street next to Besat Park are the axes with the highest amount of pedestrian traffic in the region, respectively.Conclusion: Based on detailed traffic studies, the best places to define sidewalks or urban greenways were identified, and since these axes have a high volume of pedestrian traffic, it is very important to pay attention to the needs of pedestrians in them. The three neighborhoods of Naziabad, Aliabad North and Khazaneh were identified as three suitable areas for the development of pedestrian axes in the region and were introduced to further concentrate the municipality of the region.
Original Article
Mahsa Tamjidi; Yousef Rashidi; Majid Abbaspour Tehrani; Seyed Alireza Mirzahoseini
Abstract
Introduction: Dust is one of the most important atmospheric phenomena It happens in spring and summer in many regions, including Iran and neighboring countries And it is one of the important challenges of the 21st century And this phenomenon in the global scale of arid and semi-arid regions and due to ...
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Introduction: Dust is one of the most important atmospheric phenomena It happens in spring and summer in many regions, including Iran and neighboring countries And it is one of the important challenges of the 21st century And this phenomenon in the global scale of arid and semi-arid regions and due to climate change, vegetation change, progressive processes of soil erosion and disturbances resulting from them, the sensitivity of the regions to rapid erosion which will have important reactions on the climate of the region and desertification. The purpose of this research is to determine the intensity of the pollution production rate of suspended particles less than 10 microns using modeling and comparing the output results with the measured data. and changing the intensity of the pollution production rate based on the measured data and calculating the formula for determining the PM10 emission rate It is caused by the dust incident in Ahvaz city.Material and methods: Ahvaz metropolis considering the complex topography In a dry area and in the vicinity of the main and primary sources of dust, it has special conditions In this study, the concentration of suspended particles less than 10 microns was investigated on the 15th of June 2019. On this date, the maximum PM10 concentration in Ahvaz city was 1422 micrograms per cubic meter on June 15. that the concentration of these particles was more than 9 times the standard concentration of free air of the Environmental Protection Organization of Iran (150 micrograms per cubic meter). From the concentration data of the environmental protection organization measurement station and surface meteorological and upper atmosphere data of Ahvaz station have been used to implement CALPUFF model and concentration outputsResults and discussion: By studying library documents, the basic calculation formula for determining the emission rate of PM10 pollutant has been estimated, and then it has been compared with the data of the monitoring stations located in the city of Ahvaz, and by modifying the calculation formula and implementing the CALPUFF diffusion and dispersion model, it has been calculated according to the actual concentration recorded by the online station. The monitoring of the Environmental Protection Organization was reached and finally the emission rate of suspended particles less than 10 microns from the centers around the city of Ahvaz was determined.Conclusion: The emission rate of PM10 pollutant has been obtained using the calculation formula and the implementation of the CALPUFF diffusion and dispersion model, which is important in the prediction of the dust phenomenon and provides the possibility of calculating the amount of production and the movement path of the particles. He thought about taking the necessary decisions to reduce the possible damages caused by this phenomenon. And using the combination of measurement and modeling, he achieved a methodology to calculate PM10 dust emissions from city centers.
