نشریه علوم محیطی
سال نوزدهم شماره 4 (پیاپی 74، زمستان 1400)

Cotton is one of the most important fiber plants in Iran which needs more production for national fiber sufficiency goal. Its cropping area in Iran is now about 140,000 ha in which 95.3% is irrigated; rainfed cotton is growing only in Khorasan, Golestan and Mazandaran. Planting date and nutrition management and their interactions are amongst the most important determinants of crop yield. 

Field experiment in 2016 in the fields of Cotton Research Center of Golestan province in Hashem Abad split plot factorial in a randomized complete block design was conducted. Treatments include the planting date as the main factor, cultivar (Latif and Golestan) and nitrogen (three levels: desirable, a third desirable and without fertilizer) as sub plots. The first planting date in the traits (TDM, LAI, CGR and RGR) was superior to the second planting date. Among the cultivars, Golestan cultivar showed a better response to Latif cultivar at zero fertilizer level and 160 kg ha-1 nitrogen fertilizer. 

TDM variation and LAI of cotton cultivars during the growing season were three stages. The first stage, the phase of presentation, in which the TDM variations continued up to 55 and 61 days after planting and the rate of changes in the LAI, respectively, was 55 and 43 days after planting in the first and second planting dates. TDM accumulation changes up to 109 and 96 days, the LAI was about 88 and 96 days, the RGR was 55 and 61 days, and the CGR was 88 and 96 days after planting in the first and second plantings increased linearly. Maximum RGR and CGR were observed at cultivar Golestan cultivar at zero and 160 kg ha-1 in first planting date.

In general, first planting date (29 June) in comparison with the second planting date (12 July) caused higher DM production, LAI, RGR and vegetative growth and Golestan cultivar had better performance than Latif cultivar at 0 and 160 khNha-1. The maximum RGR at these two fertilizer level in Golestan cultivar was recorded at the first planting date which caused a significant difference for the time reaching maximum LAI.

The sustainability of agricultural systems plays a key role in adapting to climate change. There is ample evidence that biodiversity can increase the stability of ecosystem processes by changing environmental conditions. Therefore, the effectiveness of breeding programs requires a correct understanding of the reaction of breeding cultivars to environments with different climatic and soil conditions. Therefore, this study was conducted to assess the response of some new maize hybrids to divergent environmental conditions and determine their grain yield stability.

This study was conducted with 16 maize hybrids using a randomized complete block design with three replications in six locations, during the 2017 cropping season. Considering significant differences for hybrid × environment (GxE) interaction, stability analyses were performed using AMMI and GGE-biplot methods to determine stable and high-yielding hybrids.

The results of the AMMI model showed that only the first two principal components of AMMI (AMMI1and AMMI2) were significant and described 68.53% of the variance of G×E interaction. Based on the results of statistics of the AMMI model (ASV and SPCA1), hybrids No. 16 (SC704) and 1 (KLM77002/3-1-1-1-1-1-1-3 × K18) were recognized as the most stable hybrids. Stability analysis by GGE biplot procedure explained 71.5% of grain yield variation due to two components of GGE. In addition, hybrids No. 16 and 1 were identified as superior and stable hybrids by the GGE biplot graphical method.

Generally, results of grain yield and stability analyses showed that hybrids No. 16 and 1 with 12.76 and 11.72 t/ha yields, respectively, were better than other hybrids across environments for yield and stability with wide adaptation and thus can be cultivated in Iran. Also, biplot analysis of correlation among environments revealed that Kermanshah, Esfahan, and Shiraz, as well as and Moghan and Miyandoab were closer and similar in ranking, grouping, and assessing stability. Also, Kerman and Karaj regions were less similar to other regions in terms of hybrids discrimination. Considering the high discriminate power of hybrids in Shiraz, Miyandoab, Kerman, and Karaj environments, and in order to decrease the costs, it is recommended to conduct future trials in the aforementioned environments.

While more than 2 million tonnes of nitrogen (N) fertilizers are annually used in Iran, it is documented that only 20% of applied nitrogen N are uptaken in some wheat farms of Iran. In other words, around 80% of N fertilizers are lost through leaching and volatilization, which increases the potential of environmental contamination with the increased N input expenditure of the farmer, or stored in the soil. So, the present study was aimed to quantify the role of ammonia volatilization from Iranian soils and to introduce simple and helpful techniques for ammonia volatilization reduction in Iranian wheat farms.

Firstly, a modified closed dynamic airflow system was provided. Soil materials were provided from the Tea Research Institute located in Lahijan, Iran as well as the National Salinity Research station located in Ashkezar, Yazd, Iran. The soils with three levels of acidity (7.88, 6.5, and 7.88) were incubated with five sources of nitrogenous fertilizers including ammonium sulfate, ammonium nitrate, urea, sulfur coated urea, and potassium nitrate for 22 days. Daily and cumulative volatilized ammonium was collected in 20 ml of 2% boric acid indicator solution and it was titrated with 0.01 N HCl. The analysis of variance for different parameters was done following the ANOVA technique. When F was significant at p ≤ 0.05 level, treatment means were separated using DMRT.

Results showed that soil acidity, fertilizer source, and their interactions had significant effects on total volatilized nitrogen, maximum volatilized rate, and day of highest volatilization rate. Total volatilized nitrogen depends on nitrogen fertilizer source and soil acidity. The results showed that more than 59% of applied ammonium sulfate at the soil with the pH value of 7.88 was lost through ammonia volatilization and resulted in air pollution. The volatilized nitrogen for sulfur-coated urea and potassium nitrate equaled 7.6 and 0.018% while that of ammonium nitrate and urea equaled 49%. The results showed that potassium nitrate had the minimum cumulative ammonium volatilization of less than 0.07 mg N and it was not affected by soil acidity. In addition, our results proved that soil pH reduction from 7.88 to 6.5, reduced total ammonia volatilization for ammonium sulfate and nitrate from 227.15 and 189.82 to 2.39 and 0.99 mg N, respectively. Total volatilized nitrogen from ammonium sulfate and nitrate from soils with pH of 4.5 were 2.51 and 1.33 mg N, respectively. While soil pH reduction from7.88 to 4.5 from soils treated with urea reduced ammonia volatilization from 188 to 157, this increased ammonia volatilization from sulfur coated urea from 29.2 to 87.05 mg N. In other words, our results proved that increasing soil pH resulted in a significant decrease in total volatilized ammonia from sulfur coated urea. The total volatilized nitrogen from soils with the pH values of 4.5, 6.55, and 7.88 was equal to 22, 20 and 6% of applied sulfur coated urea. The maximum volatilized rate of ammonium was affected by soil pH and fertilizer sources. With decreasing soil pH the maximum volatilization rate from urea fertilizer increased. A similar trend was found for sulfur-coated urea. However, the maximum volatilization rate from ammonium nitrate and sulfate increased with soil pH increase. Interestingly, soil pH had no significant effect on the maximum volatilized rate from potassium nitrate fertilizer and it was equal to 0.04 mg N per day.

As ammonia volatilization depends on N sources, it is possible to decrease ammonia loss by selecting the proper nitrogen fertilizer source. The results demonstrated that potassium nitrate had minimum ammonia loss and can be introduced as the optimum source of nitrogen fertilizer for a wide range of soil pH from 4.5 to 7.88. Ammonium nitrate and ammonium sulfate fertilizers had the least ammonia loss at soils with a pH of 6.55 and less. However, sulfur-coated urea had the least ammonia loss at soil pH of 7.88 and more.

Free plastic bags have practical benefits for consumers but because of their non-biodegradability and additives, they have adverse effects on the environment. Therefore, in this study, the factors affecting people's intention and behavior for using plastic bags with the Theory of Planned Behavior and Structural Equation Modeling were investigated.

A total of 360 customers in 7 major hypermarkets in different areas of Mashhad responded the questionnaire. Data were analyzed using IBM SPSS Statistic 22 and AMOS 24 software. An extended model based on the Theory of Planned Behavior was introduced with the constructs including cognitive attitude, affective attitude, economic motivation, feedback, subjective norm, behavioral control, intention and behavior to determine the factors influencing the behavior.

The results of this study showed that more than half of the respondents to the questionnaires were women and more than 30% of them were in the age group of 25-35 years. The effect of demographic information on the intention to reduce plastic bags in hypermarkets was examined by the Anova test.  Only the age (p 0.05) effect (coefficient of 0.16) on intention to reduce plastic bag. The norm with a coefficient of 0.41 has a positive and significant effect (p <0.001) on the intention.

The results showed that the structural equation model with appropriate fit could describe the relationships between variables. The main parameters of the Theory of Planned Behavior (attitude, subjective norms, and behavioral control) significantly describe the intention of using plastic bags. Adding new variables such as feedback and economic incentives to this theory will help determine other predictors of behavior. The norm is one of the most important variables that mediate the influence of other factors such as cognitive attitude, affective attitude, economic motivation, feedback, and behavioral control on intention to using plastic bag. Although the economic incentive has an effect on intention to use free plastic bags, it is appropriate to use the intervention approach based on the model presented in this study to find a solution.

Today, with the development of water treatment plants, sludge management has become one of the most important environmental issues that can be both a threat and an opportunity. Therefore, due to the increasing development of water treatment plants in the country and the production of a significant amount of sludge, it is necessary to take measures.

In this research, cationic polyelectrolyte and anionic polyelectrolyte of industrial grade from Basf company, Germany, polyaluminum chloride (AL2 (OH) n CL6) with industrial grade from Chinese company, ferric chloride (FeCl3) in industrial grade from Fanavaran Aria Mehvar company, ferric chloride (FeCl3) in industrial grade from Merc Germany, and aluminum sulfate (Al2(SO4)3) in industrial grade from Kimia Exir were purchased and used. The jar test was used to determine the appropriate type and amount of coagulants. In this experiment, sixglass containers and a stirrer were used to stir the contents of all the containers at the same time. One liter of the sample with pre-determined turbidity was added to each container. First, the mixer was set to a high speed of 200 rpm. Then for each coagulant, a certain range of it is added to the dishes at the same time and was mixed at 200 rpm for one minute. In the next step, the stirrer was placed on a slow speed of 20 rpm for 15 minutes, and finally the solutions were allowed to settle for 30 seconds and the turbidity of the top layer was measured. To compare sedimentation by coagulant and flocculant, 2% (w/v)of coagulant and flocculant were prepared and equal volume of each one was added to the sludge sample from Maragheh water treatment plant to improve the performance of materials in acidic and alkaline environments. . By creating acidic and equal alkaline environments for all samples, half-hour sedimentation was measured. To observe more sedimentation and compare the samples, 1, 2 and 3 hour sedimentation was also measured. In the last experiment, which was performed without coagulant and it was done just by raising the Tss and mixing with the sewage sludge, more settling time was given and a very good result was obtained. ​​Maragheh city is one of the environs of Tabriz. In this research, it was necessary to select an area which firstly had a water treatment plant and secondly had a wastewater treatment plant, which was possible in Maragheh city. Maragheh water treatment plant is located next to Sufi River dam and coagulant materials are used to treat drinking water in this city. The wastewater treatment plant of this city has two phases, which according to our need for the first settling sludge to increase the TSS, the first phase of this treatment plant was sampled and tested.

In this study, the methods of reducing sludge from water coagulation using various coagulants and flocculants and changing their ratio in acidic and alkaline environments were evaluated. Also, coagulation of sludge from water treatment plants by raising TSS was investigated using initial sewage sludge containing detachable municipal wastewater solids. We also tried to evaluate the volume of sludge produced, the amount of ion removal, and the amount of residual ions by selecting different coagulants and changing their ratios. Sampling was done periodically from Maragheh water treatment plant and Maragheh wastewater treatment plant. In the experiment related to the mixture of sludge from the water treatment plant and sludge from initial sedimentation of sanitary wastewater treatment plant, ideal results were obtained so that the coagulation volume reached more than 50% and with increasing retention time, this efficiency increased by more than 70%. For 5 hours, the amount of sediment was only 80 ml, and 420 units had been deposited. The gelatinous sludge in the water treatment sludge, which is due to aluminum hydroxides and compounds of other coagulants with sludge, makes further dehydration impossible, and despite the increase in coagulant and the use of other coagulants, no good dewatering was performed. In order to obtain better results experiments were performed in acidic and alkaline environments to examine the extent of sludge reduction. In practice, in these environments, good results were not obtained and setteling failed , such as in neutral medium experiments,

According to the results of the experiments, it can be concluded that without any cost of materials, by giving time for settling, mixing the two types of sludge and using a variety of sludge drying methods, dewatering of this jelly sludge is possible. If this is done, surface water pollution will be prevented and the problem of disposing of this sludge will be practically eliminated.

Desertification involves processes that are both the product of natural factors and the mismanagement of human beings. Adafic parameters and processes affecting soil condition, climate, groundwater, vegetation and management are the most important factors affecting the phenomenon of desertification in many arid and semi-arid regions. These parameters are investigated using different models in different regions.Therefore, this study was conducted to evaluate the desertification intensity based on groundwater and soil criteria in the west of Golestan province.

To determine the work unit map, topographic, geological, aerial photo interpretation, panchromatic band and multispectral Landsat satellite images and field visits were used. In this study, the Madalus method was used to prepare a map and evaluate the desertification situation. The geostatistical methods used in this research include kriging method, local estimator method (GPI), radial function method (RBF) and distance distance method (IDW). in Madalus model, 6 criteria and 20 indicators were used to evaluate the intensity of desertification. The scoring of each of the indicators was determined at the unit level in the region. The map of each criterion is also obtained through the geometric mean relationship between the indicators. To evaluate the accuracy of the model results, the desertification class in each of the work units according to the field evidence, observational and visual evaluation was performed and then the statistical comparison of the model desertification class with an expert opinion was performed. SPSS software and Mann-Whitney non-parametric test were used to validate the model results.

In this study, according to the histogram of the data, the normality of the parameters was investigated. The mean square squared error (RMSE) was used to determine the most appropriate interpolation method. The weighted average score of desertification intensity of area 135 was obtained, which indicates the middle class. In terms of zoning of desertification intensity, the region was classified into three classes: low and insignificant with a frequency of 27 and medium with a frequency of 60 and severe with a frequency of 13. Among the criteria of desertification, the criterion of management and policy with an average weight of 148 points is the dominant and effective criterion of desertification, followed by the criterion of vegetation (145), the criterion of soil (141), the criterion of erosion (138), the criterion of climate. (122) and groundwater criteria (121) were in the next rank of effective desertification criteria in the region. Also, the most important indicators of desertification are the indicators of drought resistance, conservation operations and soil salinity, respectively. These indicators have increased the trend of desertification in the work units of abandoned lands, saline and wetland lands and saline lands located in the northeastern parts of the region. Based on the spatial distribution of classes with low and insignificant desertification intensity in the southern and eastern part of the region, the middle class in the western, central and northern parts and finally the severe desertification class are located in the northeastern parts of the region.

According to the obtained results, which indicate high evapotranspiration of the region, expansion of land salinity, unprincipled road construction and incomplete drainage.it seems that the management of desertification in the west of Golestan province, as one of the agricultural hubs, should be in the managerial priority of the officials and experts of the executive departments.Accordingly, it is proposed in order to control the process of desertification and achieve sustainable development in the region.treatment of industrial and domestic effluents for reuse for various purposes, Use of modern irrigation systems for agricultural lands, Placing low-yield crops in terms of water consumption in the region's crop rotation and As well as the necessary training to justify farmers to use pesticides and chemical fertilizers in the area.

The stability and maturity indicators of composted biomasses are important to ensuring the quality of the final product, maintaining the consumer confidence, and guaranteeing the safe applicability in agricultural uses. In addition, due to the low energy density and bulk density, the composted biomasses face problems such as higher storage and transportation costs as well as overall costs in logistics management. Particle size reduction and densification of composted biomasses can partially overcome these challenges.

Sugarcane bagasse compost (SBC) was prepared from South bagasse processing development company (Biofer) to quality characterization and assessing the grinding process toward densification. For assessing the quality of SBCs, the physicochemical characterization as well as the analytical techniques were investigated through differential scanning calorimetry (DSC), X-ray diffraction (XRD), Fourier transform infrared (FT-IR) and scanning electron microscopy (SEM). In the following, a hammer-attrition mill was used to improving the physicomechanical properties and reducing the particle size of SBCs. To this end, an experimental design in the form of factorial design (D-optimal) was used to assessing the significance and optimization of the effects of moisture content of SCBs (8, 12, and 16 w.b.%) and screen opening size (1, 2.5, and 4 mm) and rotational speed (1400 and 2000 rpm) of hammer-attrition mill as independent variables on specific energy consumption and bulk density as design responses.

The results obtained from chemical analysis exhibited that the properties of SBCs are accordance with existing standards. The SEM micrographs revealed a physical change on the surfaces of SBCs with a wrinkly and heterogeneous morphology along with longitudinal cracks with opening of fiber bundles in cellulose resulting from the degradation of lignin and hemicellulose. This trend was also demonstrated by XRD analysis, so that with increasing the crystallinity index (from 62 up to 75), the crystalline regions of cellulose in SBCs remained unchanged, but the amorphous regions, which includes hemicellulose and lignin, was slightly decomposed. Changes in functional groups from FT-IR spectra demonstrated that the microbial-biological degradation of lipids and carbohydrates, as well as dissociation of lignin and polyphenols was occurred in SBCs. From the DSC thermal curves, a glass transition temperature of 89.7 °C was obtained for SBCs, which due to the peak intensity at this point, the improved maturation and humification of SBCs is guaranteed. For both responses of specific energy consumption and bulk density of SBCs, a two-factor interaction (2FI) model with the highest correlation coefficient and the lowest standard deviation was proposed. The mesh opening size had the greatest effect among the parameters on the specific energy consumption and the bulk density.

The results demonstrated that the use of comprehensive analytical analyses for accurate and comparative study between the final composted biomasses and the raw materials in terms of stability and maturity indicators, is practical and reliable. Optimization results from D-optimal design showed that under optimum conditions of moisture content of 8 %w.b, 1-mm mesh opening size and rotational speed 1400 rpm of hammer-attrition mill, a minimum amount of SEC (141.38 KJ/Kg) and the maximum amount of bulk density (209.62 kg/m3) were introduced as optimum responses with the desirability function of 0.88.

The amount of soil permeability depends on the size of the holes, the concentration of liquid, and the surface tensile force. In fact, the factors affecting the initial porosity are also effective in permeability.The results of different researches show that soil permeability has been prioritized in different researches. In Iran, various researches have been conducted on soil physical and chemical properties and its relationship with permeability. This study was conducted based on infiltration field measurements under simulated rainfall conditions in order to determine the penetration rate and interaction effect between slope aspect and intensity of precipitation relative to acidic precipitation on Aghajari and Gachsaran formations.

In this study, in order to determine the interaction effect between slope aspect and rainfall intensity in soil permeability compared to acidic precipitation in the deposits of Gachsaran and Aghajari formations due to the existence of petroleum pollutants and air pollution, a part of Gypsum and Margha watersheds of Izeh city with an area of 1202 and 1609 hectares was selected. Then, soil permeability was sampled at 16 points and with three replicates in rangeland land use and in the northern, southern, eastern, and western aspects of Gachsaran and Aghajari formations at different rainfall intensities of 1 and 1.25 mm/min and in distilled water precipitation, the acidity of 4 and 5 was performed using kamphorst rain simulator.

The results showed that in Aghajari formation, the interaction effect of slope aspect and rain intensity, as well as rainfall intensity had the highest sensitivity and slope aspect had the lowest sensitivity to soil permeability compared to acid rains. However, the Gachsaran Formation showed uniformity changes compared to acidic precipitation and showed positive effects on slope aspect and rain intensity and interaction effect of slope aspect and rain intensity almost all three concentrations. In addition, by increasing the amount of soil impregnated with acid rains, the amount of soil porosity will increase, which is due to this type of contamination on the main ingredients of soil and washing soil bonds. Of course, the slope aspect is also due to the different amount of clays in both Aghajari and Gachsaran formations due to erosion and different washing rates that are created from the beginning of the slope to its bottom especially in the Aghajari Formation and the influence of soil permeability on more acidic precipitations, as well as the existence of different organic matter in the main aspects of the slopes, especially in the northern and eastern slope aspects, creates a more complex situation in electrical charge changes, which necessitates further research to understand this complex mechanism.

In general, by increasing the acidic degree and increasing the penetration time, soil properties have been changed, including these changes can be noted the resistance characteristics and bearing capacity of the soil, which in the meantime, due to the amount of clay and different organic matter, causes more influence of acidic precipitation on soil permeability.

Land-use changes in developing countries have negative environmental and ecological consequences for the environment. Therefore, access to the updated information in land-use changes is necessary for the analysis of different needs of human settlements and adopting appropriate policies to ensure the future. Past studies and prediction of land-use in the future have a fundamental role in decision making and policymaking of land-use planners. The purpose of this study was to study land- use and its changes over the years 2001 - 2013 and to identify the land-use changes in Hamedan city and to simulate and future land- use and its changes by Ca - Markov model in 2010.Ingredients: After obtaining satellite images of TM, ETM, and OLI, preprocessing steps including radiometric and geometric corrections were performed on images. Then, using the support vector machine (SVM) algorithm. We used a support vector machine (SVM) to classify satellite images and divide the land- uses into four classes of residential and non - residential, barren lands and poor rangeland, garden lands, and irrigated farming, mountainous, and grassland. After land-use change detection and changes to predict the trend of these changes by the Markov chain model due to the high capability in detecting spatial - spatial component changes, for 2010.

The results of the present study indicate that over time, the growth and development of urbanization in this metropolis cause to expand the physical texture of the city in this region. Therefore, at the beginning of the study, the residential and non - residential land use area in this metropolis, if at the end of the period, the total area of the region has arrived. The study of land-use changes showed that from 1390 to 1392, residential and non - residential land uses were added to residential and non - residential land uses and the increase of the next land-use area was related to arid lands and pastures. Land- use and irrigated farming, along with mountain use, were among the number of land uses that had been decreased in 2010 compared to the previous year. This trend continues with time in a way that the area of residential and non - residential construction and bare lands continues to increase its area in 1390 and is added to the area of land uses. Finally, over the past year, it can be said that over the past year, the land- use of residential and non - residential areas and land use has decreased. This conversion has negative consequences in the future of the region to reduce the negative consequences of these changes in the future.

In this study, the automated cell model and Markov chain have a high ability to predict land-use changes in the future. It is also necessary to increase the land-use area for residential and non - residential and bare land uses and other uses such as garden lands, irrigated farming, mountain, and grassland are decreasing areas in the region. Therefore, planners should always consider this growth and expansion in the future to better plan their programs.

  This study investigated the effects of Yazd-Eghlid railway construction on some vegetation and soil characteristics of artemisia and camel grass species located in Kalmand-Bahadoran protected area.

In order to evaluate the vegetation and soil variables in the studied types, random-systematic sampling method was used. Finally, the data obtained from vegetation measurements and soil experiments were analyzed using analysis of variance and Duncan test using SPSS software.

The results of this study showed that the construction of a railway in the Kalmand-Bahadoran protected area and the measures taken during the construction process can have effects on the physical and chemical properties of soil and vegetation, which in the Artemisia type causes There was a significant decrease in the production of plant vegetative form srub (0.81 g) (P <0.05).

The construction of the railway and due to the activities that take place during the processes for the construction of the railway line units can cause the movement of soil around the railway, and this action provides the introduction of soil and water erosion in the region, which causes poor and decrease of soil quality around the areas near the railway and consequently the decrease of vegetation production in some areas.

Urban growth has accelerated in recent decades, therefore, predicting the future growth pattern of the city is very important to prevent some environmental, economic and social problems. The city of Tabriz has also experienced rapid growth of urban lands due to significant demographic changes, which requires accurate simulation of urban growth to prevent negative environmental and economic consequences. The purpose of this study is to evaluate the performance accuracy of the proposed machine learning algorithms by spatial cross-validation method in combination with the cellular automata model to simulate urban growth.

In this study, to analyze urban land use changes, Landsat satellite images related to the years 1997, 2006 and 2015 were classified using the support vector machine algorithm. In the next step, change potential maps of non-urban to urban areas using random forest algorithms, support vector machine and multilayer perceptron neural network for two periods of calibration (1997 and 2006) and validation (2006 and 2015) based on distance from the main roads, distance from the city center, distance from built-up areas, distance from the rivers and railways, as well as slope, elevation and two-class (agricultural / barren) land use layer were produced as effective factors in the growth of the city. Finally, using the cellular automata model, the growth simulation of Tabriz city based on land use and change potential maps obtained from machine learning algorithms for the mentioned periods was performed. To prevent over-fitting of algorithms to training samples and to obtain optimistic results, in the process of extracting optimal parameters of machine learning algorithms, the spatial cross-validation method was used to reduce spatial correlation between training and test data.

The results showed that the random forest algorithm with the area under the ROC curve of 0.9228 compared to the support vector machine and multilayer perceptron neural network algorithms with 0.8951 and 0.8726, respectively, had a better performance in estimating the change potential of non-urban to urban areas. Furthermore, in comparison with others, random forest also clearly showed local variations in potential change. Finally, the growth of Tabriz city was simulated using the cellular automata model based on the obtained change potential maps. Comparison of the prediction map in the validation period with the current situation of urban areas in 2015 showed that the accuracy of urban growth simulation model based on random forest with a Figure of Merit index of 0.3569 compared to models based on support vector machine and artificial neural network was more accurate in allocating non-urban to urban lands with 0.3496 and 0.3434, respectively.

As machine learning algorithms such as artificial neural network, support vector machines and random forest are capable of solving non-linear problems, using them is strongly recommended for urban growth simulation. Also, among the algorithms used in this research, the random forest algorithm based on ensemble learning has a higher advantage than the two support vector machine and the artificial neural network algorithms.

In recent decades, global economic growth and industrialization have increased the demand for consumption of energy. The increasing demand for energy is met by burning fossil fuels which emit air pollution and greenhouse gas emissions. After the industrial revolution, energy generation has increased the amount of greenhouse gases abnormally, critically damaging the environment of countries. In this regard, the purpose of this study is investigating the determinants of carbon dioxide emissions (CO2) as an indicator of environmental quality and air pollution.

This study has proposed a long-run relationship between CO2, economic growth, energy consumption, trade openness, financial development, and urbanization for a global panel of 11 countries spanning the period 2000–2015 using Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS). In a first step, the LLC and IPS unit root tests were performed to examine the non-stationarity properties of our dataset. Then, Pedroni and Kao co-integration tests were applied to identify if there is a correlation between variables in the long term. In addition, the F (Chow) test was used to detect the best model. The software package used for estimation and analysis of the models is Eviews 10.

Our manuscript first performs panel unit root test proposed by Levin, Lin, and, Chu (LLC) and Im, Pesaran and, Shin (IPS) to examine the null hypothesis that all the series have unit root. The results of IPS test indicate that the null hypothesis is rejected only for urbanization, implying that this variable is stationary, while for the other six variables the panel unit root test null hypothesis is not rejected. However, all tests confirmed that variables are stationary after first difference. It is hereby inferred that variables are first differenced stationary. Our results suggest that there is a need to examine co-integration among variables. In addition, we conduct Pedroni and Kao co-integration tests whose results reject the null hypothesis of no co-integration. The results of the F-test indicate that the panel model is the right choice. To help us choose between the fixed effects or random effects estimators, we conduct the Hausman test where the null hypothesis is that the preferred model is random effects. Our results from the Hausman test do not reject the null hypothesis, suggesting that the random effects estimator is more appropriate for our data than the fixed effects estimator. The results from the FMOLS and DOLS estimations indicate that energy consumption from renewable sources, trade openness, financial development, and urbanization had a negative impact on CO2 emissions, while the energy consumption from non-renewable sources had a positive impact. The positive impact of economic development on CO2 emissions was also investigated.

The results of the research imply that policymakers should focus more on public awareness of renewable energy, mainly in solar and wind power to alleviate environmental pressure and CO2 emission. The findings also suggest that the governments should set a price per ton on carbon i.e., a carbon tax. Furthermore, developed countries should transfer sophisticated technology to emerging and undeveloped countries to generate electricity and avoid unsafe climate change.

One of the most important factors that play a major role in reducing soil fertility and ‎agricultural land degradation is soil salinization. Soil salinity problem is more sever in agricultural lands of ‎arid and semi-arid regions. In many cases, human activities and irrigation of agricultural lands with saline ‎water are the cause of salinization. This is a serious problem in different regions of Iran, especially in ‎Khuzestan province. Therefore, the present study has been conducted with the aim of monitoring and ‎evaluating the effect of Gotvand Dam on the salinization of the downstream area and changing its plant ‎ecosystem before and after water intake using remote sensing imagery.‎

The images used in the research, time series of two ETM +, OLI sensors from ‎‎2019-1999 have been collected using plant indices (NDVI, SAVI), biophysical index of leaf cover (LAI) ‎and salinity indices. The soil is classified by salient decision-making method of changes in halophyte and ‎Non-halophyte plants according to the threshold obtained from the indicators used in each year. Then, ‎the final results were evaluated according to the trend of changes obtained from the used indicators and ‎their correlation with changes in the plant ecosystem of the region.‎

The rate of vegetation changes in the four years of 2018, 2013, 2002, and ‎‎1999 was more than other years, were prepared by the method of supervised classification of the area ‎under normal vegetation and saline plants. According to the results obtained in 1999, the total vegetation ‎area of the groves was about 1117 hectares, of which about 134 hectares were related to halophyte ‎vegetation. But in 2018, these values were estimated at 921 hectares, with areas covered by halophyte ‎changing to 445 hectares and halophyte to 476 hectares. ‎

The results of the study indicate the onset of the highest stresses in the plant ecosystem of ‎the region and the simultaneous decline in leaf cover and NDVI with the dewatering of Gotvand Dam ‎since 2011. This coincidence, which is due to the salinity of the water of Gotvand Dam Lake and ‎consequently Karun River, has a significant effect on increasing salinity and changes in soil quality of the ‎region and consequently increasing halophyte plants as well as high vegetation degradation in the region. ‎These conditions can create more serious challenges for the ecosystem of this area and in the long period ‎change the ecosystem and vegetation cover of this region to halophyte plants.‎

Yazd-Ardakan plain consists of political, economic, social and ecological systems. It has valuable agricultural products, cultural background, various industries of steel, tile, glass, textile, lime kiln, asphalt, brick and sand production industries and metal and non-metal mines. On the other hands the existence of vast intact deserts and natural areas and habitats bring this plane among very important places in Iran. Therefore, it’s is essential to comprehensively study the factors affecting different ecosystems services in this plain. The DPSIR framework with a systems approach is a useful tool to formulating executive and managerial strategies. DPSIR could finally identify practical solutions for sustainable development by determines the response to the driving forces and structuring the information, determining the important connections and comprehensive understanding of the problems. In the present study, the DPSIR system approach was used to evaluate the causal relationships of the environmental challenges of the Yazd-Ardakan plain in different sectors. This framework also used to evaluate the vulnerability and to suggest the planning strategies. From this, a chain of causal connections of driving force and the consecutive pressures on the environment was identified. By examining the effect of pressures, changes in environmental conditions, consequences and effects in the system were analyzed. Finally, according to the causal relationships, short- and long-term appropriate strategies to sustainable use of ecological, hydrological, economic and social services of the plain were suggested to the policymaker.

Species separation based on phylogenetic results can be supported by modeling whose input is habitat data. In the present study, two sister taxa that have been separated based on molecular documentation have been examined in terms of habitat influencing factors that may have been involved in this separation, as well as in terms of past and future historical distribution.

in order to model the distribution of species, Bio-Climatic variables from CHESLA database with variables of DEM, Slope and vegetation index were examined as habitat data to input the model. Also, the presence points of the species were filtered after collection in the reproductive interval and added to the models as train data. In this study, sdm package including eight models (GLM،GAM ، BRT، RF،CART ،SVM ، MaxEnt و MARS) in R software environment was used for modeling. Modeling of species distribution from the last glacial period to 2050 was also performed.

the results showed the ecological niche separation of the species under the influence of environmental variables. . Also, according to the results, in 2050, suitability habitats for Embriza bruniceps species will be limited to the northeast of the country and for Embriza melanocephala species, suitability will be limited to areas in the south of Alborz mountain range, northwest and west of Iran.

According to the results the area of suitable habitats for Embriza melanocephala species in the west has been less than today, which according to studies,

Today, agricultural resource management is a fundamental task for managers and planners due to the need to address the challenging issues between the supply and demand sectors. Accordingly, many researchers have emphasized that water, food, and energy in the world are experiencing significant stress and scarcity, and demand for these resources will increase significantly in the coming decades. The main purpose of this study is to provide a method for decision makers in analysing the link between water, energy and food in the crop production system at the regional level and to perform a quantitative evaluation of it, which can be used to create a suitable and optimal cultivation pattern with Pay attention to the available resources of the area used.

The present article was conducted to evaluate the water-food-energy relations of agricultural products in Dehgolan County. The required data were collected through face-to-face interviews with farmers and agricultural jihad statistics. The proposed method of this paper is based on six indicators of water and energy consumption, mass productivity of water and energy and economic productivity of water and energy. Based on the set of these indicators, a water-food-energy index (WFENI) was calculated for each product. This method was applied to evaluate 7 main crops of wheat, potato, alfalfa, cucumber, barley, carrot and rapeseed in water farms of Dehgolan County in water year 2019-2020.

The results of data analysis showed that alfalfa and potatoes had the highest water consumption (13131 cubic meters per hectare) and energy (85404 megajoules per hectare), respectively. Barley had the lowest water consumption (4197 cubic meters per hectare) and energy consumption (31394.4 megajoules per hectare). The use of chemical fertilizers had the largest share in the energy sector (except alfalfa). In alfalfa crop, due to high mechanization operations, machinery had the largest share of energy consumption. Carrot was the most productive in water consumption (7.08 kg/ m3) and energy (1.03 kg/ mJ). ). Also, the lowest water and energy efficiency for canola (0.44 kg / m3) and energy (0.06 kg / MJ) were obtained. In the economic index of water and energy productivity, the highest values were obtained for cucumber (92959 Rials per cubic meter) and carrot (13202 Rials per megajoule), respectively. The lowest economic efficiency of water and energy was calculated with (1549 Rials per cubic meter) for carrots and (10688 Rials per megajoule) for canola. This study showed that the WEFNI calculated for carrot, cucumber, potato, wheat, barley, canola and alfalfa crops in Dehgolan city, respectively 0.86, 0.73, 0.51, 0.41, 4 / 0, 0.3 and 0.26. Carrots received the highest score WFENI (best score) and alfalfa the lowest score (worst score). Although potato, which is one of the water crops with a high level of cultivation in the region, has high water and energy consumption, but due to its high physical productivity and economic productivity, it obtained the third score of the total index.

In this study, agricultural products were compared based on indicators of water and energy consumption, physical productivity of water and energy and economic productivity of water and energy. Based on these indicators, the water, food and energy link index was calculated. The results can also be used as an effective tool to determine appropriate strategies for cultivation pattern, management of water and energy resources in the region and a basis for planning and agricultural policies in the county.