نشریه آب و خاک
سال سی و هشتم شماره 3 (پیاپی 95، امرداد و شهریور 1403)

Accurate knowledge of water balance components is necessary to optimize water consumption in agriculture. On the other hand, measuring water balance components is expensive and difficult. Therefore, the use of models that can simulate water balance values is important for water management in agriculture and water used by plants. Crop simulation models have been turned into essential tools for studying plant production systems. In the SSM-iCrop2 models, it is presumed that diseases and weeds are optimally managed and will not affect growth and yield. Additionally, except in cases where the model accounts for specific nutrients such as nitrogen, it is generally assumed that nutrient deficiencies are eliminated through fertilization. Therefore, parameterized and evaluated models are designed to fit these conditions. These factors are present in the field and affect crop growth and yield as well as water use. However, in several cases it is required to estimate yield and water balance components and irrigation water volume under grower conditions. Naturally, models parameterized using experiments are unable to simulate these conditions. Therefore, a model must be prepared so that it can simulate the real conditions of farmers. In this study, the SSM-iCrop2 model has been calibrated for the real conditions of farmers, and the purpose of this study is to use the SSM-iCrop2 model in simulating water performance and water balance for farmers.

In this study, the SSM-iCrop2 model was calibrated for farmers conditions using variables such as yield and harvest index, which are available for farmers’fields or are cheap to measure. The effect of factors such as pests and diseases, weeds and unsuitable nutrients, density and sowing date entered the model along with the calibration of three parameters of radiation use efficiency, maximum leaf area and maximum harvest index for farmers’ fields. Calibration was done by comparing the performance of farmers against the performance simulated by the model and by changing the parameters of radiation use efficiency (IRUE), maximum leaf area (LAIMX) and maximum harvest index (HIMAX). This calibration was done at Hashem Abad station in Gorgan for irrigated rice (paddy) and wheat. The simulated actual yield was calibrated with the actual yield. Due to the acceptable simulation of actual yields after calibration, it was presumed that other estimates made by the model are also reliable.

Measurement of water balance and other estimates of the model from growth and yield formation in the grower fields is expensive, but a calibrated model can estimate them at a low cost. In this study, it was shown that with the model calibrated for farmers' conditions, not other easily measured information (such as the irrigation water volume) can be obtained, with the assumption that the model accurately captures this information as well as performance. To evaluate the simulated real performance model, it was compared with the actual performance of farmers (Agricultural Jihad Report) after calibration. In addition to phenology, the SSM model simulates traits related to growth and yield, evapotranspiration values, irrigation water volume, runoff, available soil water during planting and harvesting, cumulative drainage, etc. The output of the model shows the amount of irrigation water is needed for a certain amount of performance in a given place (with specified rainfall and transpiration). The irrigation water volume calculated by the model was compared with the results of field tests from previous studies conducted by researchers at agricultural research centers. It was found that the model's output and the observed values were in good agreement. The root mean square error for rice and wheat was 216.6 and 157.6 kg per hectare, respectively, and the coefficient of variation and correlation coefficient were 4 and 85% for rice and 3 and 94% for wheat, respectively. Then, the irrigation water volume estimated by the model was evaluated and validated with the measured irrigation water volume in different crops (in Golestan province for different years). Based on the results of the evaluation, the coefficient of variation and the correlation coefficient for the simulated irrigation water volume were 8.9 and 98%, respectively, compared with the observed value. This calibration was done for rice (paddy) and irrigated wheat in the fields of Gorgan town, and the simulation and running were done using the meteorological statistics recorded in Hashem Abad weather station, Gorgan. Noting the fact that the actual yield has been simulated with good accuracy after the calibration, it was assumed that the other estimates of the model are also reliable. Thus, the calibrated model estimates them with low cost and appropriate accuracy and can complement field experiments.

This study discovered that the SSM_iCrop2 model, when calibrated for the conditions of farmers' fields, can accurately simulate both growth and yield traits as well as water balance characteristics. Notably, the model provides reliable estimates of irrigation water volume in farming scenarios, a crucial factor for agricultural planning and drought adaptation.

Spring frost is considered an important threat to agricultural products in high and middle latitudes. The damage caused by Late Spring Frosts (LSFs) significantly impacts vulnerable plant organs. This event has caused more economic losses to agriculture than any other climatic hazard in Asia, North America, and Europe. Also, these phenomena have contributed to low crop yields in Iran. The latest statistics released by the Food and Agriculture Organization of the United Nations (FAO) show that Iran is one of the largest producers of agricultural products and the world’s second-biggest producer of pistachios. Kerman province is one of the significant areas of pistachio production. This province has a large share of the pistachio word area plantation. Spring frost damage to pistachio crops has led to low yields in recent years. A key aspect of studying frost is the ability to accurately estimate its occurrence. In this study, artificial neural network methods have been used to estimate late spring frost in the pistachio crop of Kerman city.

In this study, the efficiency of this method was investigated in the estimation of minimum temperature. For this purpose, the daily data of the synoptic station of Kerman city were obtained from Iran Meteorological Organization from 2000 to 2020. Meteorological data including mean, maximum, and minimum temperatures, relative humidity, wind speed, saturated vapor pressure, and sunshine hours were used. Five different combinations of these variables was considered as input variables in artificial neural network method for minimum temperatures modeling. After entering data into network and modeling with each combination, RMSE and R2 values were calculated. Finally, the combination of 8 variables including average and maximum temperature, the minimum temperature the previous day and two days prior, relative humidity, wind speed, saturated vapor pressure, and sunny hours were selected as the most suitable combination of variables. Subsequently, a simulation of minimum temperature values was conducted using 10% of the data. The performance of the methods was evaluated using statistical indices of coefficient of determination (R2), mean square of error (RMSE), Mean Bias Error (MBE), and Coefficient of Nash–Sutcliffe (NSE).

The accuracy of an analytical method is the degree of agreement between the test results generated by the method and the true value. Upon examining the models, the M1 model was identified as the best due to its lowest RMSE and higher R². ANN model results were evaluated using various performance measure indicators. The simulated outcome of the model indicated a strong association with actual data, where the correlation coefficient was above 0.95, and the MBE index was zero. Also, the RMSE value was positive and close to zero, and the NSE value was above 0.75. Therefore artificial neural network method had high accuracy. In this study, mean annual minimum temperature was estimated using artificial neural network models (from March 10 to May 20). Comparison between the observed and calculated data showed that these data were in good agreement. Also, the results showed that temperature fluctuations were high between March 10 and March 31. From 2011 to 2017, an almost uniform temperature trend has been observed between March 10 and March 31. However, the years 2000, 2006, and 2020 showed a noticeable decrease in temperature. From 2018 to 2020, this trend of temperature reduction continued. In April, the temperature values were between 7 and 10 degrees Celsius. The years 2001, 2005, 2006, 2009, 2016, and 2019 had a noticeable decrease in temperature. In May, the mean minimum temperature was between 10 and 14 degrees Celsius. Therefore, the probability of frost occurrence in early-flowering cultivars was higher in late March than in April and May. The years 2000, 2004, 2005, 2012, 2015, 2019 and 2020 had the highest number of frost days in the last two decades.

The results showed that the artificial neural network method had a high performance in estimating the minimum temperature. The values of the statistical indicators were R2=0.963, RMSE=0.027oC, MBE= 0 and NSE=0.966 respectively. In addition, the ANN method performed well in estimating the number of critical frost days for pistachio crops. The results showed that, although reducing the amount of input data in models decreases their output precision, data-driven methods can still be useful tools for minimum temperature estimation.

 Groundwater is an important resource for domestic, agricultural, and industrial purposes (Andualem and Demeke, 2019). However, the growing population and advanced irrigation technologies have significantly led to increased groundwater exploitation resulting in aquifer depletion. Exploitation of groundwater from fractured rock aquifers using wells to supply drinking water is more sustainable than the utilization of springs with low and variable discharge. In the case of drought and periods of critical condition of water usage, springs of fractured rock aquifers may dry up or decrease making them unreliable water resources to supply drinking water. Over recent decades, the use of fractured rock and karstic units as a remarkable water resource is known as a valuable source of freshwater worldwide. However, these aquifers are extremely vulnerable to contamination due to their unique hydrogeological characteristics and require more protection (Zarvash & Vaezi, 2014). These resources contribute to providing more than 70% of the rural population and around 50% of the urban population with drinking and household demand needs. Since the degree of development of karst landforms varies substantially from region to region, exploring groundwater potential zones in karstic or fractured rock domains across the world is important, which is mostly achieved using evaluating affecting factors in creating the groundwater occurrence. This evaluation is done by incorporating weighted factors such as Weighted Overlay, Weighted Sum, and Fuzzy Overlay and utilizing geographic information systems (GIS) or other remote sensing techniques, which is addressed frequently in literature summarized by Vaezihir and Tabarmayeh (2016); Seif and Kargar (2011); and Amiri et al. (2021). Considering the importance of such issue, this research aims to investigate the potential of karstic or fractured rock resources in West Azerbaijan to gain more insight into this valuable resource of groundwater.

West Azerbaijan province, with an area of 43,660 km² including Lake Urmia, is equivalent to 2.65% of the total area of Iran and located in the Alborz-Azerbaijan structural zone with a mean annual precipitation of about 370 mm. The maximum temperature of this province, dominated by a semi-arid and Mediterranean climate, is recorded in Shahin Dezh and Miandoab, and the minimum is measured in Chaldoran, and Tekab Metrological Stations, respectively. About 78% of the total area of West Azerbaijan province is formed by karstic units with more spatial distribution in the southern area. This karstic area encompasses 71% of the total province springs with 59% of the total discharge. In the current research, lithology unit types, fracture density, elevation, slope, aspect, drainage density, and vegetation coverage, along with the precipitation, area, and humidity index as the main factors were regarded as governing factors in the development of karst aquifers, have been considered to evaluate the potential groundwater resources. After the preparation of all affected layers using various data resources including available geological maps digital elevation map of West Azerbaijan Province obtained from the Geological Survey and Mineral Exploration of Iran, Landsat satellite data, the Fuzzy logistic and SUM and Weighted overlay technique has been used to prepared groundwater potential zone.

The groundwater potential zone were determined through combining 9 affected layers in developing the groundwater resource. The results obtained based on employing both weighted overlay and SUM  were classified into 5 classes including low, very low, medium, high and very high potential zones. The index value in SUM methods estimated to be 16.24, 26.24, 24.24, 20.95, 12.13%, while it changes to 22.82, 24.13, 22.14, 16.23, and 14.67 respectively. Overlaying the location of springs as an indicators of groundwater resource on hardrock and karstic domain on generated maps showed that 30.9 and 33.08 percentage of springs fall in area with the high and very high potential zone, respectively. A significant differences on maps generated based on two mentioned technique, particularly in area classified as low potential zone with 24.13 and 16.24 percent in weighted overlay and SUM.  

Investigation of the groundwater potential zone by integrating the layer provided by Fuzzy logic technique through two SUM and weighted overlay methods indicated the province of Azerbaijan Arabi has a moderate level of classification. However, in some areas, there were significantly higher or lower potentials.

The rapid growth of technology, industry, and development of cities has led to an increase in heavy metal pollution in freshwater sources and greywater across the world. The use of different adsorbents in order to remove some heavy metals from aquatic environments is a topic that has been addressed many times in different studies. However, the use of inexpensive absorbents with high adsorption capacity and high efficiency is the priority of many researchers especially when they are discussing the removal of heavy metals from the aquatic environment. Nanomaterials by having exceptional properties such as high efficiency of adsorption, high specific surface area, and fast adsorption can be used to remove metal pollutants from aquatic environments. Carbon dot (CD), among various nanomaterials (carbon-based nanomaterials (CNM), including carbon nanotubes (CNTs), graphene) are suitable adsorbents for heavy metals removal due to their specific surface area and many binding sites. Carbon dots are nanoparticles that lack a specific dimension and fall under the category of carbon nanomaterials, measuring over 10 nm in size. They possess various qualities, including being environmentally friendly, simple to create, highly compatible with living organisms, stable, and capable of switching emission on and off based on the excitation wavelength. Additionally, they can be customized for specific uses due to their high carbon content, which can reach up to 99.9%. These characteristics have generated significant interest among researchers in various fields. In this study, the influence of the fungal carbon dots on the adsorption capacity and kinetics, isotherms, and thermodynamics of lead was investigated.

Alternaria alternata provided by the Department of Plant Protection at Ferdowsi university of Mashhad. It was recultured and fungal exopolysaccharide was extracted and then was converted into carbon dot using the hydrothermal method. Fungal exopolysaccharide autoclaved in a Teflon container at a temperature of 200 °C. Lead adsorption of synthesized fungal carbon dots was investigated. Lead adsorption tests by fungal carbon dots were performed in laboratory conditions. Lead concentrations (100, 200, 300, 400, 500, 750 and 1000 mg L-1), contact time (5, 10, 15, 20, 25, 30 and 60 minutes), pH (2, 4, 6, 7, 8, 9, 10 and 11), amount of carbon dots (nanosorbent) (50, 100, 200, 300, 400, 500, 750 and 1000 mg), ionic strength of the solution (0.1, 0.01 and 0.001 M potassium chloride) and solution temperature (25, 30, 35, 40 and 45 °C) was considered for kinetic tests. The data obtained from the kinetic tests were fitted using non-linear regression analysis using Statistica 7.0 software with the kinetic models of intraparticle diffusion, Lagergren (pseudo-first order) and pseudo-second-order. Thermodynamic results were calculated from the data of lead adsorption isotherms at temperatures of 25, 35 and 45 °C. Thermodynamic parameters to analyze the effect of temperature on metal adsorption, such as free energy change, enthalpy change and entropy change, were estimated using thermodynamic equations.

The initial lead concentration had a great effect on the adsorption rate it by carbon dot, and the highest and lowest percentage of lead adsorption with values of 90.65 and 44.2% were observed in two concentrations of 300 and 1000 mg L-1 of lead, respectively. With the increase of pH up to 8, the amount of lead adsorption by fungal carbon dot increased significantly. However, with further increase in pH, this trend was reversed and the amount of adsorption decreased. The results showed that lead adsorption by carbon dot increased with the decrease of potassium chloride molarity. By increasing the amount of carbon dot in the solution, the amount of lead adsorption increased, and the highest adsorption was observed at the concentration of 300 mg L-1 of carbon dot. The results of the experiment also showed that with increase in temperature, the adsorption rate increased at first and then decreased. Based on these results, as the contact time between the absorbent and lead increased, the amount of adsorption by the carbon dots also increased. The maximum adsorption was observed at 25 minutes, which was considered the equilibrium time. As shown in the results, the pseudo-second-order model shows the kinetics of Pb adsorption better than the two pseudo-first-order models and intraparticle diffusion. In this model, R2 values are between 0.9989 and 0.9994, and Qe is almost equal to the equilibrium value. According to these results, the decrease of values DG° with the increase in temperature means that the adsorption of lead increases with the increase in temperature, which shows that the adsorption process is more favorable with the increase in temperature, or in other words, it is a spontaneous reaction. Also, the positivity of the reaction enthalpy value (DH°) shows the endothermic nature of the adsorption process. The positivity of the entropy value (DS°) indicates the increase of disorder of the system between the adsorbent material and the solution during the process of lead adsorption by the carbon dot.

In total, the results showed that the carbon dot is a very good absorbent for removing lead from the water environment. In the experimental condition when the initial concentration of lead was 300 mg L-1, temperature was 25 °C, adsorbent concentration was 0.3 g L-1, reaction time was 25 minutes, and pH 8, the amount of lead adsorption increased significantly. It seems that fungal carbon dot is a safe and relatively cheap adsorbent and suitable for removing lead metal from the solution environment.

Soil properties play a crucial role as they determine the soil's suitability for different types of plant growth, ecosystems, and biota functioning. They have a significant impact on nutrient cycling, carbon sequestration, and soil management. Digital Soil Mapping (DSM) is a process aimed at delineating soil properties. Soil sampling for DSM serves as  a fundamental  step in improving prediction accuracy and is crucial for incorporating variability in terms of environmental covariates. Conditioned Latin Hypercube (CLH) sampling is a technique utilized to generate a sample of points from a multivariate distribution conditioned on one or more covariates. Numerous researchers (Ramirez-Lopez et al., 2014; Adhikari et al., 2017; Zhang et al., 2022) have endorsed this approach in their studies, following its inception by Minasny and McBratney in 2006. However, there has been limited research to date on the impact of the Latin hypercube method's random sample selection process on the accuracy of resulting maps. Hence, the central question remains: Is the Latin hypercube sampling method, which is currently widely adopted, always a dependable approach in this field?

The study area covers longitudes 50°35'47'' to 51°29'' east and latitudes 31°36''31'' to 32°15'48'' north in Borujen city, Chaharmahal, and Bakhtiari Province. The region, with an average elevation of 2338 meters above sea level, receives an annual rainfall of 250 millimeters and maintains an average temperature of 11.5 degrees centigrade. In this investigation, inherited data from soil studies were utilized, consisting of 250 samples distributed across the study area. In this research, the studied characteristics included percentage of equivalent calcium carbonate, clay, and soil organic carbon at a depth of 0 to 30 cm. Land component variables were extracted using the Alus Palsar digital elevation model with a spatial resolution of 12.5 meters. In the initial stage, digital maps of equivalent calcium carbonate, clay, and soil organic carbon were generated using the support vector machine method. The modeling process proceeded until a highly accurate model was achieved, with the root mean square error percentage (RMSE%) being less than 40. The Latin hypercube approach was utilized for sample design, with 500 repetitions in this study. After selecting sampling points for each run using the Latin hypercube method, these points were mapped onto a detailed map, and the corresponding feature values were retrieved. The final map was created based on the extracted points. Subsequently, the latin hypercube approach was employed to generate soil property maps for each selected dataset. Validation was conducted using criteria such as the coefficient of explanation, root mean square error, and root mean square error in multiple iterations to ensure the accuracy of the generated maps.

The results distinctly illustrates the varied selection of sampling positions with each implementation of the Latin hypercube method. It is important to note that there may be some overlaps in different implementations. Consequently, the primary question arises: Is a one-time execution of the Latin hypercube sufficient for selecting study points? The findings indicate that the support vector machine model achieves satisfactory accuracy for all the examined characteristics. In the studied area, the environmental factors such as slope and elevation were identified as a significant predictors for estimating percentage of equivalent calcium carbonate.

In the present study, the accuracy of the latin hypercube method was assessed for selecting sampling location for digital soil mapping endeavors in Chaharmahal and Bakhtiari Province. Given the impracticality of collecting numerous field samples to evaluate the soil sampling method, this research aimed to employ simulation methods based on highly accurate maps for this purpose. The results indicate that the different outputs of the Latin hypercube method influence the accuracy of modeling, although this effect is also influenced by the specific feature under investigation and the extent of its variability within the study area.  Considering that the Latin hypercube method is based on the principle that samples are randomly selected in each class of environmental parameters, it is suggested that future studies using this method should account for this principle. Adequate consideration should be given, and the selection of sampling locations should rely on multiple implementations of the Bhattacharya distance method to ensure robustness and reliability.

Wheat is considered the most important grain and one of the vital food products in Iran. After nitrogen, phosphorus is the most important nutrient required by plants and holds a high priority for the growth, yield and quality of plants. However, due to the introduction of phosphorus in various reactions in the soil, a small amount of consumed phosphorus fertilizer is removed by the plant and the rest of it is left in a non-absorbable form in the soil. The efficiency of using phosphorus fertilizers and the availability of this nutrient is considered as a limiting factor for the production of agricultural products in calcareous soils with alkaline reaction of Iran. Since graphene and its oxidized form, with large amounts of active oxygen groups and high specific surface area, have been proposed by many studies as non-toxic and biocompatible materials in the production of compounds with improved efficiency of using nutrient, therefore to increase the efficiency of phosphorus consumption in soil, in this study, phosphorus was loaded on graphene oxide (GO-P). The present study aims to assess the influence of this compound as a source of phosphorus and its mixing with triple superphosphate fertilizer (GO-P-TSP) compared to triple superphosphate soluble fertilizer (TSP) on the amount of water retention of fertilizers in soil and phosphorus concentration in aerial parts of wheat plant.

Methods and Materials:

Graphene oxide was prepared based on the modified Hamers method. Then graphene oxide was adjusted to certain pH and iron sulfate as a source of iron ions was added to the graphene oxide suspension with vigorous stirring. The mixture was stirred for one hour and then centrifuged for 30 minutes. Then the supernatant was removed and the residue of the compound was dry frozen. In the next step, pH was adjusted with sodium hydroxide (NaOH) solution. Then a certain weight of potassium dihydrogen phosphate salt (KH2PO4) was added to the above suspension. The mixture was stirred for one hour and centrifuged for 30 minutes. After centrifugation, the supernatant was removed and the remains of the phosphorus composition based on graphene oxide were dry frozen. Loading tests were performed in three replicates. pH, EC, bulk density, total concentration of phosphorus and iron and X-ray diffraction spectroscopy (EDS) analysis were measured in the sample of phosphorus composition based on graphene oxide. Then three fertilizer formulations were selected, which included (1) triple superphosphate fertilizer, (2) synthesized phosphorus fertilizer based on graphene oxide, and (3) mixing graphene oxide-phosphorus compound with triple superphosphate fertilizer in a ratio of 50:50% phosphorus.To investigate the water retention behavior of fertilizers in the soil, dried samples of the three studied fertilizer formulations was added into a sandy soil completely and weighed. At the same time, dried sandy soil without fertilizer was placed in another beaker as a control.Then each beaker was added distilled water and weighed. The beakers were weighed once every three days at room temperature until they reached constant mass. The water-retention behavior of the soil was calculated.In order to investigate the effect of three fertilizer formulations on phosphorus availability, soil with low amount of phosphorus was selected and physical and chemical properties of the soil sample were measured at a depth of 0-30 cm. A greenhouse experiment on wheat planting was conducted using a randomized complete design with 3 replications. The treatments included three fertilizer formulations at three fertilization levels (10, 15, and 20 mg kg-1) with 3 replications. The control treatment was performed without phosphorus fertilizer. Plants were harvested 72 days after planting, washed with distilled water and dry with tissue paper. The samples were air-dried and then oven dried at 70˚C to a constant weight in a forced air-driven oven. After harvesting, the weight of fresh and dry matter and phosphorus concentration in the soil and aerial parts of the plant were measured. Statistical data were analysed using SAS software (9.4) and the mean values were compared using LSD tests (at 1 and 5% level).

The composition of phosphorus based on graphene oxide (GO-P) in powder form had 35.5% of total P2O5, 31.1% of soluble in water P2O5, 19.6 of total iron and 15.28% of total potassium. The result of EDS analysis confirmed the loading of phosphorus on graphene oxide. The pH of the phosphorus composition based on graphene oxide was 5.8, approximately 2.5 units higher than triple superphosphate fertilizer. The bulk density of the compound (GO-P) was significantly lower than triple superphosphate fertilizer. The EC of the compound (GO-P) was similar to the EC of the triple superphosphate fertilizer. Soil water retention with synthesized phosphorus fertilizer based on graphene oxide (GO-P) was higher than soil (control) and other compounds added to soil. Experimental results showed that the addition of prepared fertilizer formulas (GO-P and GO-P-TSP) increased water retention in the soil for a longer period of time, while in the soil without adding fertilizer and triple superphosphate treatment, respectively, from 10 and 11 days, the absorbed water completely evaporated. Therefore, the combination of soil with GO-P and GO-P-TSP compared to the soil without fertilizer and the combination of soil with triple super phosphate (TSP) fertilizer had better water retention behavior. The greenhouse experiment results of wheat planting showed that all treatments were significant (P<0.01). Among all the treatments and measured levels, the control treatment showed the lowest value. The highest concentration of phosphorus in aerial parts of wheat (0.31%) and in soil after harvesting (9.5 mg kg-1), fresh (10.6 g per pot) and dry weight (2.03 g per pot) of aerial wheat plants were related to the treatment of phosphorus compounds based on graphene oxide at the level of 20 mg kg-1.

The highest concentration of phosphorus in aerial parts of wheat was related to the treatment of phosphorus compound based on graphene oxide at the level of 20 mg kg-1. Therefore, with more research in the future to produce "nutritious plants" in sustainable, efficient and flexible agricultural systems, we can benefit from technologies based on carbon materials.

Layered double hydroxides (LDH) have gained considerable attention for their potential application in agriculture, serving as a slow release sources of essential nutrients for plants. The appraising of LDH as a favorable fertilizer is in the early development, and more studies on the nutrient release mechanism of LDH are needed to answer the question of how LDH could replace commercial fertilizers for providing the stable nutrients for plants. Although several studies on the release of P from LDH exist in the literature, no information regarding ratios of divalent cation (M2+) to trivalent cation (M3+) in LDHs on phosphate release from LDHs is available. So, it is important to raise our knowledge about various parameters like pH and time on the solubility of LDHs. This study aimed to investigate the effects of pH and the ratios of M2+/M3+on the kinetics release of P from Mg-Al-LDH.

All the chemicals in this research, such as magnesium nitrate hexahydrate (Mg (NO3)2.6H2O) and aluminum nitrate nonahydrate Al(NO3)3.9H2O were of analytical grade and obtained from Merk (USA). The solutions were made with decarbonated pure water without impurities (electrical resistivity = 18 MΩcm). Two nitrate forms of Mg-Al-LDH were synthesized using the co-precipitation method at constant pH by varying the Mg/Al ratios (2:1 and 3:1) in the precursor solution. Briefly, 50 mL of 1M solution containing nitrate salt of divalent cations (Mg(NO3)2.6H2O) and trivalent cations (Al(NO3)3.9H2O) in the appropriate ratios (2:1 and 3:1) were added simultaneously for 2h to 400 mL of 0.01M solution of sodium hydroxide while being stirred vigorously in a nitrogen atmosphere. The pH was kept at 9.5 by adding volumes of 3 M NaOH. Afterward, the material was ripened in the synthesis mixture for 2 h and centrifuged at 3000 rpm for 20 min. The precipitates were washed by three washing-centrifugation cycles with Milli-Q water and subsequently dried at 70 °C. In this study, LDH-P was made by ion exchange. The LDH-N were treated with 0.05 M KH2PO4 solutions at pH 7.2. The suspensions were shaken end-over-end for 24h, followed by centrifugation, washing, and drying as described above. After digesting the dried LDHs in aqua regia (3:1 HCl/HNO3), the total P concentration of the LDHs was determined. The chemical composition of the synthesized LDHs was determined by graphite furnace atomic absorption spectrophotometry (SavantAA, GBC) after acid digestion (3:1 HCl/HNO3). Crystallization and morphology of the LDHs were characterized via scanning electron microscopy (SEM) and X-ray diffraction (XRD). The XRD patterns were prepared using an x-ray diffractometer (Panalytical x Pert Pro, Netherlands), at scan step time of 1s from 2θ=5° to 2θ=70° (40KV and 30 mA), and with a step size of 0.0260, which were used to identify the mineral phases. The phase purity was surveyed by comparing these XRD diagrams with those found in the literature. The SEM photographs were gained on a scanning electron microscope (SigmaVP, Germany). Fourier Transform Infrared (FTIR) spectrum was done on a Nicolet iS10 FT-IR spectrometer by utilizing KBr pressed disk technique.A batch study was done to determine the effect of different ratios of M2+/M3+ in LDHs at different pH 6.0 and 8.0 on the release of P from LDHs. Briefly, 0.01 g of synthesized LDH were put in a centrifuge tube mixed with 10 ml of 0.03M KNO3 at initial pH=6 and 8. Suspensions were shaken at a constant temperature (25±0.5 °C) and agitation (180 rpm) by using an incubator shaker for 8h. Phosphorus concentration in supernatant solutions was measured by vanadate yellow method at 470 nm wavelength.In order to investigate the kinetics of phosphorus release, LDH-P1 (2:1) and LDH-P2 (3:1) were used at two initial pHs of 6 and 8. First, 0.012 g of LDH sample was placed in 120 ml of KNO3 electrolyte solution (with ionic strength of 0.03 M) in an Erlenmeyer flask. The flasks were shaken for 5 to 1175 min by an incubator shaker at 100 rpm. Then the suspensions were centrifuged at a speed of 4000 rpm for 20 minutes and the phosphorus concentration was determined by the method described previously. All experiments were performed with three repetitions. Two equations (pseudo-second-order and parabolic diffusion) were used to fit the kinetics data.

According to the XRD patterns, the sharpness and reflection of diffraction planes (003) and (006) pertained to layer structures. The basal spacing as calculated by Bragg’s law (nλ = 2d sin θ) were 7.94 and 8.0 Å for Mg-Al-NO3 with M+2/M+3 2:1, 3:1 respectively. The XRD patterns of the LDHs exhibited a distinct characteristic reflection (003), which indicated that the basal spacing decreased as the Mg/Al ratio decreased (higher AEC). In addition, the decreased basal spacing is linked with a decrease in the interlayer spacing. The different basal spacing of LDH were related to the layer charge density, the content of water, and the reorientation of anions in the interlayer of LDH. The intercalation of phosphate anions into Mg/Al LDH is in adaptation with the change toward lower 2θ angles of the (001) reflections corresponding to the expansion of the basal distance d003 compared to the host Mg/Al-NO3-.Two bands of FT-IR spectrums around 3470 and 1655 cm-1 for all synthesized LDH materials designate stretching vibrations of the O-H group of hydroxide layers and the interlayer water molecules. The band vibration of phosphate was perceived at 1051 cm−1 and 1064 cm-1, reflecting the formation of inner-sphere surface complex (M-O-P) between dihydrogen phosphate ions and MgAl-LDH materials. It indicated that the phosphate exchange process may be resulted in the formation of bidentate and monodentate surface complexes. According to the SEM images, the well-crystallized and plate-like morphology were typical for layer double hydroxides. The results of the X-ray energy dispersive spectroscopy (EDS) analysis showed, the only elements that existed in the LDH-N were Mg, Al, N, and O, whereas Mg, Al, P, and O were detected in the LDH-P. The results showed that increasing the pH from 6 to 8 in the presence of 0.03 M potassium nitrate background electrolyte led to an increase in phosphorus released from both types of LDH. For example, by increasing the initial pH of suspensions from 6 to 8, the amount of cumulative phosphorus released from LDH-P1 increased from 38.59 mg kg-1 to 41.91 mg kg-1 at equilibrium. In all studied pHs, phosphorus release from LDH-P1 in background electrolyte was lower than LDH-P2. For example, at pH 6 and 8, the amount of cumulative phosphorus released from LDH-P2 was 1.46 and 1.33 times higher than LDH-P1 at equilibrium, respectively. The cumulative phosphorus release kinetics from the studied LDHs showed that the amount of phosphorus release accelerated with increasing time. Phosphorus release from LDH continued at a higher rate from 0 to 400 minutes in the first stage and at a slower rate during 400-1175 minutes. Also, based on the results, among the studied kinetic equations, pseudo-second-order and parabolic diffusion equations had the best fit on phosphorus release data.

The results of this research showed that the release of phosphorus from LDH is dependent on time, pH and the type of LDH. Based on the results of fitting the kinetics models to the experimental data, the release rate of phosphorus from LDH-P2 (3:1) was higher than that of LDH-P1 (2:1). Cumulative phosphorus release from LDH-P2 compared to LDH-P1 was 46.54, 33.61% higher at pH 6 and 8, respectively.

Dust emission is considered as one of the environmental hazards in arid and semi-arid regions. Understanding the effective variables in increasing dust mass density is very important for early warning and reducing its imposing damages. One of the main and effective variables in the occurrence of dust is the geographical and climate characteristics of the origin areas and areas affected by this phenomenon. Feeding the great rivers of Mesopotamia, it has reduced soil moisture. Also, the wind component is one of the reasons for the increase in dust in these areas. This study examines the relative importance of climatic variables to investigate seasonal and monthly changes in dust emission in West Asia and parts of South and Central Asia.

This study has examined West Asian dust from three perspectives spatial distribution, trends, and their relationship with climate variables. For this purpose, the Dust Column Mass Density (DUCMASS) variable output of the MERRA-2 dataset was used to investigate the spatial distribution of the dust mass density trend, and the AgERA5 dataset was used to investigate the seasonal and monthly changes of precipitation, wind speed, and temperature variables from 1981 to 2020. In this study, the modified Mann-Kendall (MMK) trend test method was used to investigate the trend of dust occurrence in the study area, and the Sen's slope estimator (SSE) test was used to investigate the slope of the trend and to better display the changes in dust mass density in the western region. the results of the SSE test have been examined on a decade scale.

Investigating the possible climate drivers in the changes of dust mass density for different regions by calculating the correlation between the time series of dust mass density and the variables of temperature, precipitation, and wind speed has been investigated. The results showed that there is an inverse correlation between dust mass density and precipitation and a direct relationship between dust mass density and temperature and wind speed. The highest correlations between dust mass density and temperature have been calculated, and this value has reached 0.9 in the warm months of the year. On the other hand, the highest negative correlations have been calculated in the cold period of the year (winter and autumn seasons) between dust concentration and precipitation with a value of -0.7. Thecorrelation coefficient between dust mass density and wind speed in the months of January to May and November to December was mostly above 0.6. This value shows a lower correlation in the summer season.In most months of the year, dust mass density shows an increasing trend in most regions, from March to July, an increasing trend in active dust springs in Mesopotamia, the deserts of Iraq and Syria, the desert of Rub' Al Khali, Ad-Dahna and Al Nufud Al Kabir were observed in Arabia and Thar desert in Pakistan. This increasing trend started cyclically from the beginning of spring and reaches its peak in June and July, and the intensity of the trend decreases from September and reaches its minimum value in December. The important point is that the cycle of changes in the monthly trend of dust mass density coincides with the cycle of changes in dust mass density. The northern parts of Iran and Turkey have the highest frequency among different months of the year with a decreasing trend of dust mass density. The increasing trend of dust mass density in the spring and summer seasons in Mesopotamia, the deserts of Iraq, Syria, and Yemen, the Sistan Plain, and the Thar desert in Pakistan and the southeast of Iran was significant at the level of 0.05.

The results revealed that the seasonal changes in dust mass density show well the active sources of dust in the studied area. In the spring and summer seasons, the activity of the dust centers located in the west of the study area, including the Rub' al Khali, Ad-Dahna and Al Nufud Al Kabir deserts, Mesopotamia, the deserts of Iraq and Syria, increases and on the arrival of dust to the west and southwest Iran affects. The investigation showed that climate variables play a key role in the variability of dust mass density in the study area so the areas corresponding to the summer north wind and the 120-day wind of Sistan have shown the highest dust mass density in annual variability. The correlation coefficient between dust mass density with temperature and direct wind speed and its correlation with negative precipitation have been obtained. The results showed that dust mass density has an increasing trend in most of the regions, so from March to August (spring and summer), the increasing trend of dust mass density is significant at the level of 0.05. The highest intensity of the increasing trend was observed in the spring and summer seasons in Mesopotamia, the deserts of Iraq, Syria, and Yemen, the Sistan Plain, and the Thar desert in Pakistan and southeast Iran.