Soil science
N. Sahraei; A. Landi; S. Hojati; Edoardo Pasolli
Abstract
Introduction
In recent years, soil contamination with potentially toxic elements (PTEs) has become a major problem in most parts of the world. PTEs are naturally generated from the pedogenesis in the soil and are formed mainly by rock weathering. Nevertheless, the natural content of metals, i.e., Cr, ...
Read More
Introduction
In recent years, soil contamination with potentially toxic elements (PTEs) has become a major problem in most parts of the world. PTEs are naturally generated from the pedogenesis in the soil and are formed mainly by rock weathering. Nevertheless, the natural content of metals, i.e., Cr, Zn, Ni, Pb, Cd, used to be low in the soil, but due to anthropogenic activities such as industrial emissions, atmospheric transportation, sewage irrigation, and application of pesticides and fertilizers, there is an increase in the content of PTEs. PTEs in soil are one of the most important environmental pollutants due to their toxicity, durability, easy absorption by plants and long half-life. Therefore, the assessment of soil health is very important for the sustainable development of agriculture and the rehabilitation of soils contaminated with PTEs. The present study was conducted to quantify PTEs pollution for soil environmental assessment using a flexible approach based on multivariate analysis and using pollution indicators in a part of the central lands of Khuzestan province.
Materials and Methods
For this purpose, in February 2021, 200 surface soil samples (0-10 cm) were taken using stratified random sampling. The collected soil samples were cleaned by removing plant materials and other pebbles, and air dried, powdered, and sieved by using a 2 mm sieve size. The interest in soil's physical and chemical properties i.e., pH was determined with a digital pH meter. Soil textural particles were measured by the hydrometer method, soil organic carbon (SOC) content was estimated by following Walkley and Black method, bulk density (BD) was measured by the Clod method, and total metal content was determined using the aqua-regia solution digestion method and analyzed using Inductively Coupled Plasma-Optical Emission spectrometry (ICP-OEC). The level of Pb, Ni, Zn, Cr pollution was estimated based on environmental indicators including contamination factor (CF), enrichment factor (EF), geo-accumulation index (Igeo), pollution index of individual metals (PI), and modified pollution index of individual metals (MPI). Multivariate statistical methods including correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to find the source of metals in the soil. All statistical methods were performed using SPSS (26 version) software.
Results and Discussion
Measurement of soil pH showed that the soil of the studied area tends to alkalinity. Also, the soil texture in this area is loam. The results showed that the SOC in these soil samples is 0.71%, and the range of EC (between 0.18 and 60.5 dS/m) indicates the distribution of saline and non-saline soils in the studied area. The total average concentration of Zn, Ni, Cr, and Pb were 60.26, 50.96, 50.38, and 12.67 mg/kg, respectively. The order of average for heavy metals was Zn> Ni> Cr> Pb. The highest amount of standard deviation and concentration changes were observed in Zn and Pb elements. These two elements also showed a high degree of variation coefficient in the studied area, which can indicate the high impact of human activities on the content of these elements. The results obtained from the application of multivariate statistics showed that there is a positive correlation between the elements such as Zn, Ni, and Pb in the study area, indicating that these metals probably have the same source. Whereas the absence of correlation of Cr with these elements indicates a separate source for this element compared to Pb, Zn, and Ni. There was also a strong relationship among these elements based on the PCA and CA classification. Based on the multivariate statistical analysis the source of pollution for the metals studied was mainly from both anthropogenic and geogenic activities. The results showed that the soil samples taken from the study area are in the low pollution category based on the individual element indices of CF and Igeo, but in the moderate pollution class based on the EF index. In addition, the evaluation based on the cumulative and multi-element indices of PI and MPI showed that 100% of samples have high pollution.
Conclusion
The present study concludes that the average values of Zn, Ni, Cr, and Pb were found to be below the guidelines set by the IEPA (Iran Environmental Protection Agency) as well as the Earth's crust values. The results indicate existing relationships among the studied variables, revealing that the heavy metals Zn, Ni, and Zn share the same source in the study area. Additionally, it was observed that the source of Cr is primarily geogenic in nature. These findings highlight the significance of utilizing multivariate statistical methods and pollution indicators in tandem, as they prove to be valuable tools for evaluating and quantitatively determining the potential pollution risk.
Soil science
F. Rahmati; S. Hojati; K. Rangzan; A. Landi
Abstract
Introduction Estimating soil properties on large scales using experimental methods requires specialized equipments and can be extremely time-consuming and expensive, especially when dealing with a high spatial sampling density. Soil Visible and Near-InfraRed (V-NIR) reflectance spectroscopy has ...
Read More
Introduction Estimating soil properties on large scales using experimental methods requires specialized equipments and can be extremely time-consuming and expensive, especially when dealing with a high spatial sampling density. Soil Visible and Near-InfraRed (V-NIR) reflectance spectroscopy has proven to be a fast, cost-effective, non-destructive, environmental-friendly, repeatable, and reproducible analytical technique. V-NIR reflectance spectroscopy has been used for more than 30 years to predict an extensive variety of soil properties like organic and inorganic carbon, nitrogen, organic carbon, moisture, texture and salinity. The objectives of this study were to estimate soil properties (carbonate calcium equivalent (CCE), electrical conductivity (EC), pH, and organic carbon (OC)) using visible near-infrared and short-wave Infrared (SWIR) reflectance spectroscopy (350-2500 nm). In this study, the best predictions of all the soil properties, model and pre-processing technique were also determined. The Partial Least Squares Regression (PLSR), Artificial Neural Network, Support Vector Machine Regression and Principal Component Regression (PCR) models were also compared to estimate soil properties.Materials and Methods A total number of 200 surface soil samples (0-10 cm) were collected from the Semirom region (51º 17' - 52º 3' E; 30º 42' - 31º 51' N), Isfahan, Iran. The samples were air dried and passed through a 2 mm sieve, and using standard procedures soil properties were determined in the laboratory. Accordingly, soil pH and the EC contents of soil samples were determined in saturated pastes and extracts, respectively. The CCE content of the soils were measured using back titration, and the OC contents of the samples were measured using Walkley-Black method. The Reflectance spectra of all samples were measured using an ASD field spectrometer. The selection of the best model was done according to the value of the Ratio of Performance to Deviation (RPD), the coefficient of determination (R2), and the Root Mean Square Eerror (RMSE).Results and Discussion Once the models were constructed using PLSR, ANN, SVMR and PCR approaches, descriptive analysis was carried out for each property, for the data measured in the laboratory. The parameters calculated for the properties were mean, coefficient of variation (CV), minimum and maximum, standard deviation and range. Coefficient of variation for the organic carbon, CCE, pH, and EC values were 21.7, 12.4, 1.34, and 28.74, respectively. Wilding (1985) proposed low, medium, and high variability for the CV values less than 15%, 15-35%, and greater than 35%, respectively. Accordingly, the organic carbon and EC of soils could be classified in the group with moderate variability. However, the calcium carbonate equivalent and pH are in the group with low variability. Since spectral data preprocessing has an effective role on improving the calibration, in order to perform spectral preprocessing, two first nodes at the first (350-400 nm) and the end (2450-2500 nm) of each spectrum were removed. In addition, two interruptions were eliminated, due to the change in the detector in the range of 900 to 1700 nm. Different preprocessing methods i.e., Standard Normal Variable (SNV) and First (FD) and Second Derivatives (SD) and Savitzky-Golay preprocessing techniques were performed on spectral data. Then, using PLSR, the cross‐validation method was used to evaluate soil properties calibration and validation. According to Stenberg (2002), for agricultural applications, The values of RPD greater than 2 indicate that the models provide precise predictions, the values of RPD between 1.5 and 2 are considered to be reasonably representative, and the values of RPD less than 1.5 indicate poor predictive performance. The results indicated the desirable capability of the PLSR method in estimating the EC (RPD > 2, R2 = 0.94), CCE (RPD > 2, R2 = 0.88), and OC (RPD > 2, R2 = 0.89). The best results of the pH (RPD > 2, R2 = 0.79) were estimated by the SVMR method. In this study the best methods of preprocessing techniques were First (FD) and Second Derivatives (SD) and Savitzky-Golay filter.Conclusion In general, based on the results of this study, VNIR spectroscopy was successful in estimating soil properties and showed its potential for substituting laboratory analyses. Moreover, spectroscopy could be considered as a simple, fast, and low-cost method in predicting soil properties. The PLSR model with First and Second derivatives and Savitzky-Golay pre-processing techniques seems to be more robust algorithm for estimating EC, OC, and CCE. The best results of the pH were estimated by the SVMR method with First and Second derivatives and Savitzky-Golay pre-processing techniques.
Alireza Owji; Ahmad Landi; Saeed Hojati
Abstract
Introduction: Soil is a key resource that contributes to the earth system functioning as a control and manages the cycles of water, biota and geochemical and as an important carbon reservoir. Soil organic matter is one of the most important factors in soil quality assessment and having relationship with ...
Read More
Introduction: Soil is a key resource that contributes to the earth system functioning as a control and manages the cycles of water, biota and geochemical and as an important carbon reservoir. Soil organic matter is one of the most important factors in soil quality assessment and having relationship with physical, chemical and biological properties of soil. Carbon sequestration in plant biomass and soils is the simplest and the most economically practical solution to reduce the risks of atmospheric carbon dioxide. Little information is available about the effects of grazing management on sequestration of carbon in Khuzestan Province pastures. Therefore, this study was conducted to evaluate the effects of grazing exclusion on the amount and forms of carbon management and carbon sequestration with economic view in some pasture soils from Peneti Plain of Izeh area and Dimeh regions of Ramhormoz in Khuzestan Province.
Materials and Methods: This study was conducted in two regions including Izeh and Ramhormoz representing different climates, vegetation and soil types of southwestern Iran. We selected two grazing treatments including ungrazed and grazed pastures in each region. The first area includes rangeland ecosystem in Izeh city between 31° 57ʹ 8ʺ to 31° 58ʹ 20ʺ N and 49° 41ʹ 11ʺ to 49° 42ʹ 33ʺ E. The region has a typical temperate continental climate, characterized by dry summers and cold winters. The mean annual rainfall is 623mm. The mean annual temperature (MAT) is 19.2 °C, and the mean monthly air temperature varies from -0.6 °C in January to 42.4 °C in July. The second area (Ramhormoz) is located between 31° 7ʹ 44ʺ to 31° 9ʹ 11ʺ N and 49° 29ʹ 13ʺ to 49° 28ʹ 52ʺ E. The mean annual rainfall is 200 mm and the mean annual temperature (MAT) is 27.2 °C, and the mean monthly air temperature varies from 4.2 °C in January to 51.6 °C in July. For each climate region, grazed and ungrazed sites were located on the same soil series with similar aspect and slope. Then, random soil samples were taken from the surface and subsurface in 15 points. After air drying the soil samples and passing them through a 2 mm sieve, physical, chemical properties of the soils were measured.
Results and Discussion: The soil of both studied regions are non-saline, calcareous, and alkaline and have relatively heavy texture. The results showed that the studied characteristics in four study areas had low and moderate coefficients of variation. This suggests that the contribution of edaphic and environmental factors to explain variation in the data is not high. Also, grazing management has increased soil organic matter of surface and subsurface soil, but despite the increase in organic matter contents of subsurface soils the difference was not statistically significant. The effect of management practices, in order to have a significant effect to lower parts of the soil, it requires a longer period management. Comparing the biomass upon non-grazing (405 and 42 gm-2 in Izeh and Ramhormoz respectively) and grazed (117 and 17 gm-2) areas, indicates a good condition of vegetation in the non-grazing and the effectiveness of enclosure in rehabilitation of pastures in the study area. However, due to more rainfall rates, the amount of biomass produced in Izeh is higher.
Conclusion: The carbon management index in the study areas, as well as the depths of the study is high, indicating recovery of soil carbon and improving its quality. Also, based on carbon sequestration in the study area, non-grazing was one of the most proper and efficient management practices, which improved soil quality. Accordingly, it seems that non-grazing practices should be considered as one of the major programs in renewable natural resources plans. On the other hand, estimation of the economic value of carbon sequestration in the pastures has been remarkable, and increased 17 and 12.7% of the value of carbon sequestration in Izeh and Ramhormoz regions under the management of the exclusion. Therefore, the management of rangelands should be directed to allow for their ecologic performance and capacity considering the environmental economy of rangelands so that in broad terms, the justification for the enhancement and maintenance of the economic equilibrium can be viewed as a guaranty of implementing the range managements resulting in sustained development.
Atefeh Amouzadeh; Ahmad Landi; Saeid Hojati
Abstract
Introduction: Adsorption plays a determinant role in the mobility and bioavailability of potassium in soils. Adsorption decreases the solution phase concentration, resulting in very low diffusive fluxes and small transfer by mass flow of soil solution. The K fixation in soils which occurs bytransformation ...
Read More
Introduction: Adsorption plays a determinant role in the mobility and bioavailability of potassium in soils. Adsorption decreases the solution phase concentration, resulting in very low diffusive fluxes and small transfer by mass flow of soil solution. The K fixation in soils which occurs bytransformation of available forms into unavailable ones, influences the effectiveness of fertilization in soil-plant system. Thus, understanding the mechanism that involves adsorption of K in soil is important because soils may contain widely variable pools of K which are potentially mobilized by chemical weathering of soil minerals. The clay minerals types, pH, soil organic matter (SOM), hydroxide aluminum, soil moisture status, cation exchange capacity (CEC), fertilization and tillage system are the major factors affecting the equilibrium. Adsorption sites for K by organic matter are similar to planar surfaces like kaolinite clays. Soil pH has also significant effect on K adsorption as CEC increases with increase in pH. Knowledge about the variation in behavior of K adsorption among different soils is necessary to predict the fate of applied K fertilizers in soils and to make precise K fertilizer recommendations. The objective of this study was to evaluate the effect of soil organic matter and pH on the adsorption of K by three calcareous soils of Khuzestan Province, at southwest of Iran, having different mineralogical properties.
Materials and Methods: Three soil samples (Izeh, Shavour, Ahvaz) were collected from different areas of Khuzestan Province and their physicochemical and mineralogical properties were determined. Potassium adsorption experiments were performed by pouring 2g of each air-dried and Ca+2-saturated soils, with (control) and without (H2O2) organic matter into polyethylene tubes and adding 20 ml of the stock solution of KCl with initial concentrations of 10, 20, 50, 100 and 200 mg l-1 at pH=6 and pH=7.5. The tubes were shaken at 150 rpm for 24h, as the equilibrium time, at 25 ˚C. The pH of the soils was adjusted by application of 0.1 N HCl and NaOH solutions every 4 hours during the shaking period. The soil samples dissolved in potassium solutions (1:10w/v) were centrifuged at 3000 rpm for 15min. Then, the supernatant was filtered through filter paper (Wathman filters No.42) and the potassium concentrations in the supernatants were determined by flame photometer method. The amount of sorbed potassium in soils was calculated with the equation:
(1)
where q (mg kg−1) is the amount of adsorbed K onto soil particles, Co and Ce (mg l−1) are the initial and equilibrium concentration of the potassium in solution, respectively; V is the solution volume (ml), and M is the weight of air-dried soil (kg). The data were then fitted by linear Freundlich and Langmuir models.
Results and discussion: Among the important geochemical properties of soils for the adsorption of cations are the contents of organic matter, pH, clay contents, and cation exchange capacity (CEC). Accordingly, organic matter, pH, clay and cation exchange capacity contents were 3.09%, 7.62, 20.5% and 16.7 cmol (+) /kg for Izeh, 0.79%, 7.52, 50.5% and 11.31cmol (+) / kg for Shavoor soil and 0.95%, 7.15, 20% and 7.39 cmol (+) / kg for Ahvaz soils. The mineralogical experiments showed that the order of dominant clay minerals in the soils are Vermiculite > Illite > Chlorite > in Izeh, Illite >Vermiculite > Chlorite in Shavoor and Vermiculite > Chlorite >Illite in Ahvaz soils. The results indicated that potassium sorption isotherms in the soils are L-type and both Freundlich and Langmuir equations are able (r2>0.9) to explain the results of the potassium adsorption in the soils studied. Potassium sorption capacity of Freundlich equation (kf) and maximum sorption capacity of potassium (a) in Langmuir equation were obtained between 12.47 to 32.59 (l g-1) and 7.50 to 22.13 mg kg-1, respectively at control and 22.34 to 41.16 (l g-1) and 17.81 to 28.59 mg kg-1, respectively at H2O2 treatments. The distribution coefficient is used to characterize the mobility of cations in soil; low Kd values imply that most of the cation remains in solution, and high Kd values indicate that the cation has great affinity for the surface of adsorbents. Mean content of potassium distribution coefficient at Shavoor soil was significantly higher than other soils which can be attributed to the high content of clay minerals such as illite. Moreover, the results indicated that by increasing the pH values of the soils from 6 to 7.5 the adsorption efficiency of potassium in Izeh, Shavoor and Ahvaz soils increased to 38.3, 8.3, and 26.1%, respectively.
Conclusion: Potassium adsorption in soil is affected by content and type of clay minerals. so that the soils with high illite content have more capacity for sorption and fixation of potassium in soil. On the other hand, organic matter removal from soils increased the potassium sorption by mineral components (especially clay minerals) of the soil studied. Moreover, with an increase in soil pH the potassium sorption increased significantly.
R. Beitlefteh; A. Landi; S. Hojati; Gh. Sayyad
Abstract
Introduction: Recently, air pollution due to the occurrence of dust storms is one of the worst environmental problems in Western and Southwestern Iran, especially the Khuzestan Province (12, 13). According to the reports of the Meteorological Organization of Iran the average number of dusty days in the ...
Read More
Introduction: Recently, air pollution due to the occurrence of dust storms is one of the worst environmental problems in Western and Southwestern Iran, especially the Khuzestan Province (12, 13). According to the reports of the Meteorological Organization of Iran the average number of dusty days in the cities of Ahvaz and Abadan in the Khuzestan Province reaches 68 and 76 days each year, respectively (6). Previous studies have shown that the yearly damage costs of wind erosion and occurrence of dust storms in the Khuzestan Province reach about 30 Billion Rials (5). However, very few studies have been conducted on the characterization of dust particles and also the identification of their origins in Iran, especially the Khuzestan Province. Hojati et al. (10) reported that dust deposition rate, mean particle diameter, and concentration of soluble ions in samples taken from Isfahan and Chaharmahal and Bakhtiari Province decrease with altitude, with a significantly lower gradient in periods with dust storms. They reported three factors that control the rate and characteristics of dust deposited across the study transect: 1) climatic conditions at the deposition sites, 2) distance from the dust source, and 3) differences between local and transboundary sources of dust.Therefore, this study was conducted to investigate the effects of dust storms on deposition rate, mineralogy and size distribution patterns of dust particles from twelve localities around the Houralazim lagoon.
Materials and Methods: Dust samples were collected monthly during a 6 month experiment from August 2011 to February 2012. In order to differentiate between the contribution of dust production by local soils and other sources, surface soils were also sampled from the vicinity of the dust sampling sites. The collection trays were made of a glass surface (100 × 100 cm) covered with a 2 mm-sized PVC mesh on the top to form a rough area for trapping the saltating particles (Fig. 2). Dust samples were collected by scraping materials adhered to the glass trays using a spatula. All the trays were wet cleaned before the next collection. The collected dust and soil samples were examined for their grain size distribution using a Malvern Hydro 2000g laser particle size analyzer, as well as their mineral compositions by a Philips PW1840 X-ray diffractometer and a LEO 906 E transmission electron microscope (TEM).
Results and Discussion: The results showed that wind speed and direction patterns during the periods with dust storms and those without dust storms were different. Accordingly, in periods with dust storms (3, 5 and 6) the contribution of winds with speeds greater than 11.1 m/sec, especially from the Northwest direction, increased when compared with those from the periods without dust storms (1, 2 and 4). Besides, the direction of prevailing winds in periods without dust storms were mainly from the West and the Northwest. However, in periods with dust storms East-directed winds were also observed (Fig. 3). These show that the source areas of dust particles in these periods are probably different. The results also illustrated that the average amount of deposited particles in the periods with dust storms (12.5 g m-2 month-1) was considerably more than that of the periods without dust storms (7.5 g m-2 month-1) (Figs. 4 and 5). The difference in dust deposition rate between periods having dust storms and those without dust storms seems to be due to dust input from a source outside the study area. Particle size distribution analysis showed that dust particles collected from the study area in both periods (with and without dust storms) are mainly silt-sized particles. This fraction contributes to 60 to 76 % of the particles collected from periods without dust storms and 66 to 82 % of particles affected by dust storms (Table 2). The results also imply that in both periods (with and without dust storms), dust particles collected from the study area had a bimodal distribution pattern which suggests mixing of settled particles from different sources and/or deposition processes (Fig. 6). Mineralogical composition of dust particles were collected from both periods (with and without dust storms) and those from the soils contained quartz, calcite, feldspar, halite, dolomite and palygorskite (Figs. 7 and 8). Moreover, the TEM images of dust particles collected in periods with dust storms showed higher amounts of palygorskite than in periods without dust storms (Fig. 9).
Conclusion: The similarity in the physical properties of local soils and deposited particles of the periods with and without dust storms implies that the contribution of local soils and sediments in producing dust particles is high. However, it seems that in periods with dust storms the contribution of a transboundary origin such as Iraqi arid lands in producing dust particles increases.