Showing 67 results for Mica
E. Mirzakhani, H. Motaghian, A. Hosseinpur,
Volume 25, Issue 4 (12-2021)
Abstract
Pollution of the environment by heavy metals, especially soil pollution with cadmium (Cd), is one of the most important environmental problems. Also, salinization of soils due to a decrease in irrigation water quality reduces plants growth. To investigate the effect of sugarcane bagasse biochars and salinity on Cd available and Cd fractions in a contaminated soil (15 mg kg-1 Cd), an experimental factorial design in a completely randomized design including (1) biochar factor with control, 1% (w/w) bagasse, 1% (w/w) biochar 400 °C and 1% (w/w) biochar 600 °C, and (2) salinity factor with control, 20, and 40 mmol kg-1 as sodium chloride were performed in 3 replications. The amount of available Cd was determined by the DTPA-TEA method and the Cd fractions were determined by Tessier et al. (1979). The results showed that biochar and salinity had no significant effect on soil pH (P > 0.05) but increased soil EC (P < 0.05). Interaction of biochar and salinity was not significant (P > 0.05) on available Cd and Cd fractions. Biochar application reduced Cd -DTPA-TEA (P < 0.05), whereas salinity increased Cd -DTPA-TEA (P < 0.05). Application of biochar prepared at 600 °C reduced (P < 0.05) exchangeable Cd (23.8%) and increased (P < 0.05) Cd associated with iron and manganese oxides (25.2%) and residual (15.6%) compared to the control. The results showed that salinity had no significant effect on the Cd fractions (P > 0.05) and soil treated with sugarcane bagasse biochar can reduce Cd available due to changing the Cd distribution from unstable forms to stable forms.
A. Balvaieh, L. Gholami, F. Shokrian, A, Kavian,
Volume 26, Issue 4 (12-2022)
Abstract
Changes in nutrient concentrations of soil can specify optimal management of manure and prevent environmental and water resources pollution. The present study was conducted with the objective of changing macronutrients concentrations of Nitrogen, Phosphorus, and Potassium with amendments application of polyvinyl acetate, bean residual, and a combination of polyvinyl acetate + bean residual for time periods of one, two, and four months. The results showed that the application of soil amendments had various effects on changing Nitrogen, Phosphorus, and Potassium. The maximum amount of Nitrogen related to the treatment of bean residual at the time period of four months before simulation (with a rate of 44.62 percent) and minimum amount of nitrogen related to Polyvinyl acetate treatment at the time period of one month (with a rate of -1.92 percent). The minimum rate of Phosphorus was measured at the treatment of bean residual at the time period of one month before simulation (with a rate of 0.95 percent). The maximum amount of Potassium related to the treatment of Polyvinyl acetate at the time period of four months before simulation (with a rate of 189.35 percent) and the minimum amount of Potassium related to the combination of bean residual + Polyvinyl acetate at the time period of one month after simulation (with a rate of 40.66 percent). Therefore, the application of amendments has various effects on changing soil macronutrients at different time periods.
D. Khatibi Roudbarsara, A. Khaledi Darvishan, J. Alavi,
Volume 27, Issue 2 (9-2023)
Abstract
Soil erosion followed by sediment production is the most important phenomenon that causes soil and environment degradation in many areas and is increasing. Sediment fingerprinting is a method to identify sediment sources and determine the contribution of each source to sediment production. The present research was carried out to evaluate the relative erosion sensitivity of lithological units and to determine the contribution of each unit in bed sediment production using geochemical properties in the Vaz River located in Mazandaran province. The 33 soil samples were taken from the whole watershed and one sediment sample at the outlet of the watershed. Then, five tracers of B, Al, Sc, Mo, and Sn were selected as the optimal combination using three statistical tests range tests, Kruskal-Wallis, and discriminant function analysis. Finally, using optimal tracers and a combined multivariate model, the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were obtained using FingerPro statistical package and R software. The results showed that the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were 24.23, 50.77, 15.62, and 9.36%, respectively. Then, the specific contribution of each sensitivity class was also calculated to remove the effect of area on the results. The Qal lithological unit including the Quaternary sediments in the river bed and banks with very high sensitivity to erosion (A) and a specific contribution of 0.0807 % per hectare had the maximum contribution in bed sediment production in Vaz River.
H.r. Owliaie, E. Adhami, M. Najafi Ghiri,
Volume 27, Issue 3 (12-2023)
Abstract
Soil resources are important components of the ecosystem, and therefore, their quality should be considered. One of the important factors affecting the quality of soils is land use change. The present study was conducted to investigate the effects of land use change and deforestation on some soil fertility and biological characteristics in the forest area of the Yasouj region. In this area, four land uses of dense forest, sparse forest, deforested (degraded) lands, and rainfed agriculture were randomly sampled from two slope classes. In each land use 10 soil surface samples were taken. Fifteen soil fertility and biological characteristics were measured using routine methods. The results showed that dense forest and deforested (degraded) lands had the best and worst conditions, respectively, in terms of the measured parameters. Among the measured characteristics, the values of alkaline phosphate, exhaled respiration, nitrogen, basal respiration, acid phosphatase, manganese, and zinc showed the greatest decrease respectively, and the values of phosphorus and potassium exhibited the least decrease, as a result of land use change from dense forest to degraded lands. The findings showed that the conversion of ecosystems such as forests to agricultural lands or deforestation has led to a severe decrease in the fertility and biological indicators of soil quality. Therefore, the protection programs of these areas should be more considered.
A. Barikloo, S. Rezapour, P. Alamdari, R. Taghizadeh Mehrjardi,
Volume 27, Issue 4 (12-2023)
Abstract
Soil quality is one of the most crucial factors determining crop productivity and production stability. The soil's physical, chemical, biological, and ecological characteristics affect its quality. Numerous researchers have concentrated the evaluation on a small number of soil quality indicators because measuring all soil quality indicators would be time-consuming and expensive. This study looked at the spatial autocorrelation of soil quality in the southwest areas of the Urmia Plain to establish the minimal data set for quantitative assessment. To accomplish this, 120 composite soil samples were collected from a depth of 0 to 60 cm, and the soil quality index was then calculated using the IQI method in 4 modes: Total-Linear (IQIwL-TDS), Total-Nonlinear (IQIwNL-TDS), Minimum-Linear (IQIwL-MDS), and Minimum nonlinearity (IQIwNL-MDS). 22 physical and chemical characteristics were used to choose the data set. The characteristics of sand percentage, sodium absorption ratio, cation exchange capacity, Available phosphorus, active calcium carbonate, and nickel concentration were chosen as the minimum data set (MDS) using the decomposition method into principal components. The linear IQIMDS mode produced the greatest soil quality index result, whereas the non-linear IQIMDS mode produced the lowest. The non-linear mode of the IQI index has a greater correlation coefficient (R2=0.85) than the linear mode of the IQI index (R2=0.73), according to an analysis of the linear and non-linear correlation coefficient between the soil quality index with the total category and minimum data. The findings of computing the global Moran's index for study sets of IQI soil quality index data revealed that the soil quality data are not independent of each other and are spatially autocorrelated, distributed in clusters, and have spatial autocorrelation. Getis-ord GI statistics indicated that the eastern and southeastern parts of the research region comprise clusters with poor soil quality, salt marshes produced by Lake Urmia's drying up, and surrounding arid plains.
J. Ghaneiardakani, S.a. Mazhari, F. Ayati,
Volume 29, Issue 2 (7-2025)
Abstract
This study investigates the impact of agricultural activities on the soils of southern Mehriz by analyzing their geochemical composition and comparing the physicochemical properties of pistachio orchard soils (agricultural soils) with those of undisturbed natural soils. The results indicate that agricultural practices have led to an increase in Total Organic Carbon (TOC), averaging 1.5%, and a reduction in soil acidity. Additionally, phosphorus concentrations have risen in agricultural soils. These soils also exhibit enrichment in elements such as cadmium (Cd), antimony (Sb), chromium (Cr), nickel (Ni), lead (Pb), scandium (Sc), and rare earth elements (REE) compared to natural soils, with a more homogenized REE distribution pattern. Although the concentrations of these trace elements remain within national environmental standards and below critical thresholds, the study highlights a significant increase in the bioavailability of heavy metals due to agricultural activity. This finding underscores a potential environmental risk if such changes are not properly managed in the future.
Fatemeh Jafarian, Khoshnaz Payandeh, Ahad Nazarpour, Ali Gholami, Kamran Mohsenifar,
Volume 30, Issue 2 (7-2026)
Abstract
The steel industry plays an important role in the release of toxic pollutants, including heavy metals, into the environment. The present descriptive-applied study was conducted in 2022 to identify the sources of heavy metal emissions in surface soils in the vicinity of a steel industry using positive matrix factor and chemical mass balance models. Soil samples (50 samples) were systematically collected from four areas within the steel plant, and a control area of 15 km was established. Five main sources, including the earth's crust (factor 1), vehicles (factor 2), steel industry (factor 3), biomass (factor 4), and other sources (factor 5), were identified as the main factors of heavy metals in the positive matrix factor model. Cobalt, nickel, and zinc had the highest mean concentrations with values of 14.5, 1.21, and 0.92mg kg-1, respectively. Cadmium and Lead showed the lowest concentrations with values of 0.02 and 0.10 mg kg-1 in samples inside and outside the Khuzestan Steel Company area, respectively. Comparing the contribution of different sources in the release of heavy metals in the identified factors showed that the steel industry, other sources, earth's crust, vehicles, and biomass accounted for 24, 23, 19, 18, and 16 percent in the positive matrix factor model and 23, 22, 20, 18, and 17 percent in the chemical mass balance model, respectively. The positive matrix factor and chemical mass balance models showed that there was a high level of soil contamination with heavy metals in the vicinity of the Khuzestan Steel Company in Ahvaz city.
