Sanitary landfills, created for the disposal of solid waste, usually are developed into parks after they are closed. However, soil amelioration with organic matter is usually needed to restore fertility and promote revegetation. Sewage sludge creates a massive waste disposal problem. The use of composted sewage sludge (biosolid) as a soil conditioner might restore the soil fertility at landfill sites and simultaneously alleviate the need for sewage sludge disposal. We applied biosolid to waste landfill soil and evaluated its effects on soil properties and tree growth in a field experiment. Biosolid improved soil characteristics including moisture, organic matter, and nitrogen content and also increased tree height and diameter at breast height.Physiological measures, such as chlorophyll content and photosynthetic rate, showed positive responses in trees grown in biosolid treatments. Heavy metal concentrations in soil and tree leaves after applying compost did not differ from concentrations measured at control sites. Therefore, we conclude that the use of biosolid in waste landfills would be an efficient, environmentally beneficial, and cost-effective method to restore the conditions of landfill soil for plants.

2Background and Objective: Heavy metals are regarded as serious contaminants due to their toxicity, persistence in natural conditions, and ability to enter and accumulate (bioaccumulation and biomagnification) in food chains. The aim of this study was to investigate the concentrations of the heavy metals Pb, Cd, Cu, Zn, Cr, Fe and Ni in surface agricultural soils of the Miandoab landfill area. Materials and Methods: In this study, 57 soil samples were collected from a depth of 0-20 cm. After preparing and digesting in the laboratory, the samples were analyzed using a inductively coupled plasma spectrometer (ICP-OES). The Ecological Risk Potential Index (EPRI), Earth Accumulation Index (Igeo), Principal Components Test (PCA) Pearson's Correlation, Cluster Analysis, and One-T-test were utilized. Statistical processing was conducted using SPSS software. Results: According to the results of the single T-test, the average concentrations of Pb, Cd, Cu, Zn, Cr, Ni did not significantly differ from their background concentration in the soil (p≥0. 05). A significant difference was pbserved only for Fe (p<0. 05), indicating a geological origin for this element. The EPRI was within the low-risk range, with an average value of 46. 95. PCA revealed that the first factor was positively associated with Cr, Pb and Fe,the second factor with Zn and Cu,and the third factor with Cd. Cluster analysis showed that Fe was predominantly influenced by natural resources. According to the land accumulation index, all metals, except Cu, were classified non-polluted or slightly polluted at stations 2 and 4. Conclusion: The origin of elements is related to both natural and human factors. Specifically, Cr, Pb and Cd are more likely to originate from man-made sources, while Fe primarily comes from natural sources. The decrease in the concentration of metals can be attributed to continuous and annual ploughing, inactivity of the landfill, biological absorption by crops, soil leaching and transporting to lower depths

Soil salinity is a limiting factor for plant growth and a serious cause of land degradation. Field sampling and statistical analysis for estimating soil salinity is expensive and time consuming. Estimating soil salinity by spatial statistical models and Geographic Information System (GIS) is recommended, because it saves labor and time. This study was conducted to evaluate the performance of spatial statistics with ordinary least square (OLS) incorporation with LANDSAT data to predict soil salinity. The electrical conductivity (EC) of 236 soil samples were collected from Garmsar plain at south east Tehran, Iran and were measured and correlated to 27 variables derived from LANDSAT images, including vegetation indices, salinity indices, bands 1 to 7, principal component analysis and tasseled cap indices. Using factor analysis and similarity index, these variables were divided into three components. Furthermore, two models for soil salinity estimation were derived, using the best correlation correlation coefficient (0.58 and 0.60) method. Simultaneously, soil salinity map was produced in ArcGIS by spatial statistics model OLS followed by derivation of the error map, calculated using Moran's index. The error map indicated that the spatial statistics models are superior to classic statistics methods, due to high accuracy in estimation and the fact that it doesn' t require exchange information between different software programs.

Background: Soil salinization is a world-wide land degradation process in arid and semi-arid regions that leads to sever economic and social consequences.Materials and Methods: We analyzed soil salinity by two statistical linear (multiple linear regression) and non-linear (artificial neural network) models using Landsat OLI data in Agh-Ghala plain located in north east of Iran. In situ soil electrical conductivity (EC) of 156 TOPSOIL samples (depth of 0-15cm) was also determined. A Pearson correlation between 26 spectral indices derived from Landsat OLI data and in situ measured ECs was used to apply efficient indices in assessing soil salinity. The best correlated indices such as blue, green and red bands, intensity indices (Int1, Int2), soil salinity indices (Si1, Si2, Si3, Si11, Aster-Si), vegetation Indices (NDVI, DVI, RVI, SAVI), greenness and wetness indices were used to develop two models.Results: Comparison between two estimation models showed that the performance of ANN model (R2=0.964 and RMSE=2.237) was more reliable than that of MLR model (R2=0.506 and RMSE=9.674) in monitoring and predicting soil salinity. Out of the total area, 66% and 55.8% was identified as non-saline, slightly and very slightly saline for ANN and MLR models, respectively.Conclusions: This shows that remote sensing data can be effectively used to model and map spatial variations of soil salinity.

This study was conducted to evaluate the soil physical quality (SPQ) indices of TOPSOIL and subsoil of wheat and sunflower fields in Urmia plain. Principal component analysis (PCA) was used to distinguish the effect of soil layer and cultivation type on SPQ. Soil samplings and measurements were done in two layers (TOPSOIL and subsoil) of 30 agricultural fields (15 wheat fields and 15 sunflower fields). Soil water retention and penetration resistance curves of undisturbed samples were determined using sand box and pressure plate, and micro-penetrometer, respectively. Then, least limiting water range (LLWR), integral water capacity (IWC), and Dexter’ s index of soil physical quality (Svalue) were calculated. There were significant differences (P<0. 05) in the mean values of physical quality indices between the TOPSOIL and subsoil. The relative bulk density (RBD) values of subsoil were bigger than TOPSOIL. Also, the IWC, LLWR, and S values of subsoil were much smaller than those of TOPSOIL, indicating poor physical quality of subsoil layer in the studied fields. This might be related to conventional tillage with heavy machinery, especially under high soil moisture conditions in last decades, which induced some compaction effects in the subsoil. These findings recommend improving of tillage systems and continuous monitoring of cultivation effects on SPQ in the studied area. Evaluating the SPQ indices of wheat and sunflower fields, using the means comparison and PCA, showed that wheat fields had better soil physical quality compared to sunflower fields. The difference of root systems and more human trafficking in the sunflower fields could be the main reasons of lower soil physical quality in sunflower cultivation compared to wheat cultivation.

Background and Objective: Due to the shortage of freshwater for irrigation, wastewater has been used in agricultural irrigation as an important supplement and alternative water resources in recent decades. Irrigation of fields with wastewater can cause potential contamination with heavy metals to soil crops and groundwater, therefore pose a threat to human health and food safety. The aim of this research was to evaluate the effect of irrigation with untreated municipal wastewater on the accumulation of cadmium lead (Pb), (Cd), copper (Cu) and Zinc (Zn) in TOPSOIL and subsoil and top soil properties. Method: In the present study in order to collection of TOPSOIL (0-20 cm) and subsoil (0-40 cm) samples from south of the Borujerd city, 13 fields irrigated with untreated wastewater and 7 fields irrigated with well water were selected with same soil texture. Soil samples were analyzed by the standard methods for Pb, Cd, Cu, Zn, pH, electrical conductivity (EC), organic matter (OM). Findings: Findings indicated that untreated wastewater irrigated soil contained higher concentrations of all heavy metals in TOPSOIL (with the exception of Cu) and in subsoil, compared to well water irrigated soil. Trend of depth variations of metals in irrigated soil followed this form: 1-With wastewater: Pb and Cu in subsoil>TOPSOIL; Cd and Zn in TOPSOIL > subsoil and 2-With well water: Pb and Cu in TOPSOIL > subsoil; Cd and Zn in subsoil > TOPSOIL. Discussion and Conclusion: It seems that light soil texture has been resulted to transport of the metals to deeper soil layers. Overall, the concentrations of Pb, Cu, and Zn were lower than the FAO/WHO standards in soil, while Cd higher than this. Thus, in order to ensure food safety and use of wastewater for irrigation, continuous monitoring and pollution control is required. Besides, if treatment of wastewater is done appropriately, accumulation of heavy metals in soils and crops will occur less.

Introduction: Today, the contamination caused by rapid development of industries has attracted the attention of scientific and environmental communities. This study was conducted to investigate the concentration and distribution of heavy metals in the TOPSOIL of industrial areas in Ardakan city. Methods: In this applied research, sampling of TOPSOIL (0-5 cm depth) was performed using five linear transects in an area of 20000 hectares. Concentrations of As, Cd, Cr, Ni, Mo, Pb, V, and Zn were measured in 45 samples based on ICP-OES method. Then, indices of Contamination Level of Heavy Metal ( ), Potential Ecological Risk of Heavy Metals ( ), and Total Potential Ecological Risk (RI) were calculated. Moreover, Pearson’ s correlation was used to assess the relationship between heavy metal’ s concentrations. Results: Results indicated that the mean concentrations of As, Cd, Cr, Mo, Ni, Pb, V, and Zn were 9. 85, 0. 31, 35. 33, 1. 001, 43. 28, 18. 51, 44. 8, and 78. 3 (mg/kg) in TOPSOIL of studied area, respectively. Maximum concentrations of all heavy metals were found in samples collected from downstream and near the major industries except for Mo and Ni. and RI indices also showed a significant increase in downstream. Strong correlations were found between Cr-Ni, Cd-Zn, and As-Cr, which indicate that these metals probably have the same source. Conclusion: The ecological risk of the whole area was low. However, the increase of ecological risk in the surrounding and downstream of steel, pelletizing, as well as tile and ceramic factories indicated the dominant role of prevailing wind in the distribution and spread of pollution. This fact indicates the necessity of attention to the site selection studies of these industries. Furthermore, the results indicated the necessity of taking preventive measures such as phytoremediation in the downstream of the industrial areas in this region.

Abstract Earthworms are as the most important soil forest ecosystem engineers. Present research was considered to study the reaction of earthworm group's (epigeic, anecic and endogeic) in TOPSOIL to variability of ecological characters (litter C, litter N, litter C/N, soil C, soil N, soil C/N, and pH and moisture) in Noor Forest Park. Litter and soil samples were taken, with microplots of 30×30×15 cm, under tree canopy of Alnus glotinusa, Ulmus glabra, Popolus caspica and Parrotia persica species. Earthworms were collected during soil sampling, washed in water and weighed. Biomass was defined as the weight of the worms after drying at the labratory. Results showed that the soil under Alnus glotinusa has high abundance and biomass of epigeic (0. 3 n/m2 amd 3 g/m2 respectively) and endogeic (1. 4 n/m2 and 14 mg/m2 respectively). Whereas any epigeic and endogeic were not found under Parrotia persica. The least density and biomass (0. 5 n/m2 and 0. 5 mg/m2 respectively) of anecic earhworms were recorded under Parrotia persica. The results of this research are indicating of positive role of Alnus glotinusa species, related to high litter N, on biological index of soil quality that can be considered to restore of degraded parts in the northern Iran.

Floods deposit huge amounts of suspended and dissolve materials of different sources on alluvial fans and therefore change soil characteristics such as permeability over the time. This research was carried out in Chandab-Varamin basin to assess the effect of floodwater spreading practices on TOPSOIL infiltration rate using Double Rings. 10 cm of TOPSOIL layer was collected from the profile and analyzed in the laboratory. Results showed that fine sediments (silt and clay) have been deposited in soil surface layer. Meanwhile, the permeability rate in the first row was measured control about 50 percent, in the third row of about 35 percent and about 42 percent of total area has decreased compared to the control area. Also, infiltration rate was decreased about 73 percent in the first band, 31 percent in the third band and about 52 percent in the whole area compared to the control area. Comparison of clay amount in control and treatment areas showed that their accumulation on soil surface changes negatively, soil physical characteristics including soil texture and makes soil more crusty which gradually decrease soil infiltration in floodwater spreading site.