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Volume 11, Issue 42 (winter 2008)
Phytoremediation is a new technology that employs plants to remediate contaminated soils. This method compared to those that involve the use of large scale energy consuming equipments is an inexpensive method. Phytoremediation models are useful tools to further understanding the governing processes and also to manage the contaminated soils. A thorough literature review indicates that very few models have been developed for phytoremediation due to the complexity of the phenomena. The objective of this study was to develop a simple model for phytoremediation of lead and cadmium. A new formulation of phytoremediation was established based on soil and plant responses to heavy metal pollution. A large quantity of a sandy loam soil was thoroughly mixed to ensure homogeneous different concentration levels by lead and cadmium. These contaminated soils were transferred to some plastic pots. Land Cress (Barbarea verna) and Spinach (Spinacia oleracea L.) seeds were germinated in pots containing 8 kg of contaminated soil. Plants were harvested at five time intervals. The concentrations of Pb and Cd in the plant and soil samples were digested by wet oxidation and 4 M Nitric acid digestion methods, respectively, and were determined by flame and graphite furnace atomic absorption spectrometry methods. Proposed models then were calibrated using the collected data and validated quantitatively. The results indicated that the soil adsorption isotherms followed a linear form for both Pb and Cd concentrations. The results also indicated that the phytoremediation rate of Pb by Land Cress and Spinach are first-order function of Pb concentration in soil. In contrast, a zero-order function of soil Cd contaminations was obtained. Combining these two results of soil and plant responses to Pb and Cd pollution, a simple model with reasonable performance was derived to predict the time needed for remediation of soil Pb (R2 > 0.98). However, in the case of Cd, the derived models appeared to be useful to make only some overall estimations of the remediation (R2≈0.70).
Volume 12, Issue 44 (summer 2008)
Canola (Brassica napus L.) in response to salinity represents various resistances with respect to its phonologic stages. Most plants such as Canola are resistant at germination stage. However, at seedling or earlier growth stages, plants become more sensitive to salinity but their tolerance increases with age. Salt tolerance of various plants has been extensively studied however, the results have either been qualitative or expressed as average values over root zone salinity for the whole growth season. Thus, developing appropriate models for quantitative characterization of plant response to salinity at different growth stages is essential. Canola which is considered as high economic value plant was selected for this study. Two productive stages for canola are recognized as flowering and ripening. To determine the effect of salinity on canola at vegetative growth stages, a greenhouse experiment was conducted on a natural saline loamy sand soil, using salinity treatment including one non-saline water (tap water) and 8 saline waters of 3 to 17 dS.m-1. The canola plants were irrigated with tap water before the desired stage and then salinity treatments were imposed. The Maas and Hoffman (1977), van Genuchten and Hoffman (1984), Dirksen et al., (1993), and Homaee et al., (2002b) models were used to predict relative transpiration (Ta/Tp ) and relative yield ( Y/Ym) as a function of soil salinity. The maximum error (ME), root mean square error (RMSE), coefficient of determination (CD), modeling efficiency (EF) and coefficient of residual mass (CRM) statistics were calculated to compare the models and their efficiencies. The results indicated that the van Genuchten and Hoffman (1984) model provides best prediction at flowering stage. However the Homaee et al. (2002b) model offers better prediction at ripening growth stage.
Volume 12, Issue 46 (1-2009)
Modeling plant response to salinity and nitrogen deficiency is very important for estimating optimum yield in arid and semi-arid regions. For this purpose, the models of Leibig-Sprengel (LS) and Mitscherlich-Baule (MB) originally proposed to explain plant response to nutrients only were modified to evaluate plant yield response to combined nitrogen and salinity stress conditions. Afterwards, in order to model canola (Brassica napus L.) response to combined salinity and nitrogen stress, an experiment was designed with different nitrogen and salinity levels. The water salinity treatments consisted of non-saline water, 3, 6, 9 and 12 dS m-1. The nitrogen treatments were 0, 75, 150 and 300 mg kg soil-1 added as ammonium nitrate. The results indicated that both modified models can satisfactorily predict canola yield. However, the modified MB model (R2=0.94) provided better estimation than the modified LS model (R2=0.87). The calculated statistics including Maximum Error, Root Mean Square Error, Modeling Efficiency, Coefficient of Determination and Coefficient of Residual Mass for the modified models indicated that the estimated relative grain yield for soil nitrogen, salinity and each rate of soil nitrogen in salinity levels by modified MB model compared with those by modified LS model is closer to the measured relative yield. Therefore, the use of modified MB model for estimating canola relative grain yield in salinity and nitrogen stresses is recommended. Using modified LS model showed that the salinity threshold value changes with the applied nitrogen. In this case, by application of each 75 mgN kg-1 soil, the salinity threshold value decreased 4 dS m-1 in saline conditions. Application of nitrogen decreased chloride concentration in grains under saline conditions. Nitrogen uptake also augmented with increasing canola transpiration, because nitrogen was carried over from soil to the uptake sites mainly by mass flow.
Volume 14, Issue 52 (sumer 2010)
Phytoremediation is a new, in-situ and emerging remediation technology for contaminated soils. This technology, compared to other methods, is a sustainable, natural, relatively cheap and applicable to large scale area. Modeling phytoremediation provides quantitative insight for the governing process as well as for managers to assess the remediated sites. The objective of this study was to introduce a macroscopic phytoremediation model for Ni and Cd- polluted soils. The proposed model assumes that relative transpiration reduction function can resemble total soilNi and Cd concentrations. Combining the related functions of soil and plant responses to soil Ni and Cd concentrations, the phytoremediation rate of Ni and Cd was predicted. In order to test the proposed model, large quantities of soil were thoroughly polluted with Ni and Cd. Upland Cress (Lepidum sativum) and Ornamental Kale (Brassica olerace var. Viridis) seeds were then germinated in the contaminated soils. The experimental pots were irrigated with fresh water to reach field capacity. Upland Cress and Ornamental Kale were harvested three and four times, respectively. At each harvest, relative transpiration, Ni and Cd contents of soil samples and plants were measured. Comparison of the maximum error, root mean square error, coefficient of determination, modeling efficiency and coefficient of residual mass indicated that the non-threshold non-linear model provide high efficiency to predict relative transpiration for Upland Cress and Ornamental Kale, respectively. The results also indicated that the proposed macroscopic model can well predict the phytoemediation rate of the Ni and Cd by Upland Cress (R2>0.83) and Ni by Ornamental Kale (R2=0.78).
Volume 14, Issue 54 (winter 2011)
In this study, the effects of enhancing synthetic chelators (HEDTA, EGTA) and low molecular weight organic acids (LMWOA) such as citric acid were compared on cadmium (Cd) solution in soils that were artificially contaminated. Also Cd phytoextraction capability by radish (Raphanus Sativus L.) was studied. The experiment was laid out in a randomized complete factorial design where each treatment was replicated three times. Concentration treatments of cadmium using CdCl2 were 0(control), 5, 20, 60 and 100 mg Cd kg-1. After complete growth of plants, 6, 20 and 20 mMkg-1 soil HEDTA, EGTA and Citric Acid were added per pot, keeping a control without any chelator application. In order to determine cadmium concentration ten days after adding chelates, samples were taken from the plants and soil of pots. The results showed that in all treatments the concentration of soluble Cd in soil was higher than the control. Also the results showed that synthetic chelators as compared with LMWOA (Citric Acid) have increased the solution remarkably. Among the other chelates, HEDTA had significant effects on Cd solution. In the current study, Cd concentration in shoot and root of (Raphanus Sativus L.) was increased with enhancement of Cd concentration in soil. Cd concentrations in shoots of radish were higher than those in roots. This could refer to higher bioavailability and solubility of Cd. In the current study, in all the treatments with HEDTA Cd concentrations in shoot and root of (Raphanus Sativus L.) were increased as compared with other chelates..
Volume 15, Issue 56 (sumer 2011)
Soil bulk density measurements are often required as an input parameter for models that predict soil processes. Nonparametric approaches are being used in various fields to estimate continuous variables. One type of the nonparametric lazy learning algorithms, a k-nearest neighbor (k-NN) algorithm was introduced and tested to estimate soil bulk density from other soil properties, including soil textural fractions, EC, pH, SP, OC and TNV. As many as eight nearest neighbors, based on cross validation technique were selected to perform bulk density prediction from the attributes of 136 soil samples. The nonparametric k-NN technique mostly performed equally well using Pearson correlation coefficient (r=0.86), root-mean-squared errors (RMSE=2.5) maximum error (ME=0.15), coefficient of determination (CD=1.3), modeling efficiency (EF=0.75) and coefficient of residual mass (CRM=0.001) statistics. It can be concluded that the k-NN technique is an alternative to other techniques such as pedotransfer functions (PTFs).
Volume 15, Issue 58 (winter 2012)
Microbial transport in soil is critical in different ways, especially in groundwater contamination and bioremediation of groundwater or soil. The main objectives of this research were quantitative study of bacterial transport and deposition under saturated conditions in calcareous soils. A series of column leaching experiments were conducted. Breakthrough curves (BTCs) of Pseudomonas fluorescens and Cl- were measured. After leaching experiment the bacteria was measured in difference layers of the soil columns. The HYDRUS-1D one- and two-site kinetic attachment-detachment models were used to fit and predict transport and deposition of bacteria in soil columns experiments. The results indicated that two-site kinetic model leads to better prediction breakthrough curves and bacteria retention in the calcareous soil in comparison with one-site kinetic model. Interaction with kinetic site 1 was characterized by relatively fast attachment and slow detachment, whereas attachment to and detachment from kinetic site 2 was fast. Fast attachment and slow detachment of site 1 was attributed to soil calcium carbonate that has favorable attachment site for bacteria. The detachment rate was less than 0.01 of the attachment rate, indicating irreversible attachment of bacteria. Most of the cells were retained close to the soil column inlet, and the rate of deposition decreased with depth. Microbial reduction rate for the soil was 4.02-4.88 log m-1. High reduction rate of bacteria was also attributed to soil calcium carbonate that has favorable attachment site for bacteria.
Volume 17, Issue 66 (winter 2014)
In order to assess hydraulics of LNAPLs in soil, the soil retention curves of petroleum and water were both determined through hanging column method. And, the hydraulic conductivity of petroleum and water were determined by steady head method. The water and petroleum hydraulic conductivities were 7.27 and 57.84 cm.day-1, respectively. The soil retention parameters were obtained based on van Genuchten, Brooks-Corey and Campbell models. In addition, the soil hydraulic conductivity for both fluids was predicted based on Mualem- Brooks-Corey, Burdine- Brooks-Corey, Mualem-van Genuchten and Campbell models. The accuracy assessment of models was performed by ME, RMSE, CD, EF and CRM. The results indicated that the magnitudes of the pore-size distribution parameters and the bubbling pressure parameters were reduced in NAPL-air system compared to water-air system. Due to unusual hydraulic behavior of petroleum and soil-petroleum interactions leading to remaining substantial petroleum content in porous media, more matric potential is needed to drain out petroleum from soils compared to water. Thus, soil provides more retention for petroleum at a given quantity of fluid. Owing to high amount of petroleum kinematic viscosity, the saturated soil hydraulic conductivity of petroleum was lower than that of water. However, soil hydraulic conductivity for petroleum was larger than water at more than 100 cm matric head.
Volume 19, Issue 73 (fall 2015)
Salinity and nutrient deficiency particularly nitrogen are two important limiting factors for yield production in arid and semi-arid regions. The objective of this study was to model basil response to combined salinity and nitrogen deficiency. To that end, modified Leibig-Sprengel (LS) and modified Mitcherlich-Baule (MB) and also some newly derived models based on combination of MB with salinity models of Maas and Hoffman (31), van Genuchten and Hoffman (36), Dirksen and Augustijn (17) and Homaee et al., (23) were evaluated. The experiment was conducted under four salinities including 1.175, 3, 5, and 8 dSm-1 and four nitrogen levels including 100, 75, 50, and 0 percent of fertilizer requirements each with three replicates. Results indicated that from among the evaluated models, the derived models of MB and Maas and Hoffman (MB-MH) (nRMSE=4.9), MB and van Genuchten and Hoffman (MB-VG) (nRMSE=5.4), and also MB and Homaee et al., (MB-H) (nRMSE=7.0) provide best fits to the measured data. Also, the comparison of two modified LS and MB models indicated that the estimated relative yield for irrigation water salinity levels by modified LS model (nRMSE=4.6) provides better results (nRMSE=5.9). However, for soil nitrogen levels and interactive effects of salinity and nitrogen, the modified MB model (nRMSE=10.3) provided better outputs (nRMSE=14.4). Consequently, instead of the modified LS and MB models the proposed models in this research can be recommended for use.
Volume 22, Issue 1 (Spring 2018)
In this study, the trends of changes of the standardized precipitation index in a 12-month timescale (SPI-12) and seasonal and annual precipitation were investigated in 21 humid and semi-arid stations of Iran during the 1976-2014 time period. After removing the serial correlation of some series, the trend of precipitation and SPI-12 was detected using the Mann-Kendall nonparametric trend test. The results revealed that the trends of annual precipitation had been declining in all stations over the past 39 years. The seasonal precipitation trend in winter, spring, autumn and summer was downward in approximately 90, 95, 47 and 37% of the studied stations, respectively. In addition, the descending trend of wintertime precipitation was significant in Sanandaj, Khoy, Urmia, Hamedan, Mashhad, Torbat-e-heydarieh, Nozheh and Qazvin. Also, the temporal trend of SPI-12 was decreasing in all surveyed stations except Shahrekord. Furthermore, SPI-12 showed a significant downward trend only in Sanandaj and Fasa. Moreover, the most severe meteorological drought occurred in the period 1999-2000, in Ramsar, Urmia and Hamedan, and in the period 2008-2009, in Tabriz, Sanandaj, Shiraz, Fasa, Qazvin, Mashhad, Torbat-e-heydarieh, Shahrekord, Gorgan and Kermanshah stations. Overall, the results of this study indicated that the trend of precipitation in most studied sites, particularly in semi-arid parts of the northeast and southwest of Iran, has changed due to the severe and long metrological drought that has occurred in the recent decade (2005-2015).
Volume 22, Issue 4 (Winter 2019)
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