Determination of soil-to-plant transfer factors of 137 Cs and 90 Sr in the tropical environment of Bangladesh

1998 ◽  
Vol 37 (2) ◽  
pp. 125-128 ◽  
Author(s):  
A. S. Mollah ◽  
Aleya Begum ◽  
S. M. Ullah
2021 ◽  
Vol 46 (2) ◽  
Author(s):  
M. A. Balogun ◽  
M. O. Money-Irubor

Heavy metals in varied concentrations are employed in the production of steel of different grades. Silver, cadmium, cobalt, chromium, and copper are of great importance in achieving this. They are part of the main ingredients in the production processes, which in most cases determines steel grades. The location of an integrated steel plant within Udu community of Delta State resulted in the pollution of the soil of the surrounding communities, most of which are involved in farming and fishing activities. This necessitated the transfer of these heavy metals from polluted soils into edible plants. These were mainly as a result of discharges of effluents, smoke and particulates from stack during production into the soils of the surrounding communities and finally into some edible plants; that are consumed by the communities as vegetables. Soil and leaf samples were collected from six different towns or communities in Udu. The towns are Ujevwu, Aladja, Ovwian, Ekete Inland, Orhuwhorun and Otor-Udu; and the heavy metals analysed are Ag, Cd, Co, Cr, Cu and Fe. These samples were digested using USEPA Method 3050B and the heavy metals were determined using atomic absorption spectrophotometer (AAS). Results obtained showed the following range for transfer factors (TF) in three different edible plants; which are pumpkin plant (Telfaira occidentalis), bitter leaf plant (Vernonia amygdalina) and scent leaf plant (Occinium gratissimum). The range of values obtained for the transfer factors are- Ag: 4.48–196.45; Cd: 44.52–212.79; Co: 0.03–0.46; Cr: 0.38–3.37; Cu: 21.76–102.95 and Fe: 2.85–14.40. For the six sample sites, generally, the values are in the order: Cd ˃ Ag ˃ Cu ˃ Fe ˃ Cr ˃ Co. Result interpretation shows some level of contamination when compared to recommended standard of these heavy metals in plants. The effect of which can be devastating in the future if not checked.


2021 ◽  
Author(s):  
Franck Albinet ◽  
Gerd Dercon ◽  
Tetsuya Eguchi

<p>The Joint IAEA/FAO Division of Nuclear Techniques in Food and Agriculture, through its Soil and Water Management & Crop Nutrition Laboratory (SWMCNL), launched in October 2019, a new Coordinated Research Project (D15019) called “Monitoring and Predicting Radionuclide Uptake and Dynamics for Optimizing Remediation of Radioactive Contamination in Agriculture''. Within this context, the high-throughput characterization of soil properties in general and the estimation of soil-to-plant transfer factors of radionuclides are of critical importance.</p><p>For several decades, soil researchers have been successfully using near and mid-infrared spectroscopy (MIRS) techniques to estimate a wide range of soil physical, chemical and biological properties such as carbon (C), Cation Exchange Capacities (CEC), among others. However, models developed were often limited in scope as only small and region-specific MIR spectra libraries of soils were accessible.</p><p>This situation of data scarcity is changing radically today with the availability of large and growing library of MIR-scanned soil samples maintained by the National Soil Survey Center (NSSC) Kellogg Soil Survey Laboratory (KSSL) from the United States Department of Agriculture (USDA-NRCS) and the Global Soil Laboratory Network (GLOSOLAN) initiative of the Food Agency Organization (FAO). As a result, the unprecedented volume of data now available allows soil science researchers to increasingly shift their focus from traditional modeling techniques such as PLSR (Partial Least Squares Regression) to classes of modeling approaches, such as Ensemble Learning or Deep Learning, that have proven to outperform PLSR on most soil properties prediction in a large data regime.</p><p>As part of our research, the opportunity to train higher capacity models on the KSSL large dataset (all soil taxonomic orders included ~ 50K samples) makes it possible to reach a quality of prediction for exchangeable potassium so far unsurpassed with a Residual Prediction Deviation (RPD) around 3. Potassium is known for its difficulty of being predicted but remains extremely important in the context of remediation of radioactive contamination after a nuclear accident. Potassium can help reduce the uptake of radiocaesium by crops, as it competes with radiocaesium in soil-to-plant transfer.</p><p>To ensure informed decision making, we also guarantee that (i) individual predictions uncertainty is estimated (using Monte Carlo Dropout) and (ii) individual predictions can be interpreted (i.e. how much specific MIRS wavenumber regions contribute to the prediction) using methods such as Shapley Additive exPlanations (SHAP) values.</p><p>SWMCNL is now a member of the GLOSOLAN network, which helps enhance the usability of MIRS for soil monitoring worldwide. SWMCNL is further developing training packages on the use of traditional and advanced mathematical techniques to process MIRS data for predicting soil properties. This training package has been tested in October 2020 with thirteen staff members of the FAO/IAEA Laboratories in Seibersdorf, Austria.</p>


2017 ◽  
Vol 7 ◽  
Author(s):  
M. Haque ◽  
J. Ferdous

The radioactivity of environmental samples from nuclear reactor sites must be analyzed before the public is given free access to the plants grown in these soils. Plant and corresponding soil samples were collected from a sample site around the Savar research reactor near Dhaka (Bangladesh) and the activity concentrations of natural radionuclides <sup>226</sup>Ra (<sup>238</sup>U-chain), <sup>228</sup>Ra (<sup>232</sup>Th-chain) and non-chained <sup>40</sup>K were measured using gamma ray spectrometry. Soils of Savar contained more radioactive <sup>40</sup>K than <sup>226</sup>Ra and <sup>228</sup>Ra. The influence of certain soil properties on the activity concentrations and transfer factors (TF) of natural radionuclides were investigated by correlating the observed data with those of soil properties. The activity concentrations of <sup>40</sup>K were much higher than those of <sup>226</sup>Ra and <sup>228</sup>Ra in plants due to higher uptake from soils. The transfer factors for <sup>226</sup>Ra, <sup>228</sup>Ra and <sup>40</sup>K were found to range from 0.04 to 0.10, 0.12 to 0.32, and 0.24 to 0.72, respectively. The soil to plant transfer factors for <sup>40</sup>K was found to be much higher in plants, which might be due to this element being vital in plants. This study showed that activity concentrations of these radionuclides in plants and their plant transfer factors seem to depend on the activity concentrations of the same radionuclides in soil.</p><p><strong> </strong>


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