scholarly journals Zinc and cadmium adsorption from wastewater using hydroxyapatite synthesized from flue gas desulfurization waste

2021 ◽  
Author(s):  
Sıla Kızıltas Demir ◽  
Nurcan Tugrul
Keyword(s):  
Heavy Metal ◽  
Adsorption Capacity ◽  
Metal Concentration ◽  
Flue Gas ◽  
Contact Time ◽  
Heavy Metal Concentration ◽  
Flue Gas Desulfurization ◽  
Synthetic Wastewater ◽  
Cadmium Adsorption ◽  
Adsorbent Dose

Abstract The purpose of this work is to produce an alternative cost-effective adsorbent to remove zinc and cadmium from wastewater using hydroxyapatite (HAP) synthesized with hydrothermal method from FGD (Flue gas desulfurization) waste generated by two different coal power plants. The effects of FGD type (Cayırhan and Orhaneli) and molar ratio (H3PO4/CaSO4) (0.6–4.79) on HAP synthesis were investigated. Afterwards effects of the adsorbent dose (1–2 g/L), heavy metal concentration (30, 40, 50 mg/L) and contact time (1, 2, 3, 4 h) on zinc and cadmium adsorption yield from synthetic wastewater using produced HAP were examined. FGD waste and synthesized FGD-HAP were characterized by X-Ray Diffraction (XRD), Fourier Transformed Infrared Spectroscopy (FT-IR), Scanning Electron Microscope (SEM) and Brunauer-Emmett-Teller (BET) instruments. The zinc and cadmium concentration was studied by Inductively coupled plasma atomic emission spectroscopy (ICP-AES). Maximum zinc adsorption capacity of the Cayırhan FGD-HAP was 49.97 and 49.99 mg/L, Orhaneli FGD-HAP was 49.96 and 49.99 mg/L, for 1 g/L and 2 g/L adsorbent dose respectively, for 50 mg/L heavy metal concentration and 4 h contact time. Maximum cadmium adsorption capacity of the Cayırhan FGD-HAP was 39.98 and 39.99 mg/L, Orhaneli FGD-HAP was 40 and 39.99 mg/L, for 1 g/L and 2 g/L adsorbent dose respectively, for 40 mg/L heavy metal concentration and 4 h contact time. Adsorption yields were calculated between 98.53 and 100%. The adsorption data were well explained by second order kinetic model and the Freundlich isotherm model fits the equilibrium data. The adsorption results demonstrated that FGD's waste is an effective source to synthesis HAP which is used as an adsorbent for zinc and cadmium removal from wastewater due to high adsorption capacity.

Use of agro-waste (Musa paradisiaca peels) as a sustainable biosorbent for toxic metal ions removal from contaminated water

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Contact Time ◽  
Metal Ion ◽  
Equilibrium Concentration ◽  
Ion Concentration ◽  
Contaminated Water ◽  
Musa Paradisiaca ◽  
Percentage Removal ◽  
Adsorbent Dose

A study of removal of heavy metal ions from heavy metal contaminated water using agro-waste was carried out with Musa paradisiaca peels as test adsorbent. The study was carried by adding known quantities of lead (II) ions and cadmium (II) ions each and respectively into specific volume of water and adding specific dose of the test adsorbent into the heavy metal ion solution, and the mixture was agitated for a specific period of time and then the concentration of the metal ion remaining in the solution was determined with Perkin Elmer Atomic absorption spectrophotometer model 2380. The effect of contact time, initial adsorbate concentration, adsorbent dose, pH and temperature were considered. From the effect of contact time results equilibrium concentration was established at 60minutes. The percentage removal of these metal ions studied, were all above 90%. Adsorption and percentage removal of Pb2+ and Cd2+ from their aqueous solutions were affected by change in initial metal ion concentration, adsorbent dose pH and temperature. Adsorption isotherm studies confirmed the adsorption of the metal ions on the test adsorbent with good mathematical fits into Langmuir and Freundlich adsorption isotherms. Regression correlation (R2) values of the isotherm plots are all positive (>0.9), which suggests too, that the adsorption fitted into the isotherms considered.

scholarly journals Heavy metal concentration in fish tissues inhabiting waters of “Buško Blato” reservoar (Bosnia and Herzegovina)

2008 ◽  
Vol 145 (1-3) ◽  
pp. 475-475 ◽  
Author(s):  
Elizabeta Has-Schön ◽  
Ivan Bogut ◽  
Gordana Kralik ◽  
Stjepan Bogut ◽  
Janja Horvatić ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Metal Concentration ◽  
Bosnia And Herzegovina ◽  
Heavy Metal Concentration ◽  
Fish Tissues

Remediation-related monitoring of heavy metal concentration of contaminated Technosol using hyperspectral measurements

2021 ◽  
Author(s):  
Friederike Kaestner ◽  
Magdalena Sut-Lohmann ◽  
Thomas Raab ◽  
Hannes Feilhauer ◽  
Sabine Chabrillat
Keyword(s):  
Heavy Metal ◽  
Random Forest ◽  
Metal Concentration ◽  
Strong Dependence ◽  
Scatter Correction ◽  
Heavy Metal Concentration ◽  
Standard Normal Variate ◽  
Multiplicative Scatter Correction ◽  
Second Derivatives ◽  
Standard Normal

<p>Across Europe there are 2.5 million potentially contaminated sites, approximately one third have already been identified and around 15% have been sanitized. Phytoremediation is a well-established technique to tackle this problem and to rehabilitate soil. However, remediation methods, such as biological treatments with microorganisms or phytoremediation with trees, are still relatively time consuming. A fast monitoring of changes in heavy metal content over time in contaminated soils with hyperspectral spectroscopy is one of the first key factors to improve and control existing bioremediation methods.</p><p>At former sewage farms near Ragow (Brandenburg, Germany), 110 soil samples with different contamination levels were taken at a depth between 15-20 cm. These samples were prepared for hyperspectral measurements using the HySpex system under laboratory conditions, combing a VNIR (400-1000 nm) and a SWIR (1000-2500 nm) line-scan detector. Different spectral pre-processing methods, including continuum removal, first and second derivatives, standard normal variate, normalisation and multiplicative scatter correction, with two established estimation models such as Partial Least Squares Regression (PLSR) and Random Forest Regression (RFR), were applied to predict the heavy metal concentration (Ba, Ni, Cr, Cu) of this specific Technosol. The coefficient of determination (R2) shows for Ba and Ni values between 0.50 (RMSE: 9%) and 0.61 (RMSE: 6%) for the PLSR and between 0.84 (RMSE: 0.03%) and 0.91 (RMSE: 0.02%) for the RFR model. The results for Cu and Cr show values between 0.57 (RMSE: 17.9%) and 0.69 (RMSE: 15%) for the PLSR and 0.86 (0.12%) and 0.93 (0.01%) for the RFR model. The pre-processing method, which improve the robustness and performance of both models best, is multiplicative scatter correction followed by the standard normal variate for the first and second derivatives. Random Forest in a first approach seems to deliver better modeling performances. Still, the pronounced differences between PLSR and RFR fits indicate a strong dependence of the results on the respective modelling technique. This effect is subject to further investigation and will be addressed in the upcoming analysis steps.</p>

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