Effect of acid rain on the fractionation of heavy metals and major elements in contaminated soils

Acid rain is a serious environmental problem worldwide. In the present study, we investigated the effect of acid rain (1:1 equivalent basis H₂SO₄:HNO₃) at pH values of 2.0, 4.0 and 7.0 on the fractionation of heavy metals (Cd, Cu, Fe, Mn, Ni, Pb and Zn) and major elements (K, Na, Ca, and Mg) in contaminated calcareous soils over a 2084 h period. Heavy metals and major elements in soil samples were fractionated before and after 2084 h kinetic release using a sequential extraction procedure. Before kinetic studies the predominant fractions of K, Na, Ca, Mg, Cd and Ni were mainly associated with carbonate fraction (CARB), whereas Fe, Mn and Zn were associated with the Fe–Mn oxide fraction (Fe–Mn oxide). The highest percentage of Pb and Cu were found in the exchangeable (EXC) and organic matter (OM) fractions, respectively. After kinetic study using different simulated acid rain solutions, the major fractions of heavy metals (expect of Cu) and Na was the same as before release. Upon the application of different acid rain solutions, K and Mg were found dominantly in Fe–Mn oxide fraction, whereas Ca was in the EXC fraction. The results provide valuable information regarding metal mobility and indicated that speciation of metals (Cu and Zn) and major elements in contaminated calcareous soils can be affected by acid rain.     

Carbon dioxide separation and capture by adsorption: a review

Environmental Chemistry Letters - Rising adverse impact of climate change caused by anthropogenic activities is calling for advanced methods to reduce carbon dioxide emissions. Here, we...     

Assessment of mobile and potential mobile trace elements extractability in calcareous soils using different extracting agents

• DTPA and NH₄OAc, HNO₃ and EDTA, and MgCl₂ and NH₄NO₃ had similar behavior. • In NH₄OAc, DTPA, and EDTA, the possibility of re-adsorption of trace elements is low. • CaCl₂ may be more suitable than other extracts in calcareous soils. Understanding trace elements mobility in soils, extracting agents, and their relationships with soil components, are essential for predicting their movement in soil profile and availability to plants. A laboratory study was conducted to evaluate extractability of cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), and zinc (Zn) from calcareous soils utilizing various extracting agents to be specific CaCl₂, DTPA, EDTA, HNO₃, MgCl₂, NaNO₃, NH₄NO₃, and NH₄OAc. Cluster analysis indicated that DTPA and NH₄OAc, HNO₃ and EDTA, and MgCl₂ and NH₄NO₃ extracting agents yielded comparative values, whereas NaNO₃ and CaCl₂ have shown different behavior than other extracting agents for all studied trace elements. The speciation of extracted trace elements in solutions indicated that in the CaCl₂, NaNO₃, NH₄NO₃, and MgCl₂ extracting agents most extracted Cd, Co, Ni, Zn, and part of Cu were as free ions and may be re-adsorbed on soils, leading to lower extractability, whereas, in the case of HNO₃ extracting agent, the likelihood of re-adsorption of trace elements may be little. The results of speciation of trace elements using NH₄OAc, DTPA, and EDTA extracting agents showed that Me-(Acetate)₃^–, Me-(Acetate)₂(aq), Me(DTPA)³⁻, Me(EDTA)²⁻, and MeH(EDTA)^– complexes dominated in solutions indicating that the extracted trace elements may not be re-adsorbed on soils, leading to higher extractability. The results of this study are useful for short and long-term evaluations of trace elements mobility and further environmental impacts.     

Modeling biodegradation and kinetics of glyphosate by artificial neural network

An artificial neural network (ANN) model was developed to simulate the biodegradation of herbicide glyphosate [2-(Phosphonomethylamino) acetic acid] in a solution with varying parameters pH, inoculum size and initial glyphosate concentration. The predictive ability of ANN model was also compared with Monod model. The result showed that ANN model was able to accurately predict the experimental results. A low ratio of self-inhibition and half saturation constants of Haldane equations (< 8) exhibited the inhibitory effect of glyphosate on bacteria growth. The value of K(i)/K(s) increased when the mixed inoculum size was increased from 10(4) to 10(6) bacteria/mL. It was found that the percentage of glyphosate degradation reached a maximum value of 99% at an optimum pH 6-7 while for pH values higher than 9 or lower than 4, no degradation was observed.     

The Comparison of Lagrangian and Gaussian Models in Predicting of Air Pollution Emission Using Experimental Study,a Case Study: Ammonia Emission

Ammonia, as a colorless gas with a sharp odor, is considered as one of the created odors in the composting and landfill of solid waste. We used experimental data to study the robustness of AERMOD and the forward Lagrangian stochastic (FLS) in predicting ammonia emission in short range. The study area was Kahrizak landfill and composting plants, Tehran, Iran. The boundary layer parameters for the FLS were calculated on the basis of mean values of temperature, wind speed, and direction. While, the boundary layers of AERMOD were computed on the basis of exact meteorological data. The results depicted that AERMOD prediction at distances less than 1000 m from the sources and the locations inside the sources were poor. However, the results of FLS indicated more agreement with the field measurement, which the coefficient of determination was 0.83. Both models predicted, in the distance of 2000 m from the source, the ammonia concentration would be insignificant.     

Correction to: Effect of organic and inorganic phosphorus fertilizers on phosphorus availability and its leaching over incubation time

Environmental Science and Pollution Research - The correct presentation of the equations in Table 6 footnote is presented in this paper     

Optimization and assessment of an electrochemical advanced oxidation system for synthetic stormwater treatment

Environmental Science and Pollution Research - Electrochemical advanced oxidation processes (eAOPs) such as the current advanced oxidation system (AOS) are a type of electrochemical wastewater...     

Simultaneous monitoring of SARS-CoV-2, bacteria,and fungi in indoor air of hospital: a study on Hajar Hospital in Shahrekord,Iran

The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients’ clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m^?3 and 18 to 141 CFU m^?3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients’ clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.