Synergism effects of phenol-degrading yeast and ammonia-oxidizing bacteria for nitrification in coke wastewater of Esfahan Steel Company.

Ammonia-oxidizing bacteria and phenol-degrading yeast were isolated in order to study the synergism effects of phenol-degrading yeast and ammonia-oxidizing bacteria for enhancing the nitrification in coke wastewater from the Isfahan Steel Company. The influent and effluent samples with approximately 600-1200 mg L(-1) ammonium and 550-2350 mg L(-1) phenol were collected aseptically in sterile flasks. The biodegradation of phenol and nitrification were studied with different treatments. The results showed that addition of Na2CO3 and autotrophic bacteria to wastewater increased the ammonium removal by 100%. Furthermore, the synergism effects of phenol-degrader yeast and autotrophic bacteria reduced the time for ammonium removal.     

Detection of SARS-CoV-2 in the indoor air of intensive care unit (ICU) for severe COVID-19 patients and its surroundings: considering the role of environmental conditions

Environmental Science and Pollution Research - There is ambiguity about the airborne transmission of the SARS-CoV-2. While a distance of 6 feet is considered a safe physical distance, new findings...     

On the mitigating environmental aspects of a vertical well in underground coal gasification method

Mitigation and Adaptation Strategies for Global Change - Underground coal gasification (UCG) is an energy production pathway in underground coal deposits with the potential advantage of decreasing...     

Adaptation strategies for maize cultivation under climate change in Iran: irrigation and planting date management

Climate change is affecting the productivity of crops and their regional distribution. Strategies to enhance local adaptation capacity are needed to mitigate climate change impacts and to maintain regional stability of food production. The objectives of this study were to simulate the climate change effects on phenological stages, Leaf Area Index (LAI), biomass and grain yield of maize (Zea mays L.) in the future and to explore the possibilities of employing irrigation water and planting dates as adaptation strategies to decrease the climate change impacts on maize production in Khorasan Razavi province, Iran. For this purpose, we employed two types of General Circulation Models ((United Kingdom Met. Office Hadley Center: HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1). Long Ashton Research Station-Weather Generator (LARS-WG) was used to produce daily climatic parameters as one stochastic growing season for each projection period. Also, crop growth under projected climate conditions was simulated based on the Cropping System Model (CSM)-CERES-Maize. The results of model evaluation showed that LARS-WG had appropriate prediction for climatic parameters. Time period from cultivation until anthesis and maturity were reduced in majority of scenarios as affected by climate change. The results indicated that the grain yield of maize may be reduced (11 % to 38 %) as affected by climate change based on common planting date in baseline and changed (?61 % to 48 %) in response to different irrigation regimes in the future climate change, under all scenarios and times. In general, earlier planting date (1 May) and decreasing irrigation intervals in the anthesis stage (11 applications) caused higher yield compared with other planting dates due to adaption to high temperature. Based on our findings, it seems that management of irrigation water and planting dates can be beneficial for adaptation of maize to climate change in this region.     

A Comparison of Modified and Unmodified Cellulose Nanofiber Reinforced Polylactic Acid (PLA) Prepared by Twin Screw Extrusion

The goal of this work was to evaluate the effect of chemical modification of cellulose nanofibers (CNF) on the properties of polylactic acid (PLA) nanocomposites. Acetylated nanofibers (ACNF), with degree of substitution 1.07, were isolated from acetylated kenaf fibers by mechanical treatments. Acetylated nanofibers showed more hydrophobic properties compared to non-acetylated ones. The results showed that both crystallinity and thermal stability of acetylated nanofibers were lower than non-acetylated ones. The nanocomposites were prepared by premixing two PLA master batches, one with a high concentration of ACNF and the second with CNF. These were diluted to final concentrations (5?wt%) during the extrusion. The morphology studies of PLA and its nanocomposites showed nanofiber aggregates in both materials. The results showed that the tensile and dynamic mechanical properties were enhanced for both acetylated and non-acetylated nanocomposites compared to the neat PLA matrix while no significant improvement was observed for the acetylated nanocomposites compared to non-acetylated ones. However, the storage modulus increased slightly for acetylated nanocomposites compared to non-acetylated ones.     

Behavioral and histological characterization of the effects of cigarette smoke inhalation and withdrawal in rats

Abstract

The aims of the study are to assess some effects of smoking for 3?months and of withdrawal of male weaned rats on anxiety, locomotor activity, and depression using common behavioral tests such as the marble burying, open field, and forced swim tests. Somatic signs of abstinence and histological effects were also studied. The rats present changes of the aforementioned behaviors as well as histological alterations of the lungs.     

Nonlinear molecular based modeling of the flash point for application in inherently safer design

New chemical process design strategies utilizing computer-aided molecular design (CAMD) can provide significant improvements in process safety by designing chemicals with required target properties and the substitution of safer chemicals. An important aspect of this methodology concerns the prediction of properties given the molecular structure. This study utilizes one such emerging method for prediction of a hazardous property, flash point (FP), which is in the center of attention in safety studies. Using such a reliable data set comprising 1651 organic and inorganic chemicals, from 79 diverse material classes, and robust dynamic binary particle swarm optimization for the feature selection step resulted in the most efficient molecular features of the FP investigations. Apart from the simple yet precise five-parameter multivariate model, the FP nonlinear behavior was thoroughly investigated by a novel hybrid of particle swarm optimization and support vector regression. Besides, 195 missing experimental FPs of the DIPPR data set are predicted via the presented procedure.     

The dynamic causal links between CO2 emissions from transport,real GDP,energy use and international tourism

This study examines the dynamic causality relationship between international tourism and carbon dioxide (CO₂) emissions from transport, real gross domestic product and energy use. The vector error correction model and Granger causality test approach have been used to investigate these relationships for the top ten international tourism destinations spanning the period 1995–2013. Results reveal a unidirectional causality running from CO₂ emissions to economic growth without feedback; a bidirectional causality between economic growth and energy use; a bidirectional causality between international tourism and economic growth; and a bidirectional causality between international tourism and energy use. They also suggest that energy use and international tourism both contribute to the decrease of emissions level coming from transport sector, while economic growth leads to the increase of CO₂ emissions. This study can be used in policy recommendations by encouraging countries to use clean energy and to stimulate tourism sector for combating global warming.     

Application of quadratic regression model for Fenton treatment of municipal landfill leachate

The effectiveness of Fenton process in municipal landfill leachate treatment, as a pre- or post-treatment approach, has been demonstrated. However, no general recommendations of universal validity could be made in the term of optimized conditions affecting Fenton process. At the first stage of this study, collected leachate samples from Aradkooh site, Tehran, Iran, were investigated using one-factor-at-a-time method to find out optimum coagulation pH and flocculation time values. Subsequently, the obtained results in addition to data issued previously by the authors were employed to develop a predictive model of the true response surface, namely chemical oxygen demand (COD) removal efficiency. Finally, the main parameters of Fenton procedure, i.e. initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were optimized taking advantage of the above-mentioned quadratic model. The derived second-order model included both significant linear and quadratic terms and seemed to be adequate in predicting responses (R(2)=0.9896 and prediction R(2)=0.6954). It was found that the interaction between initial pH and Fe(2+) dosage has a significant effect on COD removal. While, the optimal [H(2)O(2)]/[Fe(2+)] molar ratio was independent of ferrous ion dosage. The optimum conditions for the maximum COD removal of 50.76% for the parameters of initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were found to be 5.8, 8.0, 22,500mg/L, and 8.7 respectively.