The interactions of Cr (VI) concentrations and amendments (biochar and manure) on growth and metal accumulation of two species of Salicornia in contaminated soil

Environmental Science and Pollution Research - Heavy metals are among the most dangerous contaminants in the environment. Organic components and plant species that can accumulate and stabilize...     

Application of dynamic models to estimate greenhouse gas emission by wastewater treatment plants of the pulp and paper industry

Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid—anaerobic/aerobic—biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ±30, ±19, and ±17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ±16, ±17, and ±14 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.     

Photoassisted and photocatalytic degradation of sulfur mustard using TiO2 nanoparticles and polyoxometalates

The decomposition of highly toxic chemical warfare agent, sulfur mustard (bis(2-chloroethyl) sulfide or HD), has been studied by homogeneous photolysis and heterogeneous photocatalytic degradation on titania nanoparticles. Direct photolysis degradation of HD with irradiation system was investigated. The photocatalytic degradation of HD was investigated in the presence of TiO₂ nanoparticles and polyoxometalates embedded in titania nanoparticles in liquid phase at room temperature (33?±?2 °C). Degradation products during the treatment were identified by gas chromatography–mass spectrometry. Whereas apparent first-order kinetics of ultraviolet (UV) photolysis were slow (0.0091 min^?1), the highest degradation rate is obtained in the presence of TiO₂ nanoparticles as nanophotocatalyst. Simultaneous photolysis and photocatalysis under the full UV radiation leads to HD complete destruction in 3 h. No degradation products observed in the presence of nanophotocatalyst without irradiation in 3 h. It was found that up to 90 % of agent was decomposed under of UV irradiation without TiO₂, in 6 h. The decontamination mechanisms are often quite complex and multiple mechanisms can be operable such as hydrolysis, oxidation, and elimination. By simultaneously carrying out photolysis and photocatalysis in hexane, we have succeeded in achieving faster HD decontamination after 90 min with low catalyst loading. TiO₂ nanoparticles proved to be a superior photocatalyst under UV irradiation for HD decontamination.     

Options for sustainable development planning based on “GHGs emissions reduction allocation (GERA)” from a national perspective

Climate change phenomenon can be seen as a simple but daunting problem. The lack of equity in emission reduction burden sharing regime, will cause a need for a greater sacrifice for poor or less developed countries. Thus, the evaluation of different aspects of equity at a national scale and presenting a top–down model of equity for allocation of GHGs emission (such as GERA) in line with sustainable development is the main objective of this study. In this study, the five equity principles proposed in the literature namely (1) population distribution, (2) GHGs emissions, (3) GDP, (4) trend of economic growth and (5) per capita of carbon productivity as appropriate criteria of equity estimation. Due to the different decision makers' preferences, different weights are allocated to indicators and analyzed. Iran has been considered as a case study, and these criteria were applied at national level to propose an allowance allocation scheme. The result of applying GERA for Iran, at provincial level and under the five equity criteria, determines which provinces have to shoulder higher reduction burdens, and makes a room for less developed provinces for growth. Based on these results, this model demonstrated to be more sensitive to criteria selection rather than to the weight factors. In addition, shifting to low carbon technologies or renewables, careful evaluation of current emission–income pattern, improving of energy intensity and finally, adjustment of secondary industries (manufacturing) based on ecological and natural resources of each region are suggested as the most efficient approaches toward sustainability and green development for the case study.     

‘How corporate social responsibility can be integrated into corporate sustainability: a theoretical review of their relationships’

The notion that corporations are expected to have social and environmental performance standards and practices while meeting their financial and legal obligations is commonly referred to as corporate social responsibility (CSR) or corporate sustainability (CS). Previous studies have discussed whether the two terms are converging or should be used as stand-alone concepts. After reviewing the trends in development of CSR and CS, and the various viewpoints on the relationships between the two, we propose a relationship model to better understand how CSR can be integrated into CS as either a transitional stage or ultimate goal for a corporation. This study aims to provide researchers and practitioners with further insights on the adoption of CSR and CS. The model is intended to provide a plausible view of the relationships between CSR and CS to help to lessen the confusion and ease the communication both between and within these fields.     

Experimental and Numerical Analysis of CO Concentration Dispersion of Vehicular Exhaust Emissions in Isolated Environment

Numerical and experimental analyses were applied to carbon monoxide (CO) concentration dispersion to monitor air quality in an enclosed residential complex parking area in Tehran. Firstly, the parking area was preliminary assessed through verifying the characteristics of the problem including the geometry and boundary conditions. Then, proportion of vehicular exhaust emissions was estimated and eventually experimental and numerical analyses were performed. In order to perform numerical calculation, a three-dimensional model was created to numerically simulate the enclosed residential complex parking area by FLUENT software that solves flow governing equations with finite volume method. In FLUENT, species model was selected to assess the dispersion of CO in flow domain. In experimental analysis, CO concentration was measured using sampling bags with a volume of 10 l in 4 min at 6 different points. The sample air was drawn into sampling bags by electric pumps. The findings show that the maximum amount of CO concentration is above the permissible standard recommended by the World Health Organization. Pollutant accumulation was significant in confined areas. In the place where openings exist, the level of accumulation was lower than other areas. The findings obtained from numerical simulation are in complete accord with experimental results.     

A well to wire LCA model development and sensitivity analysis for carbon footprint of combined cycle power plants in Iranian electricity network

The present research introduces a well to wire pseudo comprehensive carbon footprint model for combined cycle power plants. The mentioned model integrates land use change model, operational model and transmission and distribution model into one comprehensive model. The parameters which their effects are considered in the integrated model are: fuel type, fuel transmission type, emission for fuel extraction and processing, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. For quantifying the effectiveness of each parameter, sensitivity analyses based on different life cycle scenarios are performed. The result shows that the effect of land use change is negligible. The carbon footprint of electrical energy produced in combined cycle plant until it is delivered to the end users varies from 321 to 522 g CO₂ eq/kWh.     

Uncertainty analysis of developed ANN and ANFIS models in prediction of carbon monoxide daily concentration

This study aims to predict daily carbon monoxide (CO) concentration in the atmosphere of Tehran by means of developed artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. Forward selection (FS) and Gamma test (GT) methods are used for selecting input variables and developing hybrid models with ANN and ANFIS. From 12 input candidates, 7 and 9 variables are selected using FS and GT, respectively. Evaluation of developed hybrid models and its comparison with ANN and ANFIS models fed with all input variables shows that both FS and GT techniques reduce not only the output error, but also computational cost due to less inputs. FS–ANN and FS–ANFIS models are selected as the best models considering R², mean absolute error and also developed discrepancy ratio statistics. It is also shown that these two models are superior in predicting pollution episodes. Finally, uncertainty analysis based on Monte-Carlo simulation is carried out for FS–ANN and FS–ANFIS models which shows that FS–ANN model has less uncertainty; i.e. it is the best model which forecasts satisfactorily the trends in daily CO concentration levels.