Drivers of local people’s participation in sustainable natural resource management: a case study in central Iran

The driving forces behind natural resource management (NRM) vary among countries. Most NRM programmes focus on biophysical drivers such as soil, water and vegetation, with little attention directed towards the nuanced sociocultural and religious drivers of sustainable natural resource management (SNRM) practices. This paper explores those understudied drivers that influence local people’s participation (LPP) in SNRM in Isfahan, Iran. Using a multi-stage stratified sampling method, we selected 200 natural resource experts and natural resource users to complete a questionnaire about their perceptions of SNRM. Results reveal that sociocultural and religious beliefs are the major drivers of SNRM. The results also indicate that subsidiary drivers include: a sense of responsibility towards SNRM; the conviction that natural resources belong to God and should therefore be preserved; participation to preserve natural resources because of training courses and media influence; a long-established custom of preserving natural resources; and the specific impact of environmental television programmes. Demographic analysis finds a significant relationship between educational level and LPP in SNRM. This study’s results therefore suggest that natural resource managers would benefit from a deeper understanding of the local sociocultural and religious contexts that motivate people to participate in SNRM.     

Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet

We are introducing graphene oxide modified with amine groups as a new solid phase for extraction of heavy metal ions including cadmium(II), copper(II), nickel(II), zinc(II), and lead(II). Effects of pH value, flow rates, type, concentration, and volume of the eluent, breakthrough volume, and the effect of potentially interfering ions were studied. Under optimized conditions, the extraction efficiency is >97 %, the limit of detections are 0.03, 0.05, 0.2, 0.1, and 1 μg L^?1 for the ions of cadmium, copper, nickel, zinc, and lead, respectively, and the adsorption capacities for these ions are 178, 142, 110, 125, and 210 mg g^?1. The amino-functionalized graphene oxide was characterized by thermogravimetric analysis, transmission electron microscopy, scanning electron microscopy, and Fourier transform infrared spectrometry. The proposed method was successfully applied in the analysis of environmental water and food samples. Good spiked recoveries over the range of 95.8–100.0 % were obtained. This work not only proposes a useful method for sample preconcentration but also reveals the great potential of modified graphene as an excellent sorbent material in analytical processes.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Contaminants of emerging concern: a review of new approach in AOP technologies

The presence of contaminants of emerging concern (CECs) such as pharmaceuticals and personal care products (PPCPs), endocrine-disrupting compounds (EDCs), flame retardants (FRs), pesticides, and artificial sweeteners (ASWs) in the aquatic environments remains a major challenge to the environment and human health. In this review, the classification and occurrence of emerging contaminants in aquatic environments were discussed in detail. It is well documented that CECs are susceptible to poor removal during the conventional wastewater treatment plants, which introduce them back to the environment ranging from nanogram per liter (e.g., carbamazepine) up to milligram per liter (e.g., acesulfame) concentration level. Meanwhile, a deep insight into the application of advanced oxidation processes (AOPs) on mitigation of the CECs from aquatic environment was presented. In this regard, the utilization of various treatment technologies based on AOPs including ozonation, Fenton processes, sonochemical, and TiO₂ heterogeneous photocatalysis was reviewed. Additionally, some innovations (e.g., visible light heterogeneous photocatalysis, electro-Fenton) concerning the AOPs and the combined utilization of AOPs (e.g., sono-Fenton) were documented.     

Optimized processing power and trainability of neural network in numerical modeling of Al Matrix nano composites

In this research, an experimental study of reinforcing alumina nano-particles into the aluminum alloy matrix was implemented to verify the accuracy of modeling results obtained by feed forward neural networks. Artificial neural network combined with numerical technique were used to predict the various parameters of mechanical properties such as hardness, tensile and compressive yield stress, UTS and elongation percentage. Much experimentation were taken to discover a suitable number of hidden neurons, avoid detraction from the trainability and enable feed forward neural networks to solve more complex problems. The predictions were found to be consistent with experimental measurements.     

Are photocatalytic processes effective for removal of airborne viruses from indoor air? A narrative review

A wide variety of methods have been applied in indoor air to reduce the microbial load and reduce the transmission rate of acute respiratory diseases to personnel in healthcare sittings. In recent months, with the occurrence of COVID-19 pandemic, the role of portable ventilation systems in reducing the load of virus in indoor air has received much attention. The present study delineates a comprehensive up-to-date overview of the available photocatalysis technologies that have been applied for inactivating and removing airborne viruses. The detection methods for identifying viral particles in air and the main mechanisms involving in virus inactivation during photocatalysis are described and discussed. The photocatalytic processes could effectively decrease the load of viruses in indoor air. However, a constant viral model may not be generalizable to other airborne viruses. In photocatalytic processes, temperature and humidity play a distinct role in the inactivation of viruses through changing photocatalytic rate. The main mechanisms for inactivation of airborne viruses in the photocatalytic processes included chemical oxidation by the reactive oxygen species (ROS), the toxicity of metal ions released from metal-containing photocatalysts, and morphological damage of viruses.

     

Current understanding of the influence of environmental factors on SARS-CoV-2 transmission,persistence, and infectivity

Environmental Science and Pollution Research - Coronavirus disease 2019 (COVID-19) has emerged as a significant public health emergency in recent times. It is a respiratory illness caused by the...