Behavioral intentions toward genetically modified crops in Southwest Iran: a multi-stakeholder analysis

This study examined the influencing factors of the self-reported behavioral intentions toward genetically modified (GM) crops using a multi-stakeholder approach in the Khuzestan Province in Southwest Iran. The study focused on three different groups, including: “agricultural students,” “agricultural private firms’ managers” and “rich-resource farmers.” Data were collected using a researcher-made questionnaire and was analyzed by SPSS (V20) and AMOS (V20). Results indicated that the respondents perceive more benefits than risks for GM crops and that the perception of benefits and risks, respectively, had positive and negative impacts on the self-reported behavioral intention of the respondents. The knowledge of the respondents regarding these crops had positive impacts on perception of benefits. The results showed that both managers and students worried about the food safety and impact of GM crops on human health while farmers worried about the environmental risks of GM crops. The results also revealed that those who are the most conscious about GM crops are more trusted. The findings also showed that the majority of the respondents hold a positive view of the potential of GM crops.     

Drought effects on the Iranian economy: a computable general equilibrium approach

Environment, Development and Sustainability - In the last two decades, recurring drought becomes a challenge for Iran’s economy, which is located in a drought-prone area, and it has been...     

Elimination of Cs+ from aquatic systems by an adsorbent prepared by immobilization of potassium copper hexacyanoferrate on the SBA-15 surface: kinetic,thermodynamic, and isotherm studies

Environmental Science and Pollution Research - For elimination of cesium from aqueous solutions, mesoporous SBA-15 was synthesized and employed as the support for immobilization of potassium copper...     

Uncertainties in vegetated buffer strip function in controlling phosphorus export from agricultural land in the Canadian prairies

Environmental Science and Pollution Research - Vegetated buffer strips (VBSs) are widely encouraged as a cost-effective strategy to address phosphorus (P) pollution associated with agricultural...     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

Evaluation of practicing safety features for hospital waste collection among Iran’s public hospitals

Journal of Material Cycles and Waste Management - Hospital waste management is imperative due to its impending health hazards. This study was meant to evaluate the strong safety awareness of...     

Effect of virtual water trade on freshwater pollution in trading partners: a systematic literature review

Environmental Science and Pollution Research - Systematic reviews are a more complete, repeatable, and less biased form of literature reviews leading to evidence-based conclusions. A systematic...