Site selection and environmental risks assessment of medical solid waste landfill for the City of Kermanshah-Iran.

In this study, an integration of multi-criteria evaluation, geographic information system, and remote sensing techniques were used for site selection of medical waste landfills in Kermanshah, Iran. Also, an environmental risk assessment for the selected site has been conducted in order to minimize the possible hazardous. The GIS and remote sensing were used for acquiring and preparing layers and maps and the multi-criteria evaluation was used for setting aim, criteria selection, criteria weighting, and final decision making. The results showed that only 1.2% of the study area is scored high-suitable, while 90% of the area is considered unsuitable that makes this region critical for preservation. After further assessment and field visits, a suitable site was selected for landfilling. Environmental risk assessment showed that the selected site poses a low-level of risks to the environment and surrounding areas and this is because various environmental and health aspects have been considered in the site selection process.

Review on Metal-Based Nanoparticles: Role of Reactive Oxygen Species in Renal Toxicity.

The rapidly emerging field of nanotechnology has offered innovative discoveries. Due to a wide variety of nanotechnology applications in the industrial, medical, and consumptive products, the application of nanotechnology has received considerable attention in the past decades. Metal-based nanoparticles including metal and metal oxide nanoparticles are now widely utilized in different areas of nanotechnology, leading to an increase in human exposure to nonmaterial. Since the kidney is one of the major organs to remove a variety of potentially harmful substances, including nanoparticles (NPs), from living organisms and a large proportion of cardiac output reaches the kidney, this organ is susceptible to the toxin-induced renal injury. However, despite the extensive use of NPs, there is still a limited understanding of NP-mediated toxicity. The unique physicochemical properties of metal-based NPs not only make them highly desirable in a variety of applications but also enable them to induce changes at biological levels of cellular activities, including reactive oxygen species (ROS) generation. Since oxidative stress is a key factor of NP-induced injury, it is urgent to characterize the ROS response resulting from metal-based NPs. This review summarizes an assessment of the signaling pathways that are involved in the metal-based NP-induced nephrotoxicity, with a particular focus on ROS production along with the potential oxidative stress-dependent mechanism. However, available data show that metal-based NPs may have a severe impact on the renal system, but the exact molecular mechanism of nephrotoxicity is not fully understood. A highly effective strategy for a better understanding of the mechanism would be to collect an increasing volume of information about the exposure time, physicochemical characteristics of the engineered NPs, and the cellular effects. In order to achieve a thorough knowledge of ROS-dependent renal toxicity, both in vitro and in vivo studies should be considered.

Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran.

Land use change simulation is an important issue for its role in predicting future trends and providing implications for sustainable land management. Hybrid models have become a recognized strategy to inform decision-makers, but further attempts are needed to warrant the reliability of their projected results. In view of this, three hybrid models, including the cellular automata-Markov chain-artificial neural network, cellular automata-Markov chain-logistic regression, and Markov chain-artificial neural network, were applied to simulate land use change on the largest island in Iran, Qeshm Island. The Figure of Merit (FOM) was used to measure the modeling accuracy of the simulations, with the FOMs for the three models 6.7, 5.1, and 4.5, respectively. Consequently, the cellular automata-Markov chain-artificial neural network most precisely simulates land use change on Qeshm Island and is, thus, used to simulate land use change until 2026. The simulation shows that the incremental trend of the built-up class will continue in the coming years. Meanwhile, the areas of valuable ecosystems, such as mangroves, tend to decrease. Despite the protection plans for mangroves, these areas require more attention and conservation planning. This study demonstrates a referential example to select the proper land use models for informing planning and management in similar coastal zones.