Effect of nuclear power on CO<Subscript>2</Subscript> emission from power plant sector in Iran

Introduction  

It is predicted that demand for electricity in Islamic Republic of Iran will continue to increase dramatically in the future due to the rapid pace of economic development leading to construction of new power plants. At the present time, most of electricity is generated by burning fossil fuels which result in emission of great deal of pollutants and greenhouse gases (GHG) such as SO₂, NO_x, and CO₂. The power industry is the largest contributor to these emissions. Due to minimal emission of GHG by renewable and nuclear power plants, they are most suitable replacements for the fossil-fueled power plants. However, the nuclear power plants are more suitable than renewable power plants in providing baseload electricity. The Bushehr Nuclear Power Plant, the only nuclear power plant of Iran, is expected to start operation in 2010. This paper attempts to interpret the role of Bushehr nuclear power plant (BNPP) in CO₂ emission trend of power plant sector in Iran.     

The association between air pollution and cancers: controversial evidence of a systematic review

Environmental Science and Pollution Research - There are inconsistent reports on the association between air pollution and cancers. This systematic review was, therefore, conducted to ascertain the...     

Simultaneous derivatization and extraction of nitrophenols in soil and rain samples using modified hollow-fiber liquid-phase microextraction followed by gas chromatography–mass spectrometry

A simple and sensitive method based on a modified hollow-fiber liquid-phase microextraction followed by gas chromatography–mass spectrometry has been successfully developed for the extraction and simultaneous derivatization of some nitrophenols (NPs) in soil and rain samples. Microwave-assisted solvent extraction was used for the extraction of NPs from the soil, while the rain sample was directly applied to the previously mentioned method. Briefly, in this method, the analytes were extracted from aqueous samples into a thin layer of organic solvent (dodecane?+?10 % tri-n-octylphosphine oxide) sustained in the pores of a porous hollow fiber. Then, they were back-extracted using a small volume of organic acceptor solution (25 μl; 10 mg/L N-methyl-N-(trimethylsilyl)trifluoroacetamide, as derivatization reagent, in acetonitrile) that was located inside the lumen of the hollow fiber. Under the optimized extraction conditions, enrichment factors of 255 to 280 and limits of detection of 0.1 to 0.2 μg/L (S/N?=?3) with dynamic linear ranges of 1–100 μg/L were obtained for the analytes. The accuracy of the approach was tested by the relative recovery experiments on spiked samples, with results ranging from 93 to 113 %. The method was shown to be rapid, cost-effective, and potentially interesting for screening purposes.     

Assessing Multi-site Drought Connections in Iran Using Empirical Copula

Drought is a multi-dimensional natural hazard with stochastic characteristics usually related to each other. Separate univariate statistical models cannot capture the important relationships among drought characteristics, that is, severity and duration. In this study, an empirical copula is employed to construct a bivariate model of droughts, where droughts are defined as continuously negative standardized precipitation index (SPI) periods with one SPI value reaching ?1 or less. Bivariate frequency analyses in terms of recurrence intervals are performed using the established empirical copula-based bivariate drought model. The inter-connection among different regions of droughts is explored by a lower tail dependence coefficient. A nonparametric estimation based on an empirical copula is employed pairwisely to calculate the lower tail dependence coefficient among stations. The proposed method is applied to six rainfall gauge stations in Iran to explore drought properties of single sites as well as the inter-connection among multi-sites. The results show that greater mean drought severity and duration are associated with the least arrival rate of drought events, which occurs at the Ahwaz station. The tail dependence analysis reveals that distance between stations is not a key parameter. Generally, the Ahwaz and Isfahan stations have the highest probability of simultaneous droughts among the six stations.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Biodegradable Composite Foams of PLA and PHBV Using Subcritical CO<Subscript>2</Subscript>

One key strategy for increasing the application potential for biodegradable plastics lies in improving the physical and mechanical characteristics, which can be attained by inducing a cellular morphology in the pure polymer with the aid of a blowing agent, as well as by blending two or more polymers with the desirable properties. This paper examines the effect that blending two biodegradable polymers has on the thermal properties and morphology of the resultant foams blown with carbon dioxide (CO₂). Polylactic acid (PLA), polyhydroxybutyrate-co-valerate (PHBV) and blends of both were foamed and characterized in terms of thermal characteristics, relative density, cell size, and foam morphology. The results indicate that although PLA and PHBV are immiscible, the presence of small quantities of PHBV (25 wt%) could lead to low density foams with finer, more uniform cells. Furthermore, the crystallinity of PHBV was found to be unaffected by the presence of PLA in the composite, which supports the immiscibility of PLA and PHBV.     

Organochlorine pesticide and polychlorinated biphenyl residues in feathers of birds from different trophic levels of South-West Iran

Persistent organochlorine pesticides (OCPs), such as dichlorodiphenyltrichloroethane (DDT) and its metabolites, hexachlorobenzene (HCB), alpha, beta and gamma-hexachlorocyclohexane (HCH) isomers, together with polychlorinated biphenyl (PCB) congeners (IUPAC Nos. 28, 52, 101, 138, 153 and 180), were determined in tail feathers from 37 birds belonging to 18 species, all originating from the South-West of Iran (Khuzestan, coast of the Persian Gulf). This is the first report on organochlorine contaminants in feathers from museum collections and it is an indication of the concentrations of OCPs and PCBs in the past (1991-1996). Median concentrations of HCHs, DDTs, PCBs and HCB were 22, 14, 11 and 10 ng/g feather, respectively. Significant correlations (p<0.05) were calculated between OCPs (except HCB) and PCBs in the bird feathers. p,p'-DDE and gamma-HCH were the most abundant OCPs, while CB 180, CB 138 and CB 101 were the predominant PCB congeners in almost all species. Significant differences (p<0.05) in the mean concentrations of DDTs and PCBs were detected among species grouped according to their feeding habits. Levels of DDTs and PCBs were highest in the carnivorous species and lowest in the herbivorous species. Levels of OCPs and PCBs in feathers of bids in the 1990s were generally below the thresholds reported to affect reproduction.     

An improved optimization model for predicting Pb recovery efficiency from residual of liberator cells: a hybrid of support vector regression and modified tunicate swarm algorithm

Journal of Material Cycles and Waste Management - In this study, a hybrid of support vector regression and a modified tunicate swarm algorithm (SVR-MTSA) strategy is developed to optimize the...     

The detection of drowsiness using a driver monitoring system

Abstract

Objective: Drowsiness is a major cause of driver impairment leading to crashes and fatalities. Research has established the ability to detect drowsiness with various kinds of sensors. We studied drowsy driving in a high-fidelity driving simulator and evaluated the ability of an automotive production-ready driver monitoring system (DMS) to detect drowsy driving. Additionally, this feature was compared to and combined with signals from vehicle-based sensors.

Methods: The National Advanced Driving Simulator was used to expose drivers to long, monotonous drives. Twenty participants drove for about 4?h in the simulator between 10 p.m. and 2 a.m. They were allowed to use cruise control and traffic was sparse and semirandom, with both slower- and faster-moving vehicles. Observational ratings of drowsiness (ORDs) were used as the ground truth for drowsiness, and several dependent measures were calculated from vehicle and DMS signals. Drowsiness classification models were created that used only vehicle signals, only driver monitoring signals, and a combination of the 2 sources.

Results: The model that used DMS signals performed better than the one that used only vehicle signals; however, the combination of the two performed the best. The models were effective at discriminating low levels of drowsiness from moderate to severe drowsiness; however, they were not effective at telling the difference between moderate and severe levels. A binary model that lumped drowsiness into 2 classes had an area under the receiver operating characteristic (ROC) curve of 0.897.

Conclusions: Blinks and saccades have been shown to be predictive of microsleeps; however, it may be that detection of microsleeps and lane departures occurs too late. Therefore, it is encouraging that the model was able to distinguish mild from moderate drowsy driving. The use of automation may make vehicle-based signals useless for characterizing driver states, providing further motivation for a DMS. Future improvements in impairment detection systems may be expected through a combination of improved hardware, physiological measures from unobtrusive sensors and wearables, and the intelligent integration of environmental variables like time of day and time on task.     

Impact of roof rain water harvesting of runoff capture and household consumption

Environmental Science and Pollution Research - In recent years, the occurrence of floods is one of the most important challenges facing in Hamadan city. In the absence/inefficiency of urban...