Factors affecting incentive dependency of residents to participate in e-waste recycling: a case study on adoption of e-waste reverse supply chain in Iran

Modern societies face a dilemma called electronic waste (e-waste). This waste, which may contaminate the soil or cause unwanted impacts on human health when treated improperly, is one of the fastest growing waste streams in developed as well as developing countries and has brought great environmental impacts. Developing countries like Iran also face this modern waste management challenge. In order for more appropriate disposal or, if possible, recycling of this waste, more attention has been paid to reverse logistics as the most appropriate way to manage them. The first and most important action to address e-waste and implementation of reverse logistics is to persuade residents to bring back their obsolete electronic products. This paper attempts to understand significant factors affecting residents’ incentive dependency to participate in e-waste recycling program. Socioeconomic and demographic information of different residents is discussed by means of logistic regression for the first time in Iran. The results show that about 58.7 % of residents will participate even if no incentive is given. Household income, household size, education, e-waste concern level, and marital status are the significant factors affecting the incentive dependency of respondents.     

Engineering risk assessment for emergency disposal projects of sudden water pollution incidents

Without an engineering risk assessment for emergency disposal in response to sudden water pollution incidents, responders are prone to be challenged during emergency decision making. To address this gap, the concept and framework of emergency disposal engineering risks are reported in this paper. The proposed risk index system covers three stages consistent with the progress of an emergency disposal project. Fuzzy fault tree analysis (FFTA), a logical and diagrammatic method, was developed to evaluate the potential failure during the process of emergency disposal. The probability of basic events and their combination, which caused the failure of an emergency disposal project, were calculated based on the case of an emergency disposal project of an aniline pollution incident in the Zhuozhang River, Changzhi, China, in 2014. The critical events that can cause the occurrence of a top event (TE) were identified according to their contribution. Finally, advices on how to take measures using limited resources to prevent the failure of a TE are given according to the quantified results of risk magnitude. The proposed approach could be a potential useful safeguard for the implementation of an emergency disposal project during the process of emergency response.

     

Heavy metal concentrations in litteral sediments from the Beagle Channel,Tierra del Fuego,Argentina

For the first time the concentration of trace metals (Fe, Pb, Cu, Zn, Cd and total Hg) of sediments from the coastal zone of the Beagle Channel (Tierra del Fuego, in Southern Argentina) were measured. Atomic absorption spectrophotometry was utilized in order to determine the metal contents. The level of metals as observed in the sediments was recognized as the natural background, even though the use of normalization of lead, copper, and zinc to iron allowed the identification of the main sources of metal pollution for this environment. In order to develop future environmental monitoring programmes for the area of Ushuaia city and the Beagle Channel, the present results need to be considered.     

Transition index maps for urban growth simulation: application of artificial neural networks,weight of evidence and fuzzy multi-criteria evaluation

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.     

Effluent trading in river systems through stochastic decision-making process: a case study

Environmental Science and Pollution Research - The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two...     

Plant species affect colonization patterns and metabolic activity of associated endophytes during phytoremediation of crude oil-contaminated soil

Plants coupled with endophytic bacteria hold great potential for the remediation of polluted environment. The colonization patterns and activity of inoculated endophytes in rhizosphere and endosphere of host plant are among the primary factors that may influence the phytoremediation process. However, these colonization patterns and metabolic activity of the inoculated endophytes are in turn controlled by none other than the host plant itself. The present study aims to determine such an interaction specifically for plant-endophyte systems remediating crude oil-contaminated soil. A consortium (AP) of two oil-degrading endophytic bacteria (Acinetobacter sp. strain BRSI56 and Pseudomonas aeruginosa strain BRRI54) was inoculated to two grasses, Brachiaria mutica and Leptochloa fusca, vegetated in crude oil-contaminated soil. Colonization patterns and metabolic activity of the endophytes were monitored in the rhizosphere and endosphere of the plants. Bacterial augmentation enhanced plant growth and crude oil degradation. Maximum crude oil degradation (78 %) was achieved with B. mutica plants inoculated with AP consortium. This degradation was significantly higher than those treatments, where plants and bacteria were used individually or L. fusca and endophytes were used in combination. Moreover, colonization and metabolic activity of the endophytes were higher in the rhizosphere and endosphere of B. mutica than L. fusca. The plant species affected not only colonization pattern and biofilm formation of the inoculated bacteria in the rhizosphere and endosphere of the host plant but also affected the expression of alkane hydroxylase gene, alkB. Hence, the investigation revealed that plant species can affect colonization patterns and metabolic activity of inoculated endophytic bacteria and ultimately the phytoremediation process.     

Impact of Hazardous Exposure to Metals in the Nile and Delta Lakes on the Catfish, Clarias lazera

The impact of metal pollution in the Nile and Delta lakes was studied in Clarias lazera. Lake Edku is grouped as the site highest in metal concentrations. Compared to Lakes Maryût and Edku, the Nile stations displayed lower levels of metal contamination signifying their selection as reference sites. Metals were accumulated most by the liver, less by muscles and least by serum. Iron showed the highest bioconcentration factors (BCF) in liver, muscles or serum compared to other metals. Even after the refinement of the surrounding water, fish seem to uphold the metals that have been previously ingested. Mercury, in particular, seems to eventually reside in muscles rather than in liver. The positive relationship between total serum protein and metal contents may indicate the formation of specific metal-binding proteins. Meanwhile, serum hyperalbuminemia in polluted fish is probably a shock response towards the high stress index induced by metals. The hypothesis that most of serum copper is bound to ceruloplasmin is documented also in C. lazera. Moderate, but not extennsive, exposure to metals was quite stimulatory to liver alkaline phosphatase (AP) biosynthesis. AP could, thus, be considered as a promising bioindicator for assessing sublethal water intoxicosis.     

GIS aided prediction of CO2 emission dispersion from geothermal electricity production

CO₂ is the dominant constituent of non-condensable gases in the steam phase of most geothermal fluids. This paper attempts to present the results of a study conducted to develop prediction modeling of CO₂ dispersion in the surrounding atmosphere from a planned 50 MWe geothermal power plant prior to its production. Dispersion models are widely used for predicting future concentrations of environmental emissions on a range of geographic scales. The dispersion type for gases and their average removal rate depends on the meteorological conditions such as wind direction, wind speed, precipitation, atmospheric stability, and surface roughness and topography. Geographic Information System (GIS) capabilities were used for quality visualization of the model outputs and presenting an accurate numerical copy of the study area. The results by the prediction model show that the natural transfer of CO₂ will be from the power plant toward east and northeast and CO₂ concentration trends after the power plant utilization will be similar to the background conditions with minor changes. This dispersion test was carried out to validate and field test the GIS aided dispersion modeling approach described in the paper and the procedure may be applicable for other studies assessing the emission dispersion of pollutants from a point source.