Continuous-flow column study of reductive dehalogenation of PCE upon bioaugmentation with the Evanite enrichment culture

A continuous-flow anaerobic column experiment was conducted to evaluate the reductive dechlorination of tetrachloroethene (PCE) in Hanford aquifer material after bioaugmentation with the Evanite (EV) culture. An influent PCE concentration of 0.09 mM was transformed to vinyl chloride (VC) and ethene (ETH) within a hydraulic residence time of 1.3 days. The experimental breakthrough curves were described by the one-dimensional two-site-nonequilibrium transport model. PCE dechlorination was observed after bioaugmentation and after the lactate concentration was increased from 0.35 to 0.67 mM. At the onset of reductive dehalogenation, cis-dichloroethene (c-DCE) concentrations in the column effluent exceeded the influent PCE concentration indicating enhanced PCE desorption and transformation. When the lactate concentration was increased to 1.34 mM, c-DCE reduction to vinyl chloride (VC) and ethene (ETH) occurred. Spatial rates of PCE and VC transformation were determined in batch-incubated microcosms constructed with aquifer samples obtained from the column. PCE transformation rates were highest in the first 5 cm from the column inlet and decreased towards the column effluent. Dehalococcoides cell numbers dropped from approximately 73.5% of the total Bacterial population in the original inocula, to about 0.5% to 4% throughout the column. The results were consistent with estimates of electron donor utilization, with 4% going towards dehalogenation reactions.     

Developing a master plan for hospital solid waste management: a case study

Disposal of about 1750tons of solid wastes per day is the result of a rapid population growth in the province of Khuzestan in the south west of Iran. Most of these wastes, especially hospital solid wastes which have contributed to the pollution of the environment in the study area, are not properly managed considering environmental standards and regulations. In this paper, the framework of a master plan for managing hospital solid wastes is proposed considering different criteria which are usually used for evaluating the pollution of hospital solid waste loads. The effectiveness of the management schemes is also evaluated. In order to rank the hospitals and determine the share of each hospital in the total hospital solid waste pollution load, a multiple criteria decision making technique, namely analytical hierarchy process (AHP), is used. A set of projects are proposed for solid waste pollution control and reduction in the proposed framework. It is partially applied for hospital solid waste management in the province of Khuzestan, Iran. The results have shown that the hospitals located near the capital city of the province, Ahvaz, produce more than 43% of the total hospital solid waste pollution load of the province. The results have also shown the importance of improving management techniques rather than building new facilities. The proposed methodology is used to formulate a master plan for hospital solid waste management.     

Project risk identification and assessment simultaneously using multi-attribute group decision making technique

The identification and assessment of project risks among potential risks can be considered a multi-attribute group decision making (MAGDM) problem including both quantitative and qualitative criteria. We extend the concept of safety to risk identification and assessment; this is to emphasize that the focus should not only be on the time and cost criteria, but also on the health, safety and environment (HSE) criterion. Conventional approaches to risk identification and risk assessment separately tend to be less effective in dealing with the imprecise of the risk assessment individually. The aim of this paper is to present a new methodology for identifying and assessing risks simultaneously by applying MAGDM technique. This paper includes a new procedure for classifying potential risks which it is named potential risk breakdown structure (PRBS) based on project work breakdown structure (WBS). Nominal group technique (NGT) is utilized for gathering potential risks. Obtained results have been applied in gas refinery plant construction successfully.     

Prenatal diagnosis of β-thalassemia in Southern Punjab,Pakistan

Pakistan has a large population of more than 150 million people with an overall carrier frequency of approximately 5.6% for β-thalassemia. Punjab is the largest province of the country having more than 50% of the population. The state of β-thalassemia is alarming as consanguinity is very high (>81%) and the literacy rate is low in South Punjab. A thalassemia prevention program is the need of the hour in this part of Pakistan. In this study, we initiated awareness, screening, and characterization of the mutations causing β-thalassemia as well as a genetic counseling program mainly in the districts of Faisalabad and D.G. Khan to establish prenatal diagnosis, a facility previously unavailable in this region for disease prevention. A total of 248 unrelated transfusion-dependent children and the available members of their families were screened to characterize the mutations and identify the carriers. Genetic counseling was provided to these families and prenatal diagnosis offered. In the samples analyzed, 11 β-thalassemia mutations and three hemoglobin variants were detected mainly by using the Monoplex and Multiplex ARMS-PCR. First-trimester prenatal diagnosis was carried out through chorionic villus sampling (CVS) in seven pregnancies at risk. As a result of our campaign, 145 carrier couples planning to have more children gave their consent to have retrospective prenatal diagnosis in every pregnancy in future. A cooperative trend and a positive attitude toward the prevention of β-thalassemia were noticed in the families with affected children and in the general population. Copyright © 2006 John Wiley & Sons, Ltd.     

A cross-validation of safety climate scale using confirmatory factor analytic approach

PROBLEM: Given the lack of a consistent factor structure of safety climate, this study tested the stability of a factor structure of a safety climate scale developed through an extensive literature review using confirmatory factor analytic approach and cross-validation. METHODS: A cross-sectional sample of 722 U.S. grain industry workers participated in the questionnaire survey. RESULTS: The safety climate scale developed through the generation of an item pool based on a table of specifications, subsequent scientific item reduction procedures, reviews from experts, and pilot test yielded adequate reliabilities for each dimension. Each item showed proper discriminative power based on both internal and external criteria. Criterion validity was manifested by the significant positive correlation of the scale with five criteria. Evidence of construct validity was provided by both exploratory and confirmatory factor analyses. Both calibration and validation samples supported a consistent factor structure. Management commitment and supervisor support were found to influence other dimensions of safety climate. DISCUSSION: This study provides an insight into the primary reason why previous attempts have failed to find a consistent factor structure of safety climate: No specification of the influence of management commitment and supervisor support on other dimensions of safety in their models. IMPACT ON INDUSTRY: The findings of this study provide a framework upon which accident prevention efforts can be effectively organized and underscore the importance of management commitment and supervisor support as they affect employee safety perceptions.     

Safety beliefs and safe behavior among midwestern college students

PROBLEM: This study investigated the impact of safety beliefs on safe behavior and the effect of age, gender, class standing, and geographic region on these beliefs and behaviors. It also compares the level of safety beliefs and safe behavior of Midwestern college students in 1993 to those in 2002. METHOD: A total of 1,059 undergraduate students at four Midwestern universities completed the 33-item questionnaire developed by Crowe (J. Saf. Res. 26 (1995) 187) during the spring semester of 2002. RESULTS: Significant main effects for gender and age on safety beliefs and safe behavior were found as well as a significant interaction between gender and age for both outcome variables. The regression model with the independent variables of personal responsibility and gender yielded a multiple R of.58, which explained 34% of the variance of the self-reported safe behavior. Midwestern college students in 2002 were found less safety-conscious in terms of self-reported safety beliefs and safe behavior than those in 1993. DISCUSSION: The findings indicate that safety education of adolescents and young adults in the United States has not been effective, at least for the last decade, or today's social and school environment is less conducive to the students' safe behavior and beliefs than a decade ago. IMPACT ON INDUSTRY: Proactive multidisciplinary approaches to enhance safe behavior and beliefs of young adults should be made based on critical evaluation of current approaches.     

Preparation of GO/MIL-101(Fe,Cu) composite and its adsorption mechanisms for phosphate in aqueous solution

Environmental Science and Pollution Research - In this study, MIL-101(Fe), MIL-101(Fe,Cu), and graphene oxide (GO)/MIL-101(Fe,Cu) were synthesized to compose a novel sorbent. The adsorption...     

Randomly selected order statistics in ranked set sampling: A less expensive comparable alternative to simple random sampling

Rank-based sampling designs are powerful alternatives to simple random sampling (SRS) and often provide large improvements in the precision of estimators. In many environmental, ecological, agricultural, industrial and/or medical applications the interest lies in sampling designs that are cheaper than SRS and provide comparable estimates. In this paper, we propose a new variation of ranked set sampling (RSS) for estimating the population mean based on the random selection technique to measure a smaller number of observations than RSS design. We study the properties of the population mean estimator using the proposed design and provide conditions under which the mean estimator performs better than SRS and some existing rank-based sampling designs. Theoretical results are augmented with some numerical studies and a real-life example, where we also study the performance of our proposed design under perfect and imperfect ranking situations.