Use of chemical coagulants to control fouling potential for wastewater membrane bioreactor processes.

Chemical coagulation with ferric chloride, alum, and an organic polymer were used to control the fouling potential of mixed liquors for submerged membrane bioreactor (MBR) processes in treating municipal wastewater. Their filterability was evaluated using a submerged hollow fiber ultrafiltration apparatus operated in constant permeate flux mode. The collected transmembrane pressures over filtration time were used to calculate the membrane fouling rates. The results showed that coagulation pretreatment can reduce fouling rates when MBRs were operated above the critical flux. Even though coagulation with the organic polymer formed larger mixed liquor suspended solids particles and had shorter time-to-filtration than those with ferric chloride and alum, the filterability for membrane filtration were similar, indicating that the membrane fouling in MBR systems was mainly controlled by the concentration of smaller colloidal particles.     

Nitrogen dioxide induced changes in level of free fatty acids, triglyceride, esterified fatty acid, ganglioside and lipase activity in the guinea pig brain.

The biochemical response to controlled inhalation of nitrogen dioxide (NO2) was studied in 18 male guinea pigs. Animals were exposed to 2.5, 5.0, and 10 ppm NO2 for 2h daily for 35 consecutive days, and the results compared with six control animals exposed to filtered air for 2h daily for same period. Five biochemical parameters, including triglyceride, free fatty acids, esterified fatty acid, ganglioside and lipase activity were measured immediately after the last day of exposure. At 2.5 ppm NO2 inhalation no significant changes occurred in any region of the central nervous system (CNS). While as the dose concentration was increased to 5 and 10 ppm nitrogen dioxide, significant dose-related alteration were observed in the levels of triglyceride, free fatty acid, esterified fatty acid, ganglioside and lipase activity in the different regions of the guinea pig CNS.     

Design and cognitive evaluation of 6 dynamic lane departure warning symbols

Objective: Lane departure, caused by inattention, distraction, drowsiness, or any unusual driver behavior, is a typical risk threatening the driver as well as other road users. Accurate perception of such situations through effective warnings would help drivers to avoid serious consequences. With regard to critical functions of warning symbols for risk communication, the present study focused on providing effective and easily perceivable symbols, compatible with human cognitive capabilities. Thus, the main purpose of the present study was to design and cognitively appraise 6 newly designed dynamic symbols, candidates for a new type of lane departure warning system.

Methods: Simplicity, familiarity, concreteness, meaningfulness, and semantic closeness were the major assessment criteria, defining cognitive features by the earlier researchers in the field. A total number of 187 driving license applicants, with a mean age of 20.58 years (SD = 3.20), participated in the present survey. The participants rated cognitive features of the 6 dynamic symbols along a 0–100 scale.

Results: Significant main effect of the element factor type of the designed symbols on rating cognitive features revealed that the existence of car element was the best predictor for illustrating lane departure. The interaction of both element factor and location of element factor significantly affected the ratings. However, the location of element factor did not solely have any strong effect on the ratings. The results also demonstrated that semantic closeness received the highest overall mean score across symbols (M = 61.80), especially within the symbols that include the car element (M = 75.67). Moreover, a significant difference was observed between the average ratings of the cognitive features, despite the fact that a significant correlation was found between cognitive features.

Conclusion: The most considerable result of the current study was the match between the symbol with the highest ratings and the International Organization for Standardization (ISO)-related icon in appearance. Because previous studies demonstrated a strong correlation between comprehension scores of the symbol and both semantic closeness and meaningfulness, high-level comprehensibility of the best ranked symbol is expected.     

Spatial and temporal variability of fluoride concentrations in groundwater resources of Larestan and Gerash regions in Iran from 2003 to 2010

Environmental Geochemistry and Health - There is discrepancy about intervals of fluoride monitoring in groundwater resources by Iranian authorities. Spatial and temporal variability of fluoride in...     

Estimation of maximum scour depths at upstream of front and rear piers for two in-line circular columns

Previous investigations indicate that scour around bridge piers is one of the most important factors for the failure of waterway bridges. Hence, it is essential to determine the accurate scour depth around the bridge piers. Most of the previous studies were based on scour around a single pier; however, in practice, new bridges are usually wide and then piers comprise two circular piers aligned in the flow direction that together support the loading of the structure. In this study, the effect on maximum scour depth of the spacing between two piers aligned in the flow direction was investigated experimentally under clear water scour conditions. The results show that the maximum scour depth at upstream of the front pier occurs when the spacing between the two piers is 2.5 times the diameter of the pier. Two semi empirical equations have been developed to predict the maximum scour depth at upstream of both front and rear piers as a function of the spacing between the piers, in terms of a pier-spacing factor. If the new equations for the pier-spacing factor are used with some of the existing equations for scour at a single pier, the predicted scouring depths are in good agreement with observed results. The S/M equation exhibited the best performance among the various equations tested and was recommended for use in prediction of the equilibrium scour depth. The findings of this study can be used to facilitate the positioning of piers when scouring is a design concern.     

Estimation of Aerobic Capacity and Determination of Its Associated Factors Among Male Workers of Industrial Sector of Iran

Introduction. The aim of this study was to estimate maximal aerobic capacity (V_O2max), to determine its associated factors among workers of industrial sector of Iran and to develop a regression equation for subjects’ V_O2max. Methods. In this study, 500 healthy male workers employed in Shiraz industries participated voluntarily. The subjects’ V_O2max was assessed with the ergocycle test according to the Åstrand protocol. Required data was collected with a questionnaire covering demographic details (i.e., age, job tenure, marital status, education, nature of work, shift work, smoking and weekly exercises). Results. The subject’s mean V_O2max was 2.69 ± 0.263 L/min. The results showed that there was an association between V_O2max and age, BMI, hours of exercise and smoking, but there was no association between V_O2max and height, weight, nature of work and working schedule. On the basis of the results, regression equations were developed to estimate V_O2max. Conclusion. Final regression equation developed in this study may be used to estimate V_O2max reliably without the need to use other laboratory instruments for aerobic measurement.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Refugees,water balance,and water stress: Lessons learned from Lebanon

Ambio - The Syrian crisis caused a massive influx of displaced people into neighboring countries, with Lebanon hosting the highest per capita number of refugees (3:10). Water remains the most...     

Mechanistic aspects of poly(ethylene terephthalate) recycling–toward enabling high quality sustainability decisions in waste management

Environmental Science and Pollution Research - Since plastic waste pollution is a severe environmental concern in modern life, the demand for recycling poly(ethylene terephthalate) (PET) has...     

On integration of policies for climate and global change

Currently envisaged mitigation of greenhouse gases (GHG) emissions will be insufficient to appreciably limit climate change and its impacts. Adaptation holds the promise of ameliorating the impacts on a small subset of systems being affected. There is no question that both will be needed. However, climate change is only part of a broader multi-stress setting of global through to local changes. Privileging climate related policies over other concerns leads to tragic outcomes. Climate policies need to be designed for and integrated into this broader and challenging context. This paper focuses on placing climate change within the broader context of global change and the importance of aligning climate policy objectives with the myriad other policies that still need to be implemented if our primary goal is improving human welfare rather than limiting our focus to climate change and its impacts.