Predicting Carbon Monoxide Concentrations in the Air of Pardis City,Iran, Using an Artificial Neural Network

To date, several methods have been proposed to explain the complex process of air pollution prediction. One of these methods uses neural networks. Artificial neural networks (ANN) are a branch of artificial intelligence, and because of their nonlinear mathematical structures and ability to provide acceptable forecasts, they have gained popularity among researchers. The goal of our study as documented in this article was to compare the abilities of two different ANNs, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks, to predict carbon monoxide (CO) concentrations in the air of Pardis City, Iran. For the study, we used data collected hourly on temperature, wind speed, and humidity as inputs to train the networks. The MLP neural network had two hidden layers that contained 13 neurons in the first layer and 25 neurons in the second layer and reached a mean bias error (MBE) of 0.06. The coefficient of determination (R²), index of agreement (IA), and the Nash–Scutcliffe efficiency (E) between the observed and predicted data using the MLP neural network were 0.96, 0.9057, and 0.957, respectively. The RBF neural network with a hidden layer containing 130 neurons reached an MBE of 0.04. The R², IA, and E between the observed and predicted data using the RBF neural network were 0.981, 0.954, and 0.979, respectively. The results provided by the RBF neural network had greater acceptable accuracy than was the case with the MLP neural network. Finally, the results of a sensitivity analysis using the MLP neural network indicated that temperature is the primary factor in the prediction of CO concentrations and that wind speed and humidity are factors of second and third importance when forecasting CO levels.     

Effects of soil amendments on the bioavailability of heavy metals from zinc mine tailings

A study was conducted to test the effects of soil amendments on the bioavailability of heavy metals in a zinc mine tailings containing soil to plants, using the Indian mustard plant (Brassica juncea) as a test organism. Zinc mine tailing containing soil was amended with humus soil (HS) and phosphatic clay (PC). The zinc mine tailing containing soil (ZMTS) was characterized for heavy metals. It was mixed with PC and HS, and four mixtures were prepared. The first mixture contained ZMTS, and served as a control. The second mixture contained ZMTS and PC in the ratio of 1:1 (w/w). The third mixture contained ZMTS and HS in the ratio of 1:1(w/w). The fourth mixture containing ZMTS, PC and HS in the ratio of (2:1:1) (w/w). A slight increase in the bioavailability of Pb, Cu, Zn and Mn was noticed with increase in the incubation time from 14 to 42 days. The bioavailability of Pb, Cu, Zn and Mn from ZMTS alone in Brassica plant was in the range of 94-99% up to 42 days. Addition of PC and HS to the ZMTS soil reduced the bioavailabilities of Pb by (15%), of Cu by (20%), of Zn by (20%) and of Mn by (25%) in the mustard plant. The data showed that PC in the presence of HS had a high affinity for the heavy metals in the order of Pb, Cu, Zn and Mn.     

Disturbance regimes,resilience, and recovery of animal communities and habitats in lotic ecosystems

Disturbance regime is a critical organizing feature of stream communities and ecosystems. The position of a given reach in the river basin and the sediment type within that reach are two key determinants of the frequency and intensity of flow-induced disturbances. We distinguish between predictable and unpredictable events and suggest that predictable discharge events are not disturbances. We relate the dynamics of recovery from disturbance (i.e., resilience) to disturbance regime (i.e., the disturbance history of the site). The most frequently and predictably disturbed sites can be expected to demonstrate the highest resilience. Spatial scale is an important dimension of community structure, dynamics, and recovery from disturbance. We compare the effects on small patches (⩽1 m²) to the effects of large reaches at the river basin level. At small scales, sediment movements and scour are major factors affecting the distribution of populations of aquatic insects or algae. At larger scales, we must deal with channel formation, bank erosion, and interactions with the riparian zone that will affect all taxa and processes. Our understanding of stream ecosystem recovery rests on our grasp of the historical, spatial, and temporal background of contemporary disturbance events.     

A RISK-BASED APPROACH FOR FLOOD CONTROL OPERATION OF A MULTIPURPOSE RESERVOIR1

ABSTRACT: Many approaches are available for operation of a multipurpose reservoir during flood season; one of them is allocation of storage space for flood control. A methodology to determine a reservoir operation policy based on explicit risk consideration is presented. The objective of the formulation is to maximize the reservoir storage at the end of a flood season while ensuring that the risk of an overflow is within acceptable limits. The Dynamic Programming technique has been used to solve the problem. This approach has been applied to develop operation policies for an existing reservoir. The performance of the policy was evaluated through simulation and was found to be satisfactory.     

Natural zeolites

Zeolites, a suite of porous, fine-grained minerals commonly found in certain near-surface, sedimentary rocks, have special physical and chemical properties that could make them valuable to farmers in developing countries. Zeolites have been used to improve soil fertility; develop slow-release fertilizers; improve animal waste disposal; and improve animal health. To date most research on zeolite deposits and their various applications has been undertaken by the industrialized nations. Some zeolite deposits, however, also exist in developing countries and the likelihood of the existence of additional deposits in those countries is high. However, thorough assessment of the mineralogy, geology, and various agricultural uses is still needed. Strengthening developing countries' geological surveys in non-metallic mineral exploration and assessment will improve the likelihood that the use of zeolites will reach their full potential in developing country agriculture.     

9,10-Phenanthrenequinone photoautocatalyzes its formation from phenanthrene, and inhibits biodegradation of naphthalene

Polycyclic aromatic hydrocarbons (PAHs) have earned considerable attention due to their widespread environmental distribution and toxicity. In the environment, PAHs decompose by a variety of biotic and abiotic pathways. In both polar and nonpolar environments, phenanthrene (Phe, a common, three-ring PAH) is converted by sunlight to more polar products such as 9,10-phenanthrenequinone (PheQ) and subsequent oxidation products such as the corresponding open-ring dicarboxylic acid product. Biodegradation of phenanthrene also usually leads to oxidative metabolites, and eventually ends in mineralization. Our experimental objective was to investigate the photodegradation of phenanthrene and determine the effect of reaction products such as PheQ on microbial biodegradation of two- and three-ring PAHs. Abiotic experiments were performed to examine the photolytic breakdown of Phe; Phe was converted to PheQ, which catalyzed its own formation. In biodegradation experiments PheQ (0.04-4 mg/L) caused marked inhibition of naphthalene (Nap) biodegradation by a Burkholderia species; Phe did not. Only 20% of the naphthalene was degraded in the presence of PheQ compared with 75% in the control culture with no PheQ added. No PAH-degrading cultures were able to use PheQ as sole carbon source; however, the Phe-degrading enrichment culture dominated by a Sphingomonas species was able to degrade PheQ cometabolically in the presence of Phe. These results may explain why photooxidized phenanthrene-containing mixtures can resist biodegradation.     

Biological assessment of bisphenol A degradation in water following direct photolysis and UV advanced oxidation

Endocrine disrupting compounds (EDCs) are exogenous environmental chemicals that can interfere with normal hormone function and present a potential threat to both environmental and human health. The fate, distribution and degradation of EDCs is a subject of considerable investigation. To date, several studies have demonstrated that conventional water treatment processes are ineffective for removal of most EDCs and in some instances produce multiple unknown transformation products. In this study we have investigated the use of direct photolysis with low-pressure (LP) Hg UV lamps and UV+hydrogen peroxide (H(2)O(2)) advanced oxidation process (AOP) for the degradation of a prototypic endocrine disrupter, bisphenol A (BPA), in laboratory water. Removal rates of BPA and formation of degradation products were determined by high performance liquid chromatography (HPLC) analysis. Changes in estrogenic activity were evaluated using both in vitro yeast estrogen screen (YES) and in vivo vitellogenin (VTG) assays with Japanese medaka fish (Oryzias latipes). Our results demonstrate that UV alone did not effectively degrade BPA. However, UV in combination with H(2)O(2) significantly removed BPA parent compound and aqueous estrogenic activity in vitro and in vivo. Removal rates of in vivo estrogenic activity were significantly lower than those observed in vitro, demonstrating differential sensitivities of these bioassays and that certain UV/AOP metabolites may retain estrogenic activity. Furthermore, the UV/H(2)O(2) AOP was effective for reducing larval lethality in treated BPA solutions, suggesting BPA degradation occurred and that the degradation process did not result in the production of acutely toxic intermediates.     

On the subjective experience and correlates of downtime at work: A mixed‐method examination

In the current paper, we studied downtime at work. Downtime represents a unique aspect of work time, as employees have low workload and more discretion about their activities but are still paid to be at work. Despite its prevalence and potentially significant implications for productivity and well‐being, the experience of downtime has not been a focus in the literature. To study this phenomenon, we first used a qualitative method involving 15 focus groups. Results from 95 employees showed that downtime is distinct from formal breaks and withdrawal behavior and is generally a negative subjective experience. Categories of antecedents of experience and downtime activities were classified. Next, to further explore the phenomenon, and based on Study 1 and relevant literature, we proposed several hypotheses and tested them using an experience sampling method. Results from 86 employees (across 5 workdays and 689 data points) indicated that the amount of downtime was negatively related to day level job satisfaction, job performance, and subjective health. The duration of relaxation activities during downtime mitigated the negative effects of downtime on fatigue. The effects of enjoyment level of the activities, job autonomy, work engagement, and boredom proneness were also examined. Implications, limitations, and future research are discussed.