Uncertain spatial reasoning of environmental risks in GIS using genetic learning algorithms

Modeling the impact of air pollution is one of the most important approaches for managing damages to the ecosystem. This problem can be solved by sensing and modeling uncertain spatial behaviors, defining topological rules, and using inference and learning capabilities in a spatial reasoning system. Reasoning, which is the main component of such complex systems, requires that proper rules be defined through expert judgments in the knowledge-based part. Use of genetic fuzzy capabilities enables the algorithm to learn and be tuned to proper rules in a flexible manner and increases the preciseness and robustness of operations. The main objective of this paper was to design and evaluate a spatial genetic fuzzy system, with the goal of assessing environmental risks of air pollution due to oil well fires during the Persian Gulf War. Dynamic areas were extracted and monitored through images from NOAA, and the data were stored in an efficient spatial database. Initial spatial knowledge was determined by expert consideration of the application characteristics, and the inference engine was performed with genetic learning (GL) algorithms. Finally, GL (0.7 and 0.03), GL (0.7 and 0.08), GL (0.98 and 0.03), GL (0.98 and 0.08), and Cordon learning methods were evaluated with test and training data related to samples extracted from Landsat thematic mapper satellite images. Results of the implementation showed that GL (0.98, 0.03) was more precise than the other methods for learning and tuning rules in the concerned application.     

Effects of aerobic exercise on histopathology and toxicology of ZnO and nano ZnO in male rats

The effects of four weeks of aerobic exercise on histopathological and toxicological effects induced by nano ZnO and ZnO powders in male rats were evaluated. Tissue sections of liver and kidneys of ZnO and nano ZnO rats showed some histopathological changes, which were partly reverted by exercise. ZnO and nano ZnO treatments caused an increase in the level of tumor necrosis factor-α, while the mean of Interleukin 10 was declined. Exercise training enhanced the mean value of and declined mean level of in rats treated with ZnO and nano ZnO. The ZnO and ZnO groups demonstrated the highest means of insulin resistance, low density lipoprotein, cholesterol, triglyceride levels and lower mean value of compared to the other groups, while exercise resulted in improvement in mean of these factors.     

Transformation of hydroxylated derivatives of 2,5-dichlorobiphenyl and 2,4,6-trichlorobiphenyl by Burkholderia xenovorans LB400

The polychlorinated biphenyl (PCB)-degrading bacterium, Burkholderia xenovorans LB400, was capable of transforming three hydroxylated derivatives of 2,5-dichlorobiphenyl (2,5-DCB) (2′-hydroxy- (2′-OH-), 3′-OH-, and 4′-OH-2,5-DCB) when biphenyl was used as the carbon source (i.e., biphenyl pathway-inducing condition), although only 2′-OH-2,5-DCB was transformed when the bacterium was growing on succinate (i.e., condition non-inductive of the biphenyl pathway). On the contrary, hydroyxlated derivatives of 2,4,6-trichlorobiphenyl (2,4,6-TCB) (2′-OH-, 3′-OH-, and 4′-OH-2,4,6-TCB) were not significantly transformed by B. xenovorans LB400, regardless of the carbon source used. Gene expression analyses showed a clear correlation between the transformation of OH-2,5-DCBs and expression of genes of the biphenyl pathway. The PCB metabolite, 2,5-dichlorobenzoic acid (2,5-DCBA), was produced following the transformation of OH-2,5-DCBs. 2,5-DCBA was not further transformed by B. xenovorans LB400. The present study is significant because it provides evidence that PCB-degrading bacteria are capable of transforming hydroxylated derivatives of PCBs, which are increasingly considered as a new class of environmental contaminants.     

Hydroxylated polychlorinated biphenyls in the environment: sources,fate, and toxicities

Hydroxylated polychlorinated biphenyls (OH-PCBs) are produced in the environment by the oxidation of PCBs through a variety of mechanisms, including metabolic transformation in living organisms and abiotic reactions with hydroxyl radicals. As a consequence, OH-PCBs have been detected in a wide range of environmental samples, including animal tissues, water, and sediments. OH-PCBs have recently raised serious environmental concerns because they exert a variety of toxic effects at lower doses than the parent PCBs and they are disruptors of the endocrine system. Although evidence about the widespread dispersion of OH-PCBs in various compartments of the ecosystem has accumulated, little is currently known about their biodegradation and behavior in the environment. OH-PCBs are, today, increasingly considered as a new class of environmental contaminants that possess specific chemical, physical, and biological properties not shared with the parent PCBs. This article reviews recent findings regarding the sources, fate, and toxicities of OH-PCBs in the environment.     

Emission factor estimation for oil and gas facilities

Fugitive emission rate quantification in an oil and gas facility is an important step of risk management. There are several studies conducted by the United States Environmental Protection Agency (USEPA) and American Petroleum Institute (API) proposing methods of estimating emission rates and factors. Four major approaches of estimating these emissions, in the order of their accuracy, are: average emission factor approach, screening ranges emission factor approach, USEPA correlation equation approach, and unit-specific correlation equation approach. The focus of this study is to optimize the USEPA correlation equations to estimate the emission rate of different units in an oil and gas facility. In the developed methodology, the data available from USEPA (1995) is used to develop new sets of equations. A comparison between USEPA correlation equations and the proposed equations is performed to define the optimum sets of equations. It is observed that for pumps, flanges, open-ended lines, and others, the proposed developed equations provide a better estimation of emission rate, whereas for other sources, USEPA equations supply the better estimate of emission rate.     

Up to 399 mV bioelectricity generated by a rice paddy-planted microbial fuel cell assisted with a blue-green algal cathode

Environmental Chemistry Letters - Microbial fuel cells are used as an alternative source of energy and for microbial degradation of waste and pollutants. Different types of microbial fuel cells...     

A spatial econometric analysis of convergence in global environmental performance

Environmental Science and Pollution Research - This study intends to test the presence of β-convergence in the global Environmental Performance (EP). For this purpose, spatial Green Solow...