Regression models for exceedance data via the full likelihood

Many situations in practice require appropriate specification of operating characteristics under extreme conditions. Typical examples include environmental sciences where studies include extreme temperature, rainfall and river flow to name a few. In these cases, the effect of geographic and climatological inputs are likely to play a relevant role. This paper is concerned with the study of extreme data in the presence of relevant auxiliary information. The underlying model involves a mixture distribution: a generalized Pareto distribution is assumed for the exceedances beyond a high threshold and a non-parametric approach is assumed for the data below the threshold. Thus, the full likelihood including data below and above the threshold is considered in the estimation. The main novelty is the introduction of a regression structure to explain the variation of the exceedances through all tail parameters. Estimation is performed under the Bayesian paradigm and includes model choice. This allows for determination of higher quantiles under each covariate configuration and upper bounds for the data, where appropriate. Simulation results show that the models are appropriate and identifiable. The models are applied to the study of two temperature datasets: maxima in the U.S.A. and minima in Brazil, and compared to other related models.     

Procedures for estimation of modelling uncertainty in air quality assessment

The main objectives of this work focus, firstly, on a review of the current existent methodologies to estimate air quality modelling uncertainty, and, secondly, in the preparation of guidelines for modelling uncertainty estimation, which can be used by local and regional authorities responsible for air quality management. From the application exercise, it was concluded that it is possible to define a subset of statistical parameters able to reproduce the general uncertainties estimation. Concerning the quality indicators defined by EU directives, the results show that the legislated uncertainty estimation measures are ambiguous and inadequate in several aspects, mainly in what concerns the error measures for hourly and daily indicators based on the highest observed concentration. A relative error at the percentile correspondent to the allowed number of exceedances of the limit value was suggested and tested, showing that is a more robust and appropriate parameter for model performance evaluation.     

Encapsulation of Nerol Oil in Polycaprolactone Polymer and Stability Evaluation

Journal of Polymers and the Environment - The objective of this study was to obtain and characterize Nerol essential oil encapsulated in PCL. The miniemulsion and solvent evaporation method was...     

Toxicity of new pyrethroid in pest insects Asciamonuste and Diaphania hyalinata,predator Solenopsis saevissima and stingless bee Tetragonisca angustula

There is increasing demand for new products for vegetable pest management. Thus, the aim of this study was to assess the toxicity of pyrethroids with acid moiety modifications to measure the insecticidal activity of these compounds on the lepidopteran vegetable pests Diaphania hyalinata (L.) (Lepidoptera: Pyralidae) and Asciamonuste (Latreille) (Lepidoptera: Pieridae) and evaluate their selectivity for the predatory ant Solenopsis saevissima (F. Smith) (Hymenoptera: Formicidae) and pollinator Tetragonisca angustula (Latreille) (Hymenoptera: Apidae: Meliponinae). Racemic mixtures of five new pyrethroids (30 µg molecule mg^?1 insect body weight) resulted in high (100%) and rapid (stable LD₅₀ after 12 h) mortality in D. hyalinata and A. monuste. In A. monuste, the trans-pyrethroid [12] isomer showed similar toxicity to permethrin. For D. hyalinata, the trans-pyrethroid [9] isomer and cis-pyrethroid [10] isomer were as toxic as permethrin. Due to their low selectivity, these new pyrethroids should be applied on the basis of ecological selectivity principles to minimize impacts on nontarget organisms S. saevissima and T. angustula.     

Demystifying the challenges and barriers to manage,develop, and transfer clean and green technologies in Brazilian academic research groups: Some empirical evidence

This work presents empirical evidence of the main challenges in managing/leading academic research groups on clean and green technologies in Brazilian universities. We also present evidence about the main barriers to the effective creation of innovation and technology transfer of these clean and green technologies. Empirical evidence come from PhD researchers/academics who lead/manage official research groups on clean (environmental, green) technologies. Results show the following: (a) The main challenges of managing research groups are the lack of an innovative culture, the lack of partnership with an industrial sector, and the necessity of keeping laboratories updated; (b) the main barriers to innovation and technology transfer are difficulties in not having enough researchers and staff members, assessments of academic performance that do not consider innovation, and an uncertain national legislation on clean technology. Based on these and others’ findings, we suggest that policymakers working on clean and green technologies pay attention to act and develop initiatives focusing on the following: providing direct financial support for laboratory improvement, linking academics and practitioners from the industrial sector, and providing training and development programs on clean and green technologies’ legislation and financial issues, such as the payoff of clean and green technologies and opportunities from green investors.     

Electrochemical wastewater treatment: influence of the type of carbon and of nitrogen on the organic load removal

Boron-doped diamond (BDD) and Ti/Pt/PbO₂ anodes were utilized to perform the electrodegradation of synthetic samples containing humic acid in the presence of different organic and inorganic carbon-containing and nitrogen-containing compounds. The influence of the chloride ion in the degradation process of the different synthetic samples was also assessed. The results showed that the anodic oxidation process can efficiently degrade recalcitrant compounds such as humic acid. The presence of carbonate in solution enhances the nitrogen removal, whereas it hinders the oxidation of the organic compounds. When organic nitrogen is present, it is converted to NH₄ ⁺, which in turn is oxidized to nitrate and to volatile nitrogen compounds. Hydroxyl radicals are more prone to oxidize the organic nitrogen than the ammonium nitrogen. The presence of chloride enhances the organic matter and nitrogen removal rates, BDD being the anode material that yields the highest removals.     

Valorization of EVA waste from footwear industry as natural aggregates substitutes in mortar: the effect of granulometry

Journal of Material Cycles and Waste Management - The increased consumption of polymers and the consequent generation of waste requires the development of efficient recycling strategies. In this...