97 resultados para Waste minimization


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A microwave reactor system was investigated as a potential technique to maximize sugar yield for the hydrolysis of municipal solid waste for ethanol production. Specifically, dilute acid hydrolysis of a-cellulose and waste cellulosic biomass (grass clippings) with phosphoric acid was undertaken within the microwave reactor system. The experimental data and reaction kinetic analysis indicate that the use of a microwave reactor system can successfully facilitate dilute acid hydrolysis of cellulose and waste cellulosic biomass, producing high yields of total sugars in short reaction times. The maximum yield of reducing sugars was obtained at 7.5% (w/v) phosphoric acid and 160 degrees C, corresponding to 60% of the theoretical total sugars, with a reaction time of 5 min. When using a very low acid concentration (0.4% w/v) for the hydrolysis in the microwave reactor, it was found that 10 g of total sugars/100 g dry mass was produced, which is significant considering the low acid concentration. When hydrolyzing grass clippings using the microwave reactor, the optimum conditions were an acid concentration of 2.5% (w/v), 175 degrees C with a 15 min reaction time, giving 18 g/100 g dry mass of total sugars, with xylose being the sugar with the highest yield. It was observed that pentose sugars were more easily formed but also more easily degraded, these being significantly affected by increases in acid concentration and temperature. Kinetic modeling of the data indicated that the use of microwave heating may account for an increase in reaction rate constant, k(1), found in this study in comparison with conventional systems described in the literature.

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This paper compares the Random Regret Minimization and the Random Utility Maximization models for determining recreational choice. The Random Regret approach is based on the idea that, when choosing, individuals aim to minimize their regret – regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. The Random Regret paradigm, recently developed in transport economics, presents a tractable, regret-based alternative to the dominant choice paradigm based on Random Utility. Using data from a travel cost study exploring factors that influence kayakers’ site-choice decisions in the Republic of Ireland, we estimate both the traditional Random Utility multinomial logit model (RU-MNL) and the Random Regret multinomial logit model (RR-MNL) to gain more insights into site choice decisions. We further explore whether choices are driven by a utility maximization or a regret minimization paradigm by running a binary logit model to examine the likelihood of the two decision choice paradigms using site visits and respondents characteristics as explanatory variables. In addition to being one of the first studies to apply the RR-MNL to an environmental good, this paper also represents the first application of the RR-MNL to compute the Logsum to test and strengthen conclusions on welfare impacts of potential alternative policy scenarios.

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The survival of pathogenic bacteria was investigated during the operation of a full-scale anaerobic digester which was fed daily and operated at 28-degrees-C. The digester had a mean hydraulic retention time of 24 d. The viable numbers of Escherichia coli, Salmonella typhimurium, Yersinia enterocolitica, Listeria monocytogenes and Campylobacter jejuni were reduced during mesophilic anaerobic digestion. Escherichia coli had the smallest mean viable numbers at each stage of the digestion process. Its mean T90 value was 76-9 d. Yersinia enterocolitica was the least resistant to the anaerobic digester environment; its mean T90 value was 18.2 d. Campylobacter jejuni was the most resistant bacterium; its mean T90 value was 438.6 d. Regression analysis showed that there were no direct relationships between the slurry input and performance of the digester and the decline of pathogen numbers during the 140 d experimental period.

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This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

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A new model to explain animal spacing, based on a trade-off between foraging efficiency and predation risk, is derived from biological principles. The model is able to explain not only the general tendency for animal groups to form, but some of the attributes of real groups. These include the independence of mean animal spacing from group population, the observed variation of animal spacing with resource availability and also with the probability of predation, and the decline in group stability with group size. The appearance of "neutral zones" within which animals are not motivated to adjust their relative positions is also explained. The model assumes that animals try to minimize a cost potential combining the loss of intake rate due to foraging interference and the risk from exposure to predators. The cost potential describes a hypothetical field giving rise to apparent attractive and repulsive forces between animals. Biologically based functions are given for the decline in interference cost and increase in the cost of predation risk with increasing animal separation. Predation risk is calculated from the probabilities of predator attack and predator detection as they vary with distance. Using example functions for these probabilities and foraging interference, we calculate the minimum cost potential for regular lattice arrangements of animals before generalizing to finite-sized groups and random arrangements of animals, showing optimal geometries in each case and describing how potentials vary with animal spacing. (C) 1999 Academic Press.</p>