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We investigated how a community of microbial decomposers adapted to a reference site responds to a sudden decrease in the water quality. For that, we assessed the activity and diversity of fungi and bacteria on decomposing leaves that were transplanted from a reference (E1) to a polluted site (E2), and results were compared to those from decomposing leaves either at E1 or E2. The two sites had contrasting concentrations of organic and inorganic nutrients and heavy metals in the stream water. At E2, leaf decomposition rates, fungal biomass, and sporulation were reduced, while bacterial biomass was stimulated. Fungal diversity was four times lower at the polluted site. The structure of fungal community on leaves decomposing at E2 significantly differed from that decomposing at E1, as indicated by the principal response curves analysis. Articulospora tetracladia, Anguillospora filiformis, and Lunulospora curvula were dominant species on leaves decomposing at E1 and were the most negatively affected by the transfer to the polluted site. The transfer of leaves colonized at the reference site to the polluted site reduced fungal diversity and sporulation but not fungal biomass and leaf decomposition. Overall, results suggest that the high diversity on leaves from the upstream site might have mitigated the impact of anthropogenic stress on microbial decomposition of leaves transplanted to the polluted site.

This work presents a crude bioethanol fueled integrated power system for backup and off-grid applications. The system is based on ethanol steam reformation to hydrogen that is used in polymer electrolyte fuel cells to produce electricity. We introduce the system design and overall system specifications, and report the experimental process of defining specifications for the produced hydrogen quality, a key variable affecting the final system cost, efficiency and durability. Results from development of individual subsystems are also presented together with discussion on the complete system integration.

This chapter discusses the present scenario and market trend of regenerated cellulosic fibers, and the properties of principal fibers existing in the market as well as some new fibers recently developed and yet to be explored. Production technologies of these fibers are discussed and their potential applications are presented. Various sustainability issues related to the production of regenerated cellulosic fibers are dealt within this chapter. The last section discusses the results of research studies conducted to assess the environmental impacts and sustainability aspects of regenerated cellulose fibers. Serie: Textile science and clothing technology, ISSN 2197-9863

A Life Cycle Assessment (LCA) with focus on carbon footprint, followed by Life Cycle Costing (LCC) of municipal solid waste (MSW) management were conducted in a residential area of a medium-sized European city of 80,000 inhabitants. The initial results showed high environmental impacts and lack of economic sustainability, due to the high amounts of waste landfilled, the low extent of separate collection, low performance of mechanical-biological treatment as well as absence from alternatives to landfilling of non-recyclable materials. Taking this result as a baseline scenario, three improvement.s were tested with the aim of turning the carbon footprint of the local MSW management system into a neutral value: (i) increased separate collection of recyclables, (ii) enhanced biogas production and (iii) refuse-derived fuel (RDF) production. Successively adding the improvements, three alternative improved scenarios were defined, until reaching a negative carbon footprint, meaning that an optimised system would avoid GHG emissions. The proposed changes were sufficient to achieve carbon neutrality, as well as reduce overall environmental impacts, but were not enough for achieving economic sustainability due to the great influence of collection costs, especially for separate collection. It was concluded that by using an adequate combination of several treatment options and increasing the separate collection of recyclable materials it is possible to turn MSW management into a carbon neutral activity as well as improve its economic balance.

Abstract One of the critical areas in the outer shell of household refrigerators is the compressor compartment, which has relatively high temperatures, due to the heat generated while the compressor is running. This implies a larger heat transfer to the interior air volume and, consequently, more energy consumption. One way to decrease this temperature is to ventilate the base of the refrigerator with a small fan. In the research carried out, a decrease of 11 °C in the temperature of the surfaces close to the compressor was recorded, when the fan was running. The implications of this effect can be seen at two levels: changes in the temperature distribution at the bottom of the refrigerator envelope and the resulting dynamic effects, and a decrease in energy consumption of the entire system. Consequently, there are lower CO 2 emissions to the environment, making household refrigerators more efficient and sustainable.

This paper deals with the medium between two reconfigurable sensor nodes characterized by radio interfaces that support multiple channels for exchanging real-time messages under energy constraints. These constraints are violated if the consumed energy in transmission is higher than the remaining quantity of energy. A reconfiguration, i.e., any addition or removal of tasks in devices and consequently of messages on the medium, can cause the violation of real-time or energy constraints at run time. To achieve a feasible scheduling in time (i.e., message deadlines will be respected) and energy (i.e., there is available energy) on the medium, we propose new dynamic solutions: Balance, Dilute, and a Combination of them to manage any addition or removal of messages. The proposed approach utilizes the energy harvesting techniques and the PowerControl algorithm to reduce the nonharvested consumed energy. The proposed strategies achieve significant improvement over existing methods and provide the highest percentage of adding messages, with a lower average in response time and energy consumption. They reach a percentage of success in adding the highest priority messages while meeting deadlines up to 85%.

This work proposes a methodology for predicting the typical daily load profile of electricity usage based on static data obtained from surveys. The methodology intends to: (1) determine consumer segments based on the metering data using the k-means clustering algorithm, (2) correlate survey data to the segments, and (3) develop statistical and machine learning classification models to predict the demand profile of the consumers. The developed classification models contribute to make the study and planning of demand side management programs easier, provide means for studying the impact of alternative tariff setting methods and generate useful knowledge for policy makers.

Small but numerically dominant species such as the cyanobacteria Prochlorococcus play a pivotal role in major nutrient cycles. To understand how Prochlorococcus populations affect nutrient flows, we present and analyze two alternative population models. These models − one including over-shading effects and one not − are based on Dynamic Energy Budget (DEB) theory to describe how growth may be affected by the availability of CO2 and/or inorganic nutrients and by changes in light conditions. In these models individuals have reserves for C, N, and P from which fluxes for maintenance and growth are mobilized. Time series data from laboratory studies of growth under three different nutrient concentrations are used to calibrate the models. The model with carbon, nitrogen and phosphate as limiting factors can reasonably describe the growth in the low N and low P media experiments, while the model with over-shading gives a proper description of the growth under all tested experimental conditions. Modeled C:N:P ratios are within range of reported in scientific literature ones and similar to measured ratios. The results suggest that (1) reserves play a critical role for cyanobacteria to thrive under the often oligotrophic conditions in which they live, and (2) over-shading has a considerable effect as co-limiting factor on the growth of cyanobacteria. We argue that an individual DEB-based model in which multiple nutrient limitations are presented can be used to successfully describe cyanobacterium growth patterns in batch cultures.