Abstract
The purpose of this paper is to develop a robust methodology to assess municipalities' performance concerning the consumption of resources in residential buildings. The assessment is carried out at a municipal level to inform decision makers about the relative position of their municipalities compared to others. In addition, the factors associated to better levels of municipal performance are identified, and the extent of their effects is quantified. The study uses an enhanced stochastic frontier panel model based on data of energy, water and materials consumption in Lisbon municipalities during the period 2003-2009. The study reveals that the municipalities' performance has remained stable over the years, although there are considerable differences in performance among municipalities. In addition, it is concluded that municipal performance tends to improve with the environmental policy expenditure and scale size, and decline with buildings' age, population density and the proportion of buildings with private ownership.

Abstract

Abstract
This paper presents an analysis of the impacts of photovoltaics and storage units for self-consumption in the day-ahead spot prices. A methodology is proposed, to access these impacts in the Iberian electricity market for 2015, 2020 and 2030.

Abstract
A large amount of duplicate data typically exists across volumes of virtual machines in cloud computing infrastructures. Deduplication allows reclaiming these duplicates while improving the cost-effectiveness of large-scale multitenant infrastructures. However, traditional archival and backup deduplication systems impose prohibitive storage overhead for virtual machines hosting latency-sensitive applications. Primary deduplication systems reduce such penalty but rely on special cluster filesystems, centralized components, or restrictive workload assumptions. Also, some of these systems reduce storage overhead by confining deduplication to off-peak periods that may be scarce in a cloud environment. We present DEDIS, a dependable and fully decentralized system that performs cluster-wide off-line deduplication of virtual machines' primary volumes. DEDIS works on top of any unsophisticated storage backend, centralized or distributed, as long as it exports a basic shared block device interface. Also, DEDIS does not rely on data locality assumptions and incorporates novel optimizations for reducing deduplication overhead and increasing its reliability. The evaluation of an open-source prototype shows that minimal I/O overhead is achievable even when deduplication and intensive storage I/O are executed simultaneously. Also, our design scales out and allows collocating DEDIS components and virtual machines in the same servers, thus, sparing the need of additional hardware.

Abstract
Grid connected energy storage systems are regarded as promising solutions for providing ancillary services to electricity networks and to play an important role in the development of smart grids. Thus far, the more mature battery technologies have been installed in pilot projects and studies have indicated their main advantages and shortcomings. The main concerns for wide adoption are the overall cost, the limited number of charging cycles (or lifetime), the depth of discharge, the low energy density and the sustainability of materials used. Vanadium Redox Flow Batteries (VRFB) are a promising option to mitigate many of these shortcomings, and demonstration projects using this technology are being implemented both in Europe and in the USA. This study presents a model using MATLAB/Simulink, to demonstrate how a VRFB based storage device can provide multi-ancillary services, focusing on frequency regulation and peak-shaving functions. The study presents a storage system at a medium voltage substation and considers a small grid load profile, originating from a residential neighbourhood and fast charging stations demand. The model also includes an inverter controller that provides a net power output from the battery system, in order to offer both services simultaneously. Simulation results show that the VRFB storage device can regulate frequency effectively due to its fast response time, while still performing peak-shaving services. VRFB potential in grid connected systems is discussed to increase awareness of decision makers, while identifying the main challenges for wider implementation of storage systems, particularly related to market structure and standardisation requirements.

Abstract
Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.