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In this paper, we consider both energy efficiency and security issues in a wireless power transfer (WPT) enabled relay system. In the considered system, the multiple-antenna decode-and-forward relay node (RN) has both information decoding and wireless power recycling capabilities, and thus can be empowered by WPT and assist the transmission from the multiple-antenna base station (BS) to the mobile terminals (MTs). In addition, we consider that there is an eavesdropper between the BS and the RNs, which tries to overhear the information sent to the MTs. We formulate a joint optimization problem with the objective to optimize energy efficiency of the presented system by considering WPT time allocation, power allocation, and secrecy data rate. In particular, we propose to select RNs based on different assigned priorities so that the physical layer security of information transmission can be guaranteed. Moreover, we take into consideration of the cases that the RNs adopt the half- and full-duplex protocols, and study the corresponding system performance analytically. The proposed schemes are evaluated by extensive simulations and it is demonstrated that the proposed resource allocation schemes can obtain energy efficiency maximization, and have superior performance over other schemes.

The question “Where has my battery gone?” remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for constructing energy models from crowdsourced measurements. In contrast to previous approaches, which have focused on the effect of a specific sensor, system setting or application, our approach can simultaneously capture relationships between multiple factors, and provide a unified view of the energy state of the mobile device. We demonstrate the validity of using crowdsourced measurements for constructing battery models through a combination of large-scale analysis of a dataset containing battery discharge and system state measurements, and hardware power measurements. The results indicate that the models captured by our approach are both in line with previous studies on battery consumption and empirical measurements, providing a cost-effective way to construct energy models during normal operations of the device. The analysis also provides several new insights about battery consumption. For example, our analysis reveals the combined effect of high CPU activity and automatic screen brightness to be higher (resulting in 9 min shorter battery lifetime on average) than the effect of medium CPU load and manual screen brightness; a Wi-Fi signal strength drop of one bar can shorten battery life by over 13%; and a smartphone sitting in direct sunlight can witness over 50% shorter battery life than one indoors in cool conditions. Based on the crowdsourced energy models, we develop Constella, a novel recommender system for system settings. Constella provides actionable and human-readable recommendations on how to adjust system settings in order to reduce overall battery drain. We validate the effectiveness of Constella through a hardware power measurement experiment carried out using three application case studies. The results of the evaluation demonstrate that Constella is capable of generating recommendations that can provide up to 61% improvements in battery life.

Abstract Circular economy and resource efficiency have recently gained enormous attention as solutions to global resource scarcity. Among other actors, cities are in a central position in putting these concepts into action. In Finland, the network of Finnish Sustainable Communities (FISU) encourages its member cities to adopt the principles of resource wisdom: zero climate emissions, zero waste and living within the Earth’s carrying capacity. These targets of the cities are monitored through three indicators: greenhouse gas emissions, material loss and ecological footprint. In this study, we tested the applicability of these indicators for the city-level sustainability measurements. The results show that for greenhouse gas emissions, the accuracy of emission inventory varies in different sectors. However, greenhouse gas emissions are applicable for the periodical city-level follow-up towards climate neutrality. Concerning material loss, industrial waste as well as mining waste and excess soil dominate the results. Allocation of waste flows to different municipalities poses a challenge to interpretation of the results. Ecological footprint is a simple and understandable indicator for pointing out overconsumption, and it easily indicates the need for action. Nevertheless, the availability of local data for the calculations is limited. The indicator set can be used as background information for setting long-term visions and targets for a resource-wise city. The conclusions from indicator calculations should be translated into practical actions by setting a local action plan towards sustainability. The annual follow-up of these kinds of action plans requires supporting indicators in addition to the three indicators tested in this study. Several different city-level sustainability indicator frameworks from the literature should be utilized in defining the relevant additional indicators.

Anthropogenic climate warming has already affected the population dynamics of numerous species and is predicted to do so also in the future. To predict the effects of climate change, it is important to know whether productivity is linked to temperature, and whether species' traits affect responses to climate change. To address these objectives, we analysed monitoring data from the Finnish constant effort site ringing scheme collected in 1987-2013 for 20 common songbird species together with climatic data. Warm spring temperature had a positive linear relationship with productivity across the community of 20 species independent of species' traits (realized thermal niche or migration behaviour), suggesting that even the warmest spring temperatures remained below the thermal optimum for reproduction, possibly due to our boreal study area being closer to the cold edge of all study species' distributions. The result also suggests a lack of mismatch between the timing of breeding and peak availability of invertebrate food of the study species. Productivity was positively related to annual growth rates in long-distance migrants, but not in short-distance migrants. Across the 27-year study period, temporal trends in productivity were mostly absent. The population sizes of species with colder thermal niches had decreasing trends, which were not related to temperature responses or temporal trends in productivity. The positive connection between spring temperature and productivity suggests that climate warming has potential to increase the productivity in bird species in the boreal zone, at least in the short term.

Abstract Understanding the influence of forest structure on forest albedo, and thus on the energy exchange between the forest and the atmosphere, is urgently needed in areas with large forest cover and active forest management. Fine resolution albedo retrievals enable quantifying the relationships between forest variables and albedo also in patchy landscapes, such as in the managed forests in Fennoscandia. In this study, field plot data, airborne laser scanning (ALS) data and high resolution satellite albedo retrievals from Landsat were used to investigate the main factors influencing forest albedo in Central Finland in midsummer. Tree species, forest structure and understory (ground) vegetation composition all influenced forest albedo. The tree species-specific models were estimated on a subpixel scale by utilizing information on the proportions of each species within a plot. Tree species considerably improved the albedo prediction when added to a model containing only a structural variable, whereas a further addition of the site fertility class as a proxy of understory vegetation composition only slightly improved the model. Albedo decreased with increasing volume of growing stock, but the decrease leveled off at high volumes. The albedo of plots with high volume was instead mainly governed by tree species and was the lowest for Norway spruce, intermediate for Scots pine and highest for broadleaved species. Norway spruce albedo decreased almost linearly with increasing mean tree height. ALS-derived canopy cover explained fairly well the variation in albedo in the visible region, but the total shortwave albedo was better predicted by ALS-derived tree height.

AbstractEnvironmental problems related to agricultural land use require better functioning solutions. Pressing problems include the increasing nutrient load in water bodies, caused by fertilization and erosion, and carbon emissions caused by various agricultural practices, for example. At a policy level, these issues are tackled via agri-environmental measures, but at farm level, these measures have not attracted as wide support as hoped for. Instead, farmers feel that many agri-environmental measures are incoherent in relation to their practices and goals, and the goals of agricultural policies in general. This type of policy problem can be called experienced policy coherence and it results in poor functioning of the policies. This paper connects practice theory and policy coherence analysis and suggests that a more systematic focus on the practices which the policies aim at influencing is needed in order to design better policies and to approach the problem of policy incoherence experienced by grass-roo...

Abstract Technological and regulatory responses to large-scale environmental threats, such as depletion of the natural resources and climate change, tend to focus on one issue at time. Emerging carbon capture and storage (CCS) technologies that are in different stages of development offer a case that demonstrates this dilemma. This article approximates the implications of two emerging CCS applications on existing steel mill’s CO2 emissions and its use of material resources. The evaluated applications are based on the mineralization method and the comparative case represents two versions of a geological CCS method. The results of the evaluation indicate that if technical bottleneck issues related to CO2 sequestration with mineralization can be solved, it can be possible to achieve a similar CO2 reduction performance with mineralization-based CCS applications as with more conventional CCS applications. If the CO2 capturing potential of mineralization-based applications could be taken into use, it could also enable the significant improvement of material efficiency of industrial operations. Urgent problem hampering the development of mineralization-based CCS applications is that the policy regimes related to CCS especially in the European Union (EU) do not recognize mineralization as a CCS method. Article suggests that the focus in the future evaluations and in policy should not be directed only on CO2 sequestration capacity of CCS applications. Similarly important is to consider their implications on material efficiency. Article also outlines modifications to the EU’s CCS policy in terms of the formal terminology.