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The promotion of rural development can benefit from the advancement of renewable energies as potential sources of growth and income in an integrated economy. Rural areas have attracted a significant proportion of renewable energy installations, mainly wind energy. Moreover, the development of renewables has been explicitly claimed as a key instrument to support rural economies through job creation, new sources of income for landowners and local authorities, and more sustainable industries with the revitalization of their productive systems. However, the installation of renewable energies can have, in the short and long term, different impacts on the territory. This study explores Campo de Belchite citizens’ perception of the effects wind energy installations has on the economy, demography, and employment opportunities. The Campo de Belchite county (Aragon) was used as a case study due to its wind-farm development. Citizens perceptions on the socio-economic effects and expectations of renewable energies have been explored on the basis of their responses to an online survey. Findings show a great heterogeneity between agents and territories, both in the evaluation of impacts and in their hopes. The management model plays a critical role for achieving its social acceptance. This work contributes with industrial and energy policy insights that call for a more decentralized, participatory and transparent management models.

Sustainable water management is challenging because of the wide range of agents who need water and the different kinds of use, in a context of limited water availability. The availability of water for use, at a given point in time and space, depends on numerous physical and climatic variables, as well as upstream uses and downstream commitments. Therefore, any analysis of water use and management must inevitably be made in the context of such variability. This paper develops an integrated, multiregional, hydro-economic modeling framework to analyze the spatial and temporal dependencies between economic agents in the different regions and areas of a river basin. We combine hydro-economic modeling (partial economic equilibrium) and a multiregional input–output model (general equilibrium) to take advantage of both methodologies. Spatial variability is considered in the input–output models, but variability in both time and space is also considered by the hydro-economic model. Hydro-economic models are used to quantify direct impacts, but not indirect impacts in some specific sectors of the economy, while the input–output model reveals the relationships between all sectors and regions, and facilitates the assessment of total impacts (direct plus indirect) of a range of scenarios. While the methodology described in this paper is applicable to any river basin, the case study considered is the Ebro River Basin, in Spain. To show the potential of the modeling framework, two scenarios are simulated to assess the impacts on water use, value added, and jobs across scales. The results of these scenarios show that decreases in water availability have negative impacts on socio-economic variables (value added and employment). The trade-off between water availability and socio-economic variables depends on the temporal and spatial variability of the resource, and affects each location in the basin in a different way, demonstrating the importance of the methodology developed.

Much attention has been paid to burden shifting of CO2emissions from developed regions to developing regions through trade. However, less discussed is that trade also acts as a mechanism enabling wealthy consumers to shift water quantity and quality stress to their trading partners. In this study, we investigate how Shanghai, the largest megacity in China, draws water resources from all over China and outsources its pollution through virtual quantity and quality water flows associated with trade. The results show that Shanghai's consumption of goods and services in 2007 led to 11.6 billion m3of freshwater consumption, 796 thousand tons of COD, and 16.2 thousand tons of NH3‐N in discharged wastewater. Of this, 79% of freshwater consumption, 82.9% of COD and 82.5% of NH3‐N occurred in other Chinese Provinces which provide goods and services to Shanghai. Thirteen Provinces with severe and extreme water quantity stress accounted for 60% of net virtual water import to Shanghai, while 19 Provinces experiencing water quality stress endured 79% of net COD outsourcing and 75.5% of net NH3‐N outsourcing from Shanghai. In accordance with the three “redlines” recently put forward by the Chinese central government to control water pollution and cap total water use in all provinces, we suggest that Shanghai should share its responsibility for reducing water quantity and quality stress in its trading partners through taking measures at provincial, industrial, and consumer levels. In the meantime, Shanghai needs to enhance demand side management by promoting low water intensity consumption. Analysis of virtual water flows for both quantity and qualityQuantification of burden shifting of water stress from ShanghaiDiscussion of consumer responsibility for megacities

Objective:To evaluate the influence of overweight, waist circumference, age, gender, and insulin resistance as risk factors for hyperleptinemia. Research Methods and Procedures:A cross‐sectional study was carried out in a population of 197 subjects: 59 men (21 aged <60 years and 38 aged ≥60 years) and 138 women (37 aged <60 years and 101 aged ≥60 years). The groups were stratified by overweight and normal weight. After a 12‐hour fasting period, we measured serum leptin and insulin levels with radioimmunoassay methods. We also measured serum glucose and lipid profile. The data were analyzed by means of comparative tests. A variance‐stabilizing transformation (natural logarithmic) was used to meet multiple linear regression, analysis of covariance, and logistic regression models. Results:The leptin serum levels were higher and statistically significant in young and older women than they were in men. We observed an interaction between gender and body mass index to explain the difference in leptin levels (p< 0.0001). Our study demonstrated an inverse relationship between leptin with age and high‐density lipoprotein cholesterol. In logistic regression analysis, the overweight × gender interaction and waist circumference have a statistically significant influence as independent variables on hyperleptinemia (overweight × gender odds ratio = 6.81; 95% confidence interval, 1.10 to 46.86; p< 0.05 and waist circumference odds ratio = 4.34; 95% confidence interval, 1.47 to 12.83; p= 0.001). Discussion:Women who were overweight or had a higher waist circumference (women ≥ 88 cm and men ≥ 102 cm) have a significantly higher risk of having hyperleptinemia. The increase in age as an isolated variable is not a risk factor for hyperleptinemia.