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As a result of the growing global demand for energy, together with the depletion of resources and the growing emphasis on mitigating climate change and greenhouse gas emissions, an urgent need for an evolution of the renewable energy resources has emerged. On the architectural scene, we have become accustomed to seeing buildings incorporated with photovoltaics and wind turbines. Despite the great contribution of biomass as a clean energy producer, the integration of biomass into architecture is quite modest and still in its initial phases. Microalgae, as a plant-based biomass, can outperform other renewable resources with their potential to absorb CO 2 , recycle wastewater, and release O 2 . The limited experience regarding building-integrated microalgae photobioreactors (PBRs) requires shedding light on some issues. So, this paper aims to explore the following: 1) the proper types of PBRs for integration with buildings, 2) the overall bioprocess and the design considerations regarding PBRs and their technical requirements, 3) the environmental and energetic performance of PBRs, 4) their challenges, and 5) their prospects. Thus, the paper's methodology consists of 1) reviewing the promulgated literature concerning microalgae and PBRs, 2) reviewing and analyzing three building-integrated PBRs and three urban-integrated PBRs, and 3) reviewing the environmental and energetic performance of building-integrated PBRs. The paper has concluded that the symbiosis between PBRs and façades encounters some challenges, including 1) the biorefinery infrastructure, 2) the provision of a source of CO 2 , and 3) the high initial cost. On the other hand, the multifaceted environmental prospects of building-integrated PBRs are represented in 1) energy savings; 2) GHG emissions reduction; 3) oxygen and hydrogen release; 4) biofuel production; and 5) wastewater treatment. The unique benefits of the bio-façades through the combination of the technical and biological cycles within buildings inaugurate an innovative approach to sustainability by integrating environmental, energetic, and iconic values. [ABSTRACT FROM AUTHOR]

Several theoretical studies have been reported in recent years which have indicated that large-scale wind farms can have an impact on local and regional meteorology, possibly on climate. Now evidence of it based on field observations has also begun to emerge. The present paper traces the evolution of this knowledge. It discusses the theoretical studies on the possibility of wind turbines effecting climate change, and summarizes the emerging confirmation of those predictions. The concluding part of the paper assesses the implications of these findings in the context of the world׳s past experience on global warming and its present thrust to meet substantial portions of its energy needs with renewables. [ABSTRACT FROM AUTHOR]

Abstract: Wind energy, commonly recognized to be a clean and environmentally friendly renewable energy resource that can reduce our dependency on fossil fuels, has developed rapidly in recent years. Its mature technology and comparatively low cost make it promising as an important primary energy source in the future. However, there are potential environmental impacts due to the installation and operation of the wind turbines that cannot be ignored. This paper aims to provide an overview of world wind energy scenarios, the current status of wind turbine development, development trends of offshore wind farms, and the environmental and climatic impact of wind farms. The wake effect of wind turbines and modeling studies regarding this effect are also reviewed. [Copyright &y& Elsevier]

Abstract: In the last century, several climate changes have been observed in regions all over the world. The main cause of these climatic changes is the rise of fossil fuel uses, which is due to the important demographic and industrial development. These negative effects have forced scientists to draw attention to renewable energy sources, which are the most suitable solution in the future. In this paper, wind energy potential was estimated using the wind speed data collected by two meteorological stations installed in the Centre of Research and Technologies of Energy (CRTEn) in the Borj-Cedria area. The data collected at 30, 20 and 10m height during 2008 and 2009, have permitted us to estimate the seasonal mean wind speed, wind speed distribution and wind power density. The results have been used to estimate the net energy output of seven 1.5MW wind turbines with taken account the air density correction and the power losses in wind farm. This comparative simulation shows difference in wind generators production and allows us to choose the best wind turbine adapted to the site conditions. [Copyright &y& Elsevier]

Abstract: Climate change and limited primary energy resources require indigenous renewable electricity generation options to change the current coal-dominated power source matrix in China. The wind power is such a solution for the above challenges, and it still has large space for improvement in China. In this paper several critical factors related to Chinese wind power were studied in details, including the wind resources, the wind turbine industry and the policies from the Chinese government. Based on the study, the perspective of wind power in China was discussed. With outstanding advantages, the offshore wind power has a bright future in China, so its main characteristics are discussed. Based on the discussions, suggestions were given to improve the development of Chinese wind power, and the government''s further measures are also recommended. [Copyright &y& Elsevier]

Abstract: The present paper analyzes the CO2 emissions from mobile communications and portable wireless electronic devices in the Korea environment. The quantitative and qualitative contributions to CO2 emission reduction of the substitution of renewable energy for traditional electricity as the power supply in these devices are also investigated. Firstly, the national CO2 emission coefficient is temporarily estimated as 0.504tCO2/MWh, which can be regarded as the basis for calculating CO2 emissions in mobile devices. The total annual CO2 emissions from mobile devices is calculated as approximately 1.4 milliontons, comprising 0.3 milliontCO2 for portable wireless electronic devices and 1.1 milliontCO2 for electric equipment required for mobile communication service. If renewable energy sources are substituted for traditional electricity sources in the supply for mobile devices, solar cell and wind turbine systems can reduce CO2 emissions by about 87% and 97%, respectively. However, the use of fuel cell systems will only slightly reduce the CO2 emissions. However, the use of the direct methanol fuel cell system can release 8% more CO2 emissions than that emitted by using traditional electricity sources. [Copyright &y& Elsevier]

In order to mitigate global climate change and air pollution, the Chinese government has assigned high priority to expanding low-carbon power generation in China. Recent studies have shown that wind power is one of the most promising renewable energy option in China. Although many studies have estimated the generation potential of onshore wind power, their results vary widely from 1783 TWh to 39,000 TWh. Therefore, we examine the different assumptions in these papers and identify three main factors influencing the results. The three influencing factors are: weather data set, land utilisation factor, and wind turbine configuration. For our model-based analysis, we define a reference scenario which is used to compare the results. Our analysis shows using a different weather data set increases the generation potential to roughly 35,000 TWh. This is 54% higher than the generation potential of the reference scenario. The land utilisation factor also has a large influence, ranging between −10% and −51%. The studies' assumptions and data should be subjected to careful scrutiny, as the calculated wind power potentials are widely used to develop decarbonisation strategies for the energy system. • Study results on wind power potentials in China vary from 1783 TWh to 39,000 TWh • Influencing factors: weather data set, land utilisation, and wind turbine configuration. • Model-based sensitivity analysis with nine scenario settings. • Chosen weather data set has the highest impact on the calculated results with a variation of 54%. [ABSTRACT FROM AUTHOR]