This study presents a life cycle assessment (LCA) study for a buoy-rope-drum (BRD) wave energy converter (WEC), so as to understand the environmental performance of the BRD WEC by eco-labeling its life cycle stages and processes. The BRD WEC was developed by a research group at Shandong University (Weihai). The WEC consists of three main functional modules including buoy, generator and mooring modules. The designed rated power capacity is 10 kW. The LCA modeling is based on data collected from actual design, prototype manufacturing, installation and onsite sea test. Life cycle inventory (LCI) analysis and life cycle impact analysis (LCIA) were conducted. The analyses show that the most significant environmental impact contributor is identified to be the manufacturing stage of the BRD WEC due to consumption of energy and materials. Potential improvement approaches are proposed in the discussion. The LCI and LCIA assessment results are then benchmarked with results from reported LCA studies of other WECs, tidal energy converters, as well as offshore wind and solar PV systems. This study presents the energy and carbon intensities and paybacks with 387 kJ/kWh, 89 gCO 2 /kWh, 26 months and 23 months respectively. The results show that the energy and carbon intensities of the BRD WEC are slightly larger than, however comparable, in comparison with the referenced WECs, tidal, offshore wind and solar PV systems. A sensitivity analysis was carried out by varying the capacity factor from 20-50%. The energy and carbon intensities could reach as much as 968 kJ/kWh and 222 gCO 2 /kWh respectively while the capacity factor decreasing to 20%. Limitations for this study and scope of future work are discussed in the conclusion.Energies 2018, 11, 2432 2 of 15 to absorb wave energy and convert it to electricity or other forms of energy [4]. Since the beginning of the century, tidal stream technology and wave energy technology development have started to ramp up [5]. Although there no large-scale WEC installation has been reported in the U.S., the U.S. Department of Energy sponsored the Wave Energy Prize in 2015, an 18-month public design-build-test competition to increase the diversity of organizations involved in WEC technology development, while motivating and inspiring existing stakeholders [6]. The UK and Portugal have the vast majority of wave energy deployments in Europe [5]. The Carbon Trust estimates that a contribution of up to 20% of total UK energy generation could be provided by marine energy by 2050 [7,8]. China possesses a total marine area of 4,700,000 km 2 [9]. With annual mean wave power of up to 7.73 kW/m wave front, China has a wave power potential of 128.5 GW, nearly half of the electricity production of China [10,11]. However, the majority of China's wave energies are without any exploitation and thus far, most of the WECs in China are still in concept design or pre-commercial stages. Aiming to stimulate and encourage the marine renewable energy technology research and development, China National Oceanic Admini...

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Automotive manufacturing is energy-intensive. The consumed energy contributes to the generation of significant amounts of greenhouse gas (GHG) emissions by the automotive manufacturing industry. In this paper, a study is conducted on assessing the application potential of such clean energy power systems as solar PV, wind and fuel cells in reducing the GHG emissions of the global auto manufacturing industry. The study is conducted on the representative solar PV, wind and fuel cell clean energy systems available on the commercial market in six representative locations of GM's global facilities, including the United States, Mexico, Brazil, China, Egypt and Germany. The results demonstrate that wind power is superior to other two clean energy technologies in the economic performance of the GHG mitigation effect. Among these six selected countries, the highest GHG emission mitigation potential is in China, through wind power supply. The maximum GHG reduction could be up to 60 tons per $1,000 economic investment on wind energy supply in China. The application of wind power systems in the United States and Germany could also obtain relatively high GHG reductions of between 40-50 tons per $1,000 economic input. When compared with wind energy, the use of solar and fuel cell power systems have much less potential for GHG mitigation in the six OPEN ACCESSEnergies 2011, 4 1479 countries selected. The range of median GHG mitigation values resulting from solar and wind power supply are almost at the same level.

Confronted with a series of problems caused by surging generation of municipal solid waste (MSW), the Chinese central and local governments have promulgated and implemented policies to deal with them, including promotions of the classification of MSW. However, to date, practical knowledge and understanding about benefits for garbage classification from its environmental performance perspective is still limited. The present study is purposed to comprehensively investigate the environmental effects of garbage classification on municipal solid waste management (MSWM) systems based on three proposed garbage classification scenarios in China, via a comparative life cycle impact assessment (LCIA). Taking advantage of Impact Assessment of Chemical Toxics (IMPACT) 2002+ method, this comparative LCIA study can quantitatively evaluate midpoint, endpoint, and single scored life cycle impacts for the studied MSWM systems. A Monte Carlo uncertainty analysis is carried out to test the effectiveness and reliabilities of the LCIA results. The LCIA and uncertainty analysis results show that MSWM systems based on various garbage classification scenarios have significant variations in the studied midpoint, endpoint, and single scored environmental impacts. Different garbage classification scenarios have their individual environmental-friendly superiority for specific impact categories. Overall, results of this study demonstrate that MSW treatment systems integrated with garbage classification are more environmentally friendly by comparison with non-classification; and that the more elaborate the level of MSW classification, the smaller its impacts on the environment.