Renewable Energy Global Innovations features: Recycled waste black polyurethane sponges for solar vapor generation and distillation

Significance Statement

Owing to the rising global concerns of energy problems, renewable energy resources are being pursued in high demand. Solar power is the most promising and yet naturally unlimited energy source in the foreseeable future. Recently, solar vapor generation has attracted extensive attention owing to the fact that water pollution, water shortages and energy shortages are alarmingly becoming global issues that ought to be addressed. The use of solar energy to enhance evaporation is currently emerging as an attractive strategy for sustainable and practical system such as in desalination, ethanol distillation and sterilization. Plasmonic metallic nanoparticles of noble metals have been widely investigated as solar absorbers due to their unique photo-thermal conversion property despite their limited applicability due to their costly nature. The quest for a high solar-thermal efficiency solar absorbers has led researchers right into the dumpsites, where waste black polyurethane sponge has been observed to possess the desired qualities upon treatment.

Researchers led by professor Yuen Hong Tsang at The Hong Kong Polytechnic University proposed a study to demonstrate that the recycled black polyurethane sponge with porous structure, low thermal conductivity and low mass density to be self-floating, could behave as an ideal absorber for solar vapor generation despite its weak hydrophilicity. Their aim was to present a recycled self-floating black polyurethane sponge which could efficiently generate water vapor after a simple treatment procedure. Their research work is now published in Applied Energy.

The research team begun by modifying the chemical properties by using a facile dopamine solution stirring treatment, so as to achieve the fast dynamic wettability of the black polyurethane sponge, for fluent water supply on the top surface of the absorber. They then used the porous floatable black polyurethane sponge with low thermal conductivity and high durability to generate localized heat at the air-water surface so as to effectively enhance the water evaporation efficiency. Afterwards, they examined the sponge for application in ethanol distillation.

The authors observed that the surface modified black polyurethane sponge showed that the evaporation rate increased by more than 3.5 times compared to the existing natural evaporation processes. They also observed that the black polyurethane sponge for the solar energy distillation application, showed that the sponge could yield up to 25 wt% concentration promotion under each distillation cycle.

The fact that the black polyurethane sponge is a major waste of the packaging industry supports its application for solar energy conversion as an alternative way for disposing it without polluting the environment. It is more advantageous as opposed to other alternative methods since it does not consume any fossil fuel which generate greenhouse gases during combustion.  Based on environmental sustainability and energy costs, the work presented is promising to be an exciting prospect and competitive for applications in practical solar-thermal technologies.

About The Author

Dr. Yuen Hong Tsang has completed his undergraduate and PhD study in the School of Physics and Astronomy, The University of Manchester, UK in 2004. He came back to Hong Kong in 2009 and he is now Assistant Professor in Applied Physics Department, The Hong Kong Polytechnic University. He has published >100 SCI international peer reviewed journals with H-index >20 and total citation >1400.

His current research interests include development of novel materials, e.g. graphene, MoS₂, WS₂ etc. for laser photonics, photo-catalysis, solar energy conversion applications, e.g. photo-catalyst, solar heat absorber, saturable absorber, optical limiter, photo detection, fiber laser, Q-switched and mode locked lasers, etc.

He has involved and successfully completed several research projects funded by some well-known international companies. These projects include 1.  Laser range funder for military applications (funded by Thales.) 2. Imaging system for dental applications (funded by Colgate Palmolive) 3. Narrow linewidth tunable lasers (funded by Huawei) 4. Carbon based mode locking laser system (funded by Fianium Asian Ltd.)

Reference

Sainan Ma, Chun Pang Chiu, Yujiao Zhu, Chun Yin Tang, Hui Long, Wayesh Qarony, Xinhua Zhao, Xuming Zhang, Wai Hung Lo, Yuen Hong Tsang. Recycled waste black polyurethane sponges for solar vapor generation and distillation. Applied Energy volume 206 (2017) pages 63–69.

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Renewable Energy Global Innovations features: GIS application and econometric analysis for the verification of the financial feasibility of roof-top wind turbines in the city of Bari (Italy)

Significance Statement

There has been an increase in the enactment of legislative acts aiming at reinforcing the idea of sustainable energy in industrialized countries, as an ingredient for private as well as public investments. In Italy, for instance, wind solutions for the production of electricity from renewable energy sources have been widely implemented, particularly in regions characterized by excellent geo-climatic conditions. With an increasing pressure to limit soil sealing, more attention has been given to the adoption of renewable energy policies integrated with the current urban establishments.

Pierluigi Morano and Francesco Tajani at Polytechnic University of Bari (Italy) in collaboration with Marco Locurcio at Sapienza University of Rome (Italy) analyzed the financial feasibility originating from the realization of roof-top wind turbines in Bari. The analysis was done via the implementation of a GIS-based decision model. Their second aim was to deal with the explanation of the mathematical relationship between economic and aerodynamic variables of the setup. Their work is published in Renewable and Sustainable Energy Reviews.

The research team implemented a methodology that encompassed the study of the wind climatology of the urban areas of Bari. Adopting the method developed by the MET office, the authors divided the desired territory into homogeneous areas in terms of potential wind energy resources. The map of use of soil and the regional technical map allowed for the implementation of the model developed in the GIS environment, generating two types of thematic maps of Bari, which related to the estimation of the annual mean wind speed and the average annual energy production.

The authors also evaluated the revenues and the costs that concurred to determine the financial feasibility of the wind investment, differentiated on the basis of the thematic maps obtained from the previous stage. The financial parameters identified allowed for the generation of two evaluative maps: the first was a financial feasibility of the investment in the geographic areas of the city of Bari; the second was for the unit land lease values per square meter of the total area covered by buildings. The outputs allowed for the enucleation of the real impact of the aerodynamic parameters on the economic variables to confirm the empirical coherence and report the inconsistencies of the qualitative analysis developed in the first objective.

Above all, the authors constitute a quick reference for a rapid analysis of the convenience of an investment in roof-top wind turbine plants in other regions. After getting the values of parameters that appeared in the econometric model and upon verifying the assumptions adopted for its definition, the authors obtained mathematical expressions that allowed for the evaluation of performance indicators for the entailed parties.

The outcomes of the study represent an evaluative support for operators interested in taking advantage of the incentives offered by energy regulations for the set-up of micro-turbines in windy territory as well as identifying the regions characterized by high power yields.

The approach used in their study, borrowing with a complementary approach GIS tools as well as econometric algorithms, displays an important basis for the formation of homogeneous territorial areas with regards to wind power capacity. The approach entails a straightforward repeatable operative and logical path, which can be implemented in other territorial areas.

About The Author

Pierluigi Morano holds a PhD in Economic Evaluation of Investments and a Master in Urban Planning and Real Estate Market. He is author and co-author of books, journal papers and conference papers on various topics, including the themes of the plans and investments valuation, the appraisal of the cost of the public works, the analysis of the real estate market, the public-private negotiation in urban planning.

About The Author

Francesco Tajani holds a PhD in Economic Evaluation of Investments and a Master in Urban Planning and Real Estate Market. He is author and co-author of published works on various topics, including the study of innovative algorithms as support to real estate appraisal, the evaluation of investments on cultural and environmental assets and the econometric analysis of the dynamics of real estate prices generated by macroeconomic variables. He is a Member of the Royal Institution of Chartered Surveyors (RICS).

About The Author

Marco Locurcio holds a PhD in Architecture and Construction and a Master in Assessment and Retrofitting in Seismic Areas. He is co-author of published works about the analysis of the real estate market, multi-criteria decision analysis and its application.

Journal Reference

Pierluigi Morano, Francesco Tajani, and Marco Locurcio.GIS application and econometric analysis for the verification of the financial feasibility of roof-top wind turbines in the city of Bari (Italy). Renewable and Sustainable Energy Reviews, volume 70 (2017), pages 999–1010.

¹ Department of Science of Civil Engineering and Architecture (DICAR), Polytechnic University of Bari, via Orabona 4, Bari 70125, Italy.

² Department of Architecture and Design (DIAP), University Sapienza of Rome, via Gramsci 53, Roma 00197, Italy.

 

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Renewable Energy Global Innovations features: Energy Resources Intelligent Management using on line real-time simulation: A decision support tool for sustainable manufacturing

Significance Statement

Eco-sustainability of industrial manufacturing has been considered as one of the building blocks of relations between the environment and people. The use of renewable energy has therefore become a fundamental element in view of this vision. A binding global accord was finally reached after several years of vain attempts to rule out an agreement to considerably curtail carbon dioxide emissions from burning fossil fuels.

A number of commonly used renewable energy sources, such as wind and solar, exhibit a problem concerning discontinuity in the production of energy owing to variability in weather as well as climatic conditions. Therefore, there has been increasing efforts by researchers to come up with a new methodology that can be capable of marrying industrial users’ instantaneous need for energy with the generation capability of renewable energy sources, and when necessary, supplemented by energy created via self-production and perhaps from third-party suppliers. This is in the view of minimizing carbon dioxide emissions as well as company energy costs.

In order to manage renewable energy sources effectively and efficiently, predictive models for industrial energy demands as well as production capacity of renewable energy sources is needed. University of Genoa researchers in Italy proposed to provide energy managers in the manufacturing environment with a support tool that can implement the potentialities of Discrete Event Simulation as well as Monte Carlo simulation and incorporated with a unique predictive algorithm to allow optimizing energy supplying mix. Their research work is published in Applied Energy.

Tackling the issue of the supplemented as well as optimal use of energy produced by renewable energy sources in the field of manufacturing, the authors proposed a management method referenced on two steps, fortified by two respective models; the Energy Resources Intelligent Management-Predictor (ERIM-P) and Energy Resources Intelligent Management-Real Time (ERIM-RT). The purpose of the former model was to come up with, 24h in advance, the hourly electrical energy requirement of the manufacturing plant referenced on the production plan made for the next day. The model was also to quantify the possible self-production of renewable energy sources energy based on weather forecast for the next day.

Upon completion of the first model, the latter ERIM-RT will act on the current day taking into consideration through the implementation of an on-line real-time Discrete Event Simulation simulator of what would be happening in real time with the manufacturing plant and the actual instantaneous generation of renewable energy sources. The use of a predictive algorithm would offer a 30min update of the available renewable energy generation prediction for subsequent times of the day.

Counting on the test cases done on the tannery, the outcomes observed showed that the ERIM-RT model allowed for obtaining considerable improvements in real time estimates, both real photovoltaic generation and daily energy demand schedule. In the combined high-variability sub-scenarios, the authors found a clear enhancement in energy performance for the tannery in view of reduction of error, carbon-dioxide emissions, and energy costs. The model was found to be more effective when the larger the deviations were between the prediction made on the day before and the real profiles for the current day.

Their study also highlighted that the more the attributes of the tannery were affected by randomness, the more the need for the ERIM-RT model became essential. With the two sub-scenarios, Demand Lower Production Higher and Demand Higher Production Lower, the ERIM-RT model led to enhancement in predictive performance by, respectively, 7.3 and 7 times greater than with the ERIM-P model alone.

Reference

Lucia Cassettari, Ilaria Bendato, Marco Mosca, and Roberto Mosca. Energy Resources Intelligent Management using on line real-time simulation: A decision support tool for sustainable manufacturing. Applied Energy, volume 190 (2017), pages 841–851.

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