• Energy Research
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The aim of this study was to investigate the effectiveness of cultivating Parachlorella kessleri and Acutodesmus obliquus, in anaerobic digestion effluent (ADE) derived from the co-digestion of end-of-life dairy products with mixtures of agro-industrial wastes. To this end, their performance under sterile and non-sterile conditions and different ADE loadings was evaluated, in terms of biomass and lipid production, nutrient removal efficiency and vitality of the photosynthetic apparatus. 10% (v/v) ADE loading inhibited growth over 9-12days of cultivation, however biomass yields of 1.1 and 1gL-1, 22.7% and 19.5% (w/w) fatty acids concentration, as well as NH3-N assimilation of 49.7mgL-1 and 32.3mgL-1 and TP removal of 84.2% and 84% were recorded for P. kessleri and A. obliquus, respectively. Among all the ADE-based treatments tested, P. kessleri outperformed A. obliquus, with no differences observed between sterilized and non-sterilized ADE.

Bioplastics are alternatives of conventional petroleum-based plastics. Bioplastics are polymers processed from renewable sources and are biodegradable. This study aims at conducting an environmental impact assessment of the bioprocessing of agricultural wastes into bioplastics compared to petro-plastics using an LCA approach. Bioplastics were produced from potato peels in laboratory. In a biochemical reaction under heating, starch was extracted from peels and glycerin, vinegar and water were added with a range of different ratios, which resulted in producing different samples of bio-based plastics. Nevertheless, the environmental impact of the bioplastics production process was evaluated and compared to petro-plastics. A life cycle analysis of bioplastics produced in laboratory and petro-plastics was conducted. The results are presented in the form of global warming potential, and other environmental impacts including acidification potential, eutrophication potential, freshwater ecotoxicity potential, human toxicity potential, and ozone layer depletion of producing bioplastics are compared to petro-plastics. The results show that the greenhouse gases (GHG) emissions, through the different experiments to produce bioplastics, range between 0.354 and 0.623 kg CO2 eq. per kg bioplastic compared to 2.37 kg CO2 eq. per kg polypropylene as a petro-plastic. The results also showed that there are no significant potential effects for the bioplastics produced from potato peels on different environmental impacts in comparison with poly-β-hydroxybutyric acid and polypropylene. Thus, the bioplastics produced from agricultural wastes can be manufactured in industrial scale to reduce the dependence on petroleum-based plastics. This in turn will mitigate GHG emissions and reduce the negative environmental impacts on climate change.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

The objective of this paper is to analyze the factors influencing the success of real estate crowdfunding projects in Spain. This type of crowdfunding invests in real estate assets. We analyzed 60 projects published on the Housers platform, a kind of participative platform that uses the lending and equity crowdfunding modalities. These projects have involved around 36,623 investment decisions and have raised a total amount of almost 26 million euros. The empirical analysis is based on ordinary least squares and negative binomial regression. Our main findings reveal that success differs depending on the type of project; in fact, buy-to-sell projects are less successful than development loan projects. In addition, while total return has a positive impact on project success, in the case of risk level and project term, the impact is negative.

Abstract Commercial potential in developing countries has always received a great attention from international investors, but this is not the case in Waste-to-Energy sector. Waste-to-Energy is bound up with various uncertainties rooted in its long-term nature therefore incorporating risks regarding political matters in developing countries makes it more complex. The present study substantiates the incompatibility of classic valuation methods in risky projects. Consequently, to deal with the riskiness of Waste-to-Energy investment in less developed countries, the combination of binomial tree analysis and Decoupled NPV is proposed. The hybrid approach is deployed to value a Waste-to-Energy project in Iran, and all evidence attest to the robustness of the method. The contribution of this paper can open up new vistas for investing in Waste-to-Energy industry, thus abating the catastrophic effects of landfill gas emissions.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

SummaryInequality has recently become a major concern in economics. Leaving aside its social and economic effects is also possible to trace its environmental consequences, which this article attempts to assess. The indicator to be measured is the household's carbon footprint (CF) for different social groups. The deep economic crisis in the Spanish economy between 2008 and 2013 has increased consumption inequality and doubled the number of households below the poverty line. When focusing on domestic consumption, we found that the shopping basket of all income groups has very similar emissions intensities; therefore, the differences among the household CFs depend mainly on the scale effect (i.e., the size of consumption). However, when international trade is also considered, we found that the emission intensity of imports is bigger than the intensity of all the respective domestic goods. Therefore, the share of imported goods and services by social class will be an important determinant of the respective total CF. Before the crisis, households with higher incomes imported 30% of their total consumption items whereas households with lower income imported only 20% of their consumption. During the crisis, the imports of medium‐high‐income households fell to 20%, whereas low‐ and middle‐income families maintained the same import share, which contributed to the reduction of the total household CF.

In recent years, the energy consumption structure has been accelerating towards clean and low-carbon globally, and China has also set positive goals for new energy development, vigorously promoting the development and utilization of renewable energy, accelerating the implementation of renewable energy substitution actions, and focusing on improving the consumption capacity of new energy. However, due to the intermittent and unstable characteristics of renewable energy, it is difficult to meet the demands of the power load side in practical applications. Energy storage is an important link for the grid to efficiently accept new energy, which can significantly improve the consumption of new energy electricity such as wind and photovoltaics by the power grid, ensuring the safe and reliable operation of the grid system, but energy storage is a high-cost resource. Therefore, this paper focuses on the energy storage scenarios for a big data industrial park and studies the energy storage capacity allocation plan and business model of big data industrial park. Firstly, based on the characteristics of the big data industrial park, three energy storage application scenarios were designed, which are grid center, user center, and market center. On this basis, an optimal energy storage configuration model that maximizes total profits was established, and financial evaluation methods were used to analyze the corresponding business models. Finally, taking an actual big data industrial park as an example, the economic viability of energy storage configuration schemes under two scenarios was discussed, and an energy storage system construction plan was proposed to promote the zero-carbon target of the big data industrial park.

The monitoring of a waste separation process in the nuclear power industry is considered. Recent advances in gamma ray emission and electrical impedance tomography mean that it is now feasible to unite these two modalities into a novel dual-modality monitoring method. This paper considers a simple model problem for the identification of a boundary between two distinct waste streams in a semi-continuous rotation separator. The simplicity of the problem affords the opportunity to demonstrate the general feasibility of the approach whilst avoiding unnecessary complications.