• Energy Research
• DE close
• FR close
• Sustainability close

Social networks expand the communication tools of nature conservation. Nonetheless, to date there is hardly any scientific literature on nature conservation communication in social networks. For this reason, this paper examines 600 Facebook and Twitter posts of three German nature conservation organizations: Federal Agency for the Conservation of Nature (Bundesamt für Naturschutz, BfN), Naturschutzbund Deutschland e. V. (NABU), and World Wide Fund for Nature (WWF) Germany. Using the Mann–Whitney U method and Spearman’s rank correlation analysis, it reveals how post design affects communication success and provides respective recommendations for German conservation organizations. Communication success was divided into four indicators: reactions, comments, shares, and overall engagement as a synthesis of the three. On Facebook, the use of hashtags, images, and many characters (up to 1500) leads to higher success, whereas emojis and videos can reduce it. On Twitter, links, images, and longer posts promote user interactions. Emojis have a positive influence on comments and overall engagement, but a negative influence on reactions and shares. In addition, hashtags reduce overall engagement on Twitter. These results are discussed with reference to similar studies from other political fields in order to provide recommendations for conservation organizations. A validation and expansion of the presented results is recommended due to the growing relevance of digital nature conservation communication.

Integrating renewable energy sources (RES) into island microgrids is usually done to provide a cost-effective electricity supply. The integration process is carried out by scheduling generating unit operations with a unit commitment (UC) scheme to ensure low system operating costs. This article discusses developing a UC optimization method for integrating solar photovoltaic plants in Indonesia’s Eastern Sumba microgrid power system. The scope of this study is the optimization algorithm of the UC, which consists of a priority list (PL) for the UC stage and an economic dispatch (ED) that relies on a genetic algorithm (GA) to minimize total operating costs (TOC). The results show that the PL-GA algorithm performs better than the extended priority list (EPL), and combinations of genetic algorithm and Lagrange, by applying continuous problem dispatch and improved binary GA hourly dispatch to meet ramping constraints. The application of RES incentive programs, such as carbon taxes and incentives for RES generation in calculating the TOC, shows an improvement in the financial feasibility analysis of the internal rate of return (IRR) and net present value (NPV) of actual projects in Indonesia.

This study aimed at assigning climate-relevant gaseous emissions from ruminants to animal- or feed-related origin. Three adult rumen-cannulated German Holstein steers and three forage types (corn silage (CS), alfalfa silage (AS) and grass hay (GH)) were used in a 3 × 3 Latin square design. Each period consisted of 12 days (d), during which animals received 10 kg dry matter/day of one forage as sole feed. Gaseous samples from forages and the steers´ rumen were taken and analyzed for CO2, CH4, and N2O using gas chromatography. There were large differences in the amounts of CO2 and N2O emitting from the forage types. Most N2O came from AS and only small amounts from GH and CS. Results indicate that fermented forages rich in nitrogen can release climate-relevant N2O. The highest CO2 amounts were measured in CS. Methane was not detected in any forage sample. Animals consuming CS showed slightly lower CH4 concentrations in the rumen gas sample than animals fed AS or GH. Big differences were found for ruminal N2O with the highest concentration after AS ingestion such that the N2O measured in the rumen seems to originate from the used feedstuff.

Continuous advancements in Information and Communication Technology and the emergence of the Big Data era have altered how traditional power systems function. Such developments have led to increased reliability and efficiency, in turn contributing to operational, economic, and environmental improvements and leading to the development of a new technique known as Demand Side Management or DSM. In essence, DSM is a management activity that encourages users to optimize their electricity consumption by controlling the operation of their electrical appliances to reduce utility bills and their use during peak times. While users may save money on electricity costs by rescheduling their power consumption, they may also experience inconvenience due to the inflexibility of getting power on demand. Hence, several challenges must be considered to achieve a successful DSM. In this work, we analyze the power scheduling techniques in Smart Houses as proposed in most cited papers. We then examine the advantages and drawbacks of such methods and compare their contributions based on operational, economic, and environmental aspects.

Viewing a computationally-intensive problem as a self-contained challenge with its own hardware, software and scheduling strategies is an approach that should be investigated. We might suggest assigning heterogeneous hardware architectures to solve a problem, while parallel computing paradigms may play an important role in writing efficient code to solve the problem; moreover, the scheduling strategies may be examined as a possible solution. Depending on the problem complexity, finding the best possible solution using an integrated infrastructure of hardware, software and scheduling strategy can be a complex job. Developing and using ontologies and reasoning techniques play a significant role in reducing the complexity of identifying the components of such integrated infrastructures. Undertaking reasoning and inferencing regarding the domain concepts can help to find the best possible solution through a combination of hardware, software and scheduling strategies. In this paper, we present an ontology and show how we can use it to solve computationally-intensive problems from various domains. As a potential use for the idea, we present examples from the bioinformatics domain. Validation by using problems from the Elastic Optical Network domain has demonstrated the flexibility of the suggested ontology and its suitability for use with any other computationally-intensive problem domain.

Payments for ecosystem services (PES) are currently being discussed as one of the most promising tools in environmental and sustainability governance. However, much criticism has been voiced against overly optimistic assumptions of PES’ management potential towards sustainability. Several contributions to the debate show that PES fail both in reducing poverty and strengthening social justice. Additionally, they neglect problems of deliberation in decision-making, as well as the legitimacy of the applied environmental practices. Our empirical investigation on participatory and deliberative structures in already existing PES initiated by non-state actors contributes to the latter body of research. Based on the assumption that playing an active part in scheme design facilitates the consideration of justice and fairness, our case studies from Germany and the UK. present interesting results on the involvement of conflicting interests and their argumentation in the design process. Summing up these findings, we conclude that paying for ES rarely contributes to sustainable development in and of itself, but deliberatively designed schemes provide a formal setting to take aspects of justice into account.

The existing recycling chain of construction and demolition waste generally considers soil inert solid waste to be sent to landfills. As the most significant component of C&D (construction and demolition) waste, excavated soil occupies approximately half of landfills. Currently, excavated soil is a big issue in China’s Pearl River Delta. This paper investigated the composition and quantity of excavated soil in Shenzhen, China. In particular, the potential market demand for critical recycled sand (a key recycled material extracted from the excavated soil) was estimated. Furthermore, the technical analysis for excavated soil recycling takes an entire excavated soil recycling process’s perspective, delving into the process flow for the excavated soil and the recycled sand’s physicomechanical properties. Then, two mainstream and legitimate models of excavated soil recycling were considered: stationary plant recycling and on-site recycling. Each model’s financial and economic viability was assessed. The financial analysis focuses on investors’ perspectives, whose primary goal is to assess their investment profitability. The economic feasibility of the excavated soil stationary plant recycling and on-site recycling models in Shenzhen were then compared via benefit and cost analysis during the lifetime of the recycling equipment. A comprehensive, complete cost calculation and investment analysis revealed that Shenzhen’s excavated soil recycling business is profitable under the current market conditions. This study investigates scaled and effective excavated soil recycling and gives a technically and economically viable reference to the global excavated soil issue.