• Energy Research
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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.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

In this paper, the performances of two iron-based syngas-fueled chemical looping (SCL) systems for hydrogen (H2) and electricity production, with carbon dioxide (CO2) capture, using different reactor configurations were evaluated and compared. The first investigated system was based on a moving bed reactor configuration (SCL-MB) while the second used a fluidized bed reactor configuration (SCL-FB). Two modes of operation of the SCL systems were considered, namely, the H2 production mode, when H2 was the desired product from the system, and the combustion mode, when only electricity was produced. The SCL systems were modeled and simulated using Aspen Plus software. The results showed that the SCL system based on a moving bed reactor configuration is more efficient than the looping system with a fluidized bed reactor configuration. The H2 production efficiency of the SCL-MB system was 11 % points higher than that achieved in the SCL-FB system (55.1 % compared to 44.0 %). When configured to produce only electricity, the net electrical efficiency of the SCL-MB system was 1.4 % points higher than that of the SCL-FB system (39.9 % compared to 38.5 %). Further, the results showed that the two chemical looping systems could achieve >99 % carbon capture efficiency and emit ~2 kg CO2/MWh, which is significantly lower than the emission rate of conventional coal gasification-based plants for H2 and/or electricity generation with CO2 capture.

Biological infestations in forests, e.g. the insect outbreaks, have been shown as favoured by future climate change trends. In Europe, the European spruce bark beetle (Ips typographus L.) is one of the main agents causing substantial economic disturbances in forests. Therefore, studies on spatio-temporal characterization of the area affected by bark beetle are of major importance for rapid post-attack management. We aimed at spatially detecting damage classes by combining multidate remote sensing data and a non-parametric classification. As study site served a part of the Bavarian Forest National Park (Germany). For the analysis, we used 10 geometrically rectified scenes of Landsat and SPOT sensors in the period between 2001 and 2011. The main objective was to explore the potential of medium-resolution data for classifying the attacked areas. A further aim was to explore if the temporally adjacent infested areas are able to be separated. The random forest (RF) model was applied using the reference data drawn from high-resolution aerial imagery. The results indicate that the sufficiently large patches of visually identifiable damage classes can be accurately separated from non-attacked areas. In contrast to those, the other mortality classes (current year, current year 1 and current year 2 infested classes) were mostly classified with higher commission or omission errors as well as higher classification biases. The available medium-resolution satellite images, combined with properly acquired reference data, are concluded to be adequate tools to map area-based infestations at advanced stages. However, the quality of reference data, the size of infested patches and the spectral resolution of remotely sensed data are the decisive factors in case of smaller areas. Further attempts using auxiliary height information and spatially enhanced data may refine such an approach.

Background. Laws that enable a circular economy (CE) are being enacted globally, but reliable standardized and digitized CE data about products is scarce, and many CE platforms have differing exclusive formats. In response to these challenges, the Ministry of The Economy of Luxembourg launched the Circularity Dataset Standardization Initiative to develop a globalized open-source industry standard to allow the exchange of standardized data throughout the supply cycle, based on these objectives: (a) Provide basic product circularity data about products. (b) Improve circularity data sharing efficiency. (c) Encourage improved product circularity performance. A policy objective was to have the International Organization for Standardization (ISO) voted to create a working group. Methods. A state-of-play analysis was performed concurrently with consultations with industry, auditors, data experts, and data aggregation platforms. Results. Problem statements were generated. Based on those, a solution called Product Circularity Data Sheet (PCDS) was formulated. A proof of concept (POC) template and guidance were developed and piloted with manufacturers and platforms, thus fulfilling objective (a). For objective (b), IT ecosystem requirements were developed, and aspects are being piloted in third party aggregation platforms. Objective (c) awaits implementation of the IT ecosystem. The policy objective related to the ISO was met. Conclusions and future research. In order to fully test the PCDS, it is necessary to: conduct more pilots, define governance, and establish auditing and authentication procedures.

Abstract With the rise of awareness of health and well-being in cities, urban environmental analysis should expand from energy performance to new environmental quality-based considerations. The limited potential to annually evaluate outdoor thermal comfort, predominant among these considerations, has restricted the exploration of the interrelations between urban morphology and annual energy performance. This study aims to bridge this gap by capitalizing on the new capabilities of Eddy3D – a Grasshopper plugin which enables effective calculations of hourly microclimatic wind factors via OpenFOAM which in turn are used to generate annual outdoor thermal comfort plots. Using this method, a parametric study was conducted for different typology and density scenarios in three different hot climatic contexts in Israel. The automated analytical workflow evaluated a total of 60 design iterations for their energy balance, outdoor thermal comfort autonomy (OTCA) and self-shading levels using the shade index. The high correlation found here between the annual shade index and the OTCA, across all climatic contexts, shows the potential of the shade index to serve as an effective indicator, in these contexts, for comparative or optimization outdoor comfort studies. Further results are both the superiority of the courtyard typology in both energy and outdoor comfort studies, and the contrasting impact of higher density on the annual energy balance (lower performance) and outdoor thermal comfort (higher performance) in hot climates. The annual plots of both the energy balance and OTCA reveal various seasonal and monthly trends in the three different climatic zones which can lead to localized and seasonal urban design strategies.

Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.

Gasification is considered to be a promising way to use biomass with high efficiency in combined heatand power production, for the production of second generation biofuels and in the chemical industry.Especially allothermal fluidized bed steam gasification produces a medium calorific, nitrogen free gassuitable for a variety of downstream processes. In general the raw product gas has to be cleaned fromcondensable hydrocarbons (tar) and conditioned (e.g. adjustment of the H2/CO-ratio) before downstreamuse. The operating conditions of the gasification reactor have a large impact on the quality of the productgas. Hence first steps to a product gas low in tar content can be undertaken directly in the reactor. In thisstudy the capability of influencing the tar content and gas composition by changing temperature (750?840 C), steam to biomass (S/B) ratio (0.8?1.2) and pressure (0.1?0.25 MPa) in an allothermal bubblingfluidized bed steam gasifier is investigated. It is found that rising temperature reduces the total tar contentand affects especially heterocyclic and light aromatic compounds. At atmospheric pressure the naphthalenecontent increases slightly with increasing temperature in contrary to pressurized gasificationwhere naphthalene decreases significantly with increasing temperature. An increase in the S/B ratio leadsto a decreasing total tar content, this tar reduction according to a higher steam content is higher at highertemperatures. Increasing pressure leads to increasing total tar content mainly due to naphthalene, theeffect is most distinct for low S/B ratios.