bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil State Testing Using Heavy Vehicle Vibrations
Authors: Kapustian Natalia K. , Antonovskaya Galina N. , Orlova Irina P.
Published: January 2022

Changes in the elastic characteristics of the railway subgrade have been determined using nonstop long-term (more than 50 days) train passage seismic observations. We examined the records of the broadband sensitive seismometer TC-120s in the low-frequency band (below 0.1 Hz) to obtain the subgrade response to various train passages and its relaxation after unloading. Analytical models of subgrade deformation by the train are proposed. When comparing models in the experiment, we showed that a lowpass filter (below 0.1 Hz) provides waveforms with parameters determined by the deformation properties of the soil. We carried out statistical processing of 1600 train seismic records and determined parameters characterizing the subgrade reaction to the vibration effects created by trains in the ultra-low-frequency range. Therefore, we can use these parameters to monitor after daily averaging and weekly smoothing. When observing the spring thawing of the soil, we considered the sensitivity of seismic monitoring using heavy vehicle vibrations, particularly changes in the soil state properties under a rise in ambient temperature. The presented observations can be used for seismic monitoring technology at an early stage of hazardous processes in the subgrade.
Microgrid Operation Optimization Using Hybrid System Modeling and Switched Model Predictive Control
Authors: Maślak Grzegorz , Orłowski Przemysław
Published: January 2022

Optimization of economic aspects of microgrid operation in both grid-connected and islanded mode leads to contradictive definitions of optimality for both modes. There is no general agreement on how to cope with this duality. To address this issue, as well as modern energy market requirements and a better renewable energy utilization necessity in the case of large facilities, a comprehensive control solution utilizing the appropriate model is needed. In response, the authors propose a hybrid microgrid model covering fundamental features and designed to work in conjunction with two switched receding horizon control laws. A relevant controller is chosen according to the current microgrid operation mode and its cost function tailored to specific demands of the islanded or grid-connected operation. Performed research led to a new switched hybrid model predictive control approach focused on microgrid economic optimization. This approach utilizes an appropriate hybrid microgrid model also contributed by the authors. The introduced solution turned out to be effective in overall energy cost reduction in the case of large commercial facilities, regardless of grid-connection and renewable generation scenarios. Furthermore, it also provides satisfactory renewable energy and storage capabilities utilization in changing grid connection conditions.
Effect of the Substrate to Inoculum Ratios on the Kinetics of Biogas Production during the Mesophilic Anaerobic Digestion of Food Waste
Authors: Khadka Aakash , Parajuli Anmol , Dangol Sheila , Thapa Bijay , Sapkota Lokesh , Carmona-Martínez Alessandro A. , Ghimire Anish
Published: January 2022

This study evaluates the effects of the varying substrate to inoculum ratios (S:I) of 0.5, 1, 2, 3, 4, 5, and 6 (volatile solids/VS basis) on the kinetics of biogas production during batch mesophilic (35 ± 1 °C) anaerobic digestion (AD) of simulated food waste (FW), using anaerobic digestate as the inoculum. Kinetic parameters during biogas production (scrubbed with NaOH solution) are predicted by the first-order and the modified Gompertz model. The observed average specific biogas yields are in descending order corresponding to the S:I ratios 1, 2, 4, 6, 3, 5, and 0.5, respectively, and the significant effect of the S:I ratio was observed. The tests with the S:I of 1 have the maximum average biogas production rates of 88.56 NmL/gVS.d, whereas tests with the S:I of 6 exhibited the lowest production rates (24.61 NmL/gVS.d). The maximum biogas yields, predicted by the first order and the modified Gompertz model, are 668.65 NmL/gVS (experimental 674.40 ± 29.10 NmL/gVS) and 653.17 NmL/gVS, respectively. The modified Gompertz model has been proven to be suitable in predicting biogas production from FW. VS removal efficiency is greater in higher S:I ratios, with a maximum of 78.80 % at the S:I ratio of 6, supported by the longer incubation time. Moreover, a significant effect of the S:I ratio is seen on kinetics and energy recovery from the AD of FW.
Indirect Fuel Rationing for a Special Self-Propelled Rolling Stock
Authors: Mitrofanov Alexander , Ivaschenko Anton , Avsievich Alexandr , Avsievich Vladimir , Golovnin Oleg
Published: January 2022

A method of indirect rationing of diesel fuel for special self-propelled rolling stock is presented, based on the identification of actual fuel consumption and controlled operating modes. Based on the results of test trips using automated accounting systems for operating modes and fuel consumption, the method allows us to assess reasonable volumes of fuel consumption in a specific section of the railway infrastructure. We show how the methods of identifying actual fuel consumption and operating modes can establish consumption rates of special self-propelled rolling stock without the use of automated fuel metering. The identification method is based on solving a multifactorial equation, the coefficients of which are determined in a program with statistical functions. To eliminate multicollinearity problems, the use of cluster analysis methods is proposed. Unlike traditional calculation methods, the method allows for the determination of the norming indicators in conditions of incomplete and partially incorrect data. The study was conducted using data on fuel consumption of special self-propelled rolling stock at a particular railway range and the relevant regulatory documents provided by Russian Railways. The results were obtained by applying the method to special self-propelled rolling stock used in the electrification and railway track departments of Russian Railways. The proposed method allows for simulation of the indicator of normalized fuel consumption with an accuracy not worse than 96%. Based on the obtained model of normalized fuel consumption, the method and parameters for identifying abnormal and unauthorized fuel overconsumption are shown. The criteria for identifying abnormal fuel overconsumption using the normalized standard deviation function were determined.
Revealing Renewable Energy Perspectives via the Analysis of the Wholesale Electricity Market
Authors: Chebotareva Galina , Tvaronavičienė Manuela , Gorina Larisa , Strielkowski Wadim , Shiryaeva Julia , Petrenko Yelena
Published: January 2022

The wholesale electricity and capacity market constitute the backbone of the Russian power industry. It is in this market that large suppliers and buyers operate, and its entire turnover is consequently transmitted to the retail market. Our paper presents a theoretical overview of the main tools for forming the cost of electricity and capacity in the wholesale market in Russia (depending on the regional affiliation), the type of end users, and the degree of state participation. We consider the specifics of the formation of the cost of electricity and capacity in the price and non-price wholesale markets of Russia, which differ in territorial, climatic, and economic characteristics, as well as the established structure of generation. In the empirical part of the paper, we carry out a structural analysis of the volumes of trade in electricity and capacity in the price and non-price zones of the market. Furthermore, we explain the reasons for the current dynamics of prices in the wholesale market. Using the obtained results, we calculate the maximum annual effect of the solar power plant operation in various zones of the Russian wholesale market, as well as in the retail market. In addition, we estimate the economic incentive for the transition of the functioning of power facilities from the wholesale to the retail market. Our results can be of considerable practical importance and might be used for improving the strategy for the development of the electric power industry at the regional level both in Russia and in the other countries.
Fuzzy Time Series Methods Applied to (In)Direct Short-Term Photovoltaic Power Forecasting
Authors: Serrano Ardila Vanessa María , Maciel Joylan Nunes , Ledesma Jorge Javier Gimenez , Ando Junior Oswaldo Hideo
Published: January 2022

Solar photovoltaic energy has experienced significant growth in the last decade, as well as the challenges related to the intermittency of power generation inherent to this process. In this paper we propose to perform short-term forecasting of solar PV generation using fuzzy time series (FTS). Two FTS methods are proposed and evaluated to obtain a global horizontal irradiance (GHI) value. The first is the weighted method and the second is the fuzzy information granular method. Using the direct proportionality of the power with the GHI, the spatial smoothing process was applied, obtaining spatial irradiance on which a first-order low pass filter was applied to simulated power photovoltaic system generation. Thus, this study proposed indirect and direct forecasting of solar photovoltaic generation which was statistically evaluated and the results showed that the indirect prediction showed better performance with GHI than the power simulation. Error statistics, such as RMSE and MBE, show that the fuzzy information granular method performs better than the weighted method in GHI forecasting.
Multiscale Analysis and Safety Assessment of Fresh and Electrical Aged Lithium-Ion Pouch Cells Focusing on Mechanical Behavior
Authors: Sprenger Marvin , Dölle Norbert , Schauwecker Florian , Raffler Marco , Ellersdorfer Christian , Sinz Wolfgang
Published: January 2022

Analyzing the impact of electrical aging on the lithium-ion cell’s mechanical behavior and safety is an important factor to assess the crash safety of electric vehicles during their lifetime. In this study, fresh and electrical aged state-of-the-art NCM pouch cells were investigated. Aged cells, which were cycled electrically to 90% state of health, under laboratory conditions in electric vehicle battery modules were used. The used charging/discharging strategy represents real customer behavior based on accelerated driving profiles. First, it is shown that electrical aging has a significant influence on the anodes’ and separators’ mechanical properties, which had a lower mechanical strength and stiffness under tension. Additionally, quasi-static cylindrical indentation and three-point bending tests were performed to investigate aging effects on cell level at varying state of charge (SOC). Aged cells with 0% SOC showed a right-shifted force–displacement curve and a 29% lower maximum force compared to fresh cells. Fully charged, aged cells reached a similar maximum force to fresh cells, but faster temperature increase and higher temperature peaks after internal short circuit. Inductively coupled plasma optical emission spectrometry analyses confirmed an increased lithium content on the anode surface, which is indicated in literature as a reason for the increased exothermic reaction of the aged cells. The results indicate a higher safety risk for the aged investigated pouch cells under mechanical loads based on their changed mechanical properties and thermal runaway behavior.
Sustainable Entrepreneurship for Business Opportunity Recognition: Analysis of an Awareness Questionnaire among Organisations
Authors: Fidlerová Helena , Stareček Augustín , Vraňaková Natália , Bulut Cagri , Keaney Michael
Published: January 2022

An important challenge for the future is focusing on sustainability in life and business. The three elements of sustainability (economic, environmental, and social), defined in 17 factors by the United Nations (UN) as the Sustainable Development Goals (SDGs), may, therefore, be the main drivers of business competitiveness and opportunity recognition. The main aim of the article is to identify the awareness level of sustainability and sustainable development goals in the context of business opportunity areas by analysing the results of a survey of organisations in six countries (Finland, Slovakia, Italy, Austria, Spain, and Turkey). A multilingual questionnaire, administered in six participating countries, was used as a collection tool to determine the organisation’s level of awareness regarding the SDGs. A research questionnaire was filled in by 238 respondents, providing a cross-cultural view of their attitudes, knowledge, and future interest in sustainability and the SDGs. The obtained results indicate differences in the approach to sustainability issues, the scope of knowledge, interest, competencies in sustainable development and SDGs, and the content of implementation of sustainability and SDGs in organisations in different sectors, regions and countries. Further statistical evaluation of the research hypotheses states the significant relationship between the two variables: sustainable strategy and the designation of a responsible employee in each organisation rs = 0.677 (α = 0.05). It is essential to eliminate the gap in the cross-cultural approach and knowledge in engaging with sustainable strategy and its implementation in current and future organisation activities in the context of sustainability and SDGs, in order to enhance opportunities for the growth of sustainability-focused entrepreneurship across different sectors and countries.
Forecasting Solar Home System Customers’ Electricity Usage with a 3D Convolutional Neural Network to Improve Energy Access
Authors: Kizilcec Vivien , Spataru Catalina , Lipani Aldo , Parikh Priti
Published: January 2022

Off-grid technologies, such as solar home systems (SHS), offer the opportunity to alleviate global energy poverty, providing a cost-effective alternative to an electricity grid connection. However, there is a paucity of high-quality SHS electricity usage data and thus a limited understanding of consumers’ past and future usage patterns. This study addresses this gap by providing a rare large-scale analysis of real-time energy consumption data for SHS customers (n = 63,299) in Rwanda. Our results show that 70% of SHS users’ electricity usage decreased a year after their SHS was installed. This paper is novel in its application of a three-dimensional convolutional neural network (CNN) architecture for electricity load forecasting using time series data. It also marks the first time a CNN was used to predict SHS customers’ electricity consumption. The model forecasts individual households’ usage 24 h and seven days ahead, as well as an average week across the next three months. The last scenario derived the best performance with a mean squared error of 0.369. SHS companies could use these predictions to offer a tailored service to customers, including providing feedback information on their likely future usage and expenditure. The CNN could also aid load balancing for SHS based microgrids.
Data-Driven Optimal Design of a CHP Plant for a Hospital Building: Highlights on the Role of Biogas and Energy Storages on the Performance
Authors: Bartolucci Lorenzo , Cordiner Stefano , De Maina Emanuele , Mulone Vincenzo
Published: January 2022

Combined heat and power (CHP) generation plants are an assessed valuable solution to significantly reduce primary energy consumption and carbon dioxide emissions. Nevertheless, the primary energy saving (PES) and CO2 reduction potentials of this solution are strictly related to the accurate definition and management of thermal and electric loads. Data-driven analysis could represent a significant contribution for optimizing the CHP plant design and operation and then to fully deploy this potential. In this paper, the use of a bi-level optimization approach for the design of a CHP is applied to a real application (a large Italian hospital in Rome). Based on historical data of the hospital thermal and electric demand, clustering analysis is applied to identify a limited number of load patterns representative of the annual load. These selected patterns are then used as input data in the design procedure. A Mixed Integer Linear Programming coupled with a Genetic Algorithm is implemented to optimize the energy dispatch and size of the CHP plant, respectively, with the aim of maximizing the PES while minimizing total costs and carbon emissions. Finally, the effects of integrating biogas from the Anaerobic Digestion (AD) of the Spent Coffee Ground (SCG) and Energy Storage (ES) technologies are investigated. The results achieved provide a benchmark for the application of these technologies in this specific field, highlighting performances and benefits with respect to traditional approaches. The effective design of the CHP unit allows for achieving CO2 reduction in the order of 10%, ensuring economic savings (up to 40%), when compared with a baseline configuration where no CHP is installed. Further environmental benefits can be achieved by means of the integration of AD and ES pushing the CO2 savings up to 20%, still keeping the economical convenience of the capital investment.
Investigation on Primary Breakup of High-Pressure Diesel Spray Atomization by Method of Automatic Identifying Droplet Feature Based on Eulerian–Lagrangian Model
Authors: Lei Yan , Wu Yue , Zhou Dingwu , Wang Kaixin , Qiu Tao , Deng Yuwan , Zhou Dan
Published: January 2022

To investigate primary breakup close to an injector, this paper presents both experimental and numerical research on high-pressure common-rail diesel injection. We propose a new method named SD-ELSA model to realize automatically identifying droplet features for high-pressure diesel spray based on the classic ELSA (Eulerian Lagrangian Spray Atomization) model; this method is suitable for varied injection operation conditions. The SD-ELSA first identifies the liquid bulk due to breakup of the continuous phase in near field, and then converts the Eulerian liquid bulk into Lagrangian particles to complete the calculation of the total spray atomization. The SD-ELSA model adopts two key criteria, i.e., the sphericity (S) and the particle diameter (D); the qualified liquid mass is transformed into Lagrangian particle, realizing the coupling of the Eulerian–Lagrangian model. The SD-ELSA model illustrates the total diesel spray atomization process from the breakup liquid column to the droplets.
Long-Term Hydrogen Storage—A Case Study Exploring Pathways and Investments
Authors: O’Dwyer Ciara , Dillon Jody , O’Donnell Terence
Published: January 2022

Future low-carbon systems with very high shares of variable renewable generation require complex models to optimise investments and operations, which must capture high degrees of sector coupling, contain high levels of operational and temporal detail, and when considering seasonal storage, be able to optimise both investments and operations over long durations. Standard energy system models often do not adequately address all these issues, which are of great importance when considering investments in emerging energy carriers such as Hydrogen. An advanced energy system model of the Irish power system is built in SpineOpt, which considers a number of future scenarios and explores different pathways to the wide-scale adoption of Hydrogen as a low-carbon energy carrier. The model contains a high degree of both temporal and operational detail, sector coupling, via Hydrogen, is captured and the optimisation of both investments in and operation of large-scale underground Hydrogen storage is demonstrated. The results highlight the importance of model detail and demonstrate how over-investment in renewables occur when the flexibility needs of the system are not adequately captured. The case study shows that in 2030, investments in Hydrogen technologies are limited to scenarios with high fuel and carbon costs, high levels of Hydrogen demand (in this case driven by heating demand facilitated by large Hydrogen networks) or when a breakthrough in electrolyser capital costs and efficiencies occurs. However high levels of investments in Hydrogen technologies occur by 2040 across all considered scenarios. As with the 2030 results, the highest level of investments occur when demand for Hydrogen is high, albeit at a significantly higher level than 2030 with increases in investments of large-scale electrolysers of 538%. Hydrogen fuelled compressed air energy storage emerges as a strong investment candidate across all scenarios, facilitating cost effective power-to-Hydrogen-to-power conversions.
Current Status and On-Going Development of VTT’s Kraken Core Physics Computational Framework
Authors: Leppänen Jaakko , Valtavirta Ville , Rintala Antti , Hovi Ville , Tuominen Riku , Peltonen Jussi , Hirvensalo Markus , Dorval Eric , Lauranto Unna , Komu Rebekka
Published: January 2022

The Kraken computational framework is a new modular calculation system designed for coupled core physics calculations. The development started at VTT Technical Research Centre of Finland in 2017, with the aim to replace VTT’s outdated legacy codes used for the deterministic safety analyses of Finnish power reactors. In addition to conventional large PWRs and BWRs, Kraken is intended to be used for the modeling of SMRs and emerging non-LWR technologies. The main computational modules include the Serpent Monte Carlo neutron and photon transport code, the Ants nodal neutronics solver, the FINIX fuel behavior module and the Kharon thermal hydraulics code, all developed at VTT. The core physics solution can be further coupled to system-scale simulations. In addition to development, significant effort has been devoted to verification and validation of the implemented methodologies. The reduced-order Ants code has been successfully used for steady-state, transient and burnup simulations of PWRs with rectangular and hexagonal core geometry. The Ants–Kharon–FINIX code sequence is actively used for the core design tasks in VTT’s district heating reactor project. This paper is a general overview on the background, functional description, current status and future plans for the Kraken framework. Due to the short history of development, Kraken has not yet been comprehensively validated or applied to full-scale core physics calculations. A review of previous studies is instead provided to exemplify the practical use.
Assessment and Integral Indexing of the Main Indicators of Oil and Gas Companies by Circular Convolution
Authors: Vygodchikova Irina , Gordienko Mikhail , Natocheeva Natalia , Rud Natalia , Namitulina Anzhela
Published: January 2022

In the oil and gas industry, which is the basis of the Russian energy market, a significant and urgent question arises: How to distribute companies according to their investment attractiveness? Accordingly, quantitative indicators are needed. Lacking extensive experience in the practical implementation of fundamental rating tools, work is needed to develop methodologies of weighting coefficients and lists, built on the experience of the “big three” rating agencies. The article proposes an algorithm for forming an integral rating of companies based on financial reporting indicators and the author’s rules of fuzzy logic based on the principle of “circular convolution”, from the best to the slave, deepening the analysis to the center, when all companies are exhausted and places in the rating are distributed. The problem of assessing and integrally indexing the indicators of large companies in leading sectors of the economy (e.g., oil and gas, banks, electricity) is becoming manifest, while it is obvious that there is competition between large companies of the country’s leading industries for state investment resources. The nature of the leading industries is such that it is necessary to assess the quality of the company’s functioning based on the formation of rating groups. Based on the rating, investments are distributed among the companies under consideration. The author has developed a portfolio model that is analogous to the Harry Max Markowitz model, which does not contradict this model but allows consideration of a broader range of risk assessments used in the model (for example, the rating of companies). The optimal portfolio is built, taking into account the resulting index and the initial grouping in the hierarchical data correction mode. The logically sequential method of circular convolution of four important indicators to an integral index and a mathematically substantiated method for optimizing the minimax portfolio presented in the work will allow the investor to develop optimal (from the point of view of the transparency of the apparatus used, mathematical feasibility and time spent on the implementation of the software package) tools for investing and enlarging his capital.
An Analytical Method for Calculating the Cogging Torque of a Consequent Pole Hybrid Excitation Synchronous Machine Based on Spatial 3D Field Simplification
Authors: Zhang Zhiyan , Zhang Ming , Yin Jing , Wu Jie , Yang Cunxiang
Published: January 2022

Consequent pole hybrid excitation synchronous (CPHES) machines have the advantage of symmetrical bidirectional magnetomotive force increments. Compared with a traditional hybrid excitation motor (HEM), a CPHES machine improves the disadvantage of asymmetry in the adjustment range when magnetization and demagnetization occur. The calculation and analysis of the cogging torque of the CPHES machine are complex due to the complicated structure. This paper proposes an analytical method for calculating the cogging torque of a CPHES machine. This analytical method converts the complex three-dimensional magnetic field problem into a two-dimensional magnetic circuit problem and, through the accumulation method, can quickly and accurately calculate the cogging torque of the CPHES machine. In contrast with the finite element method, the calculation results basically follow each other, but the analytical method is more efficient and omits complicated meshing. This is of great significance to the preliminary electromagnetic design and performance optimization of a CPHES machine.
Contribution of Road Transport to the Attainment of Ghana’s Nationally Determined Contribution (NDC) through Biofuel Integration
Authors: Saisirirat Peerawat , Rushman Johannex Fefeh , Silva Kampanart , Chollacoop Nuwong
Published: January 2022

Since the Paris Agreement in COP21, many countries around the world, including Ghana and Thailand, have established a Nationally Determined Contribution (NDC) to reduce greenhouse gas (GHG) emissions, with first update recently in COP26. With Ghana’s ongoing effort at COP26 to change its baseline to 2019, this study established a detailed Ghana vehicle ownership model with necessary transport parameters to construct an energy demand model to provide insight for reducing GHG emission contributions from road transport through biofuel (both bioethanol and biodiesel) potential by recourse to a Low Emission Analysis Platform (LEAP), with two scenarios of development from Thailand’s best practice for policy recommendation, which are alternative (ALT), with up to E20/B20, and extreme (EXT), with up to E85/B50, for new vehicles. In each case, energy demand and GHG emissions were analyzed from detailed data on Ghana’s transport sector to show potential benefit from biofuel usages. From Ghana’s transport sector contribution to NDC, 8.4% and 11.1% of GHG emission reduction in 2030 can be achieved with a 0.13% and 0.27% additional arable land requirement from ALT and EXT scenarios. Policy recommendation and implication were also discussed.
Research on the Application Performance of the Helmholtz High-Efficiency Wave-Elimination Chamber in Gas Wave Tubes
Authors: Nuermaimaiti Wutekuer , Liu Xuewu , Yan Pengze , Zou Jiupeng , Hu Dapeng
Published: January 2022

A gas wave refrigerator is a device that uses gas pressure to expand and refrigerate; the moving shock wave in the gas wave tube is the key to cooling. If the shock wave is reflected to the open mouth of the gas wave tube, it will heat the expanded refrigeration gas at the open end, severely reducing the refrigeration efficiency. In order to reduce this effect, a Helmholtz middle wave chamber-type gas wave tube is presented here. This study describes the performance of this structure in the gas wave refrigeration process. The refrigeration performance of the structure’s gas wave tube use was evaluated experimentally and numerically using computational fluid dynamics (CFD). The function of the middle wave elimination chamber was studied and explained: the chamber turns the reflected shock wave back to the end section of the tube and converts part of the incoming shock wave to an expansion wave, which may counteract the reflected shock wave by escaping from wave elimination chamber. The experimental results showed that the structure increased refrigeration efficiency by about 2.9% (50 Hz), 2% (40 Hz), and 2.2% (25 Hz) at the corresponding ejection frequencies, and reduced the reflected shock wave intensity by 11%, which proves the high-efficiency energy dissipation performance and the significant increase in refrigeration efficiency of the Helmholtz-type gas wave tube.
Assessment of Waterfront Office Redevelopment Plan on Optimal Building Arrangements with Rooftop Photovoltaics: A Case Study for Shinagawa, Tokyo
Authors: Choi Younghun , Kobashi Takuro , Yamagata Yoshiki , Murayama Akito
Published: January 2022

Designing waterfront redevelopment generally focuses on attractiveness, leisure, and beauty, resulting in various types of building and block shapes with limited considerations on environmental aspects. However, increasing climate change impacts necessitate these buildings to be sustainable, resilient, and zero CO2 emissions. By producing five scenarios (plus existing buildings) with constant floor areas, we investigated how buildings and district forms with building integrated photovoltaics (BIPV) affect energy consumption and production, self-sufficiency, CO2 emission, and energy costs in the context of waterfront redevelopment in Tokyo. From estimated hourly electricity demands of the buildings, techno-economic analyses were conducted for rooftop PV systems for 2018 and 2030 with declining costs of rooftop PV systems. We found that environmental building designs with rooftop PV system are increasingly economical in Tokyo with CO2 emission reduction of 2–9% that depends on rooftop sizes. Payback periods drop from 14 years in 2018 to 6 years in 2030. Toward net-zero CO2 emissions by 2050, immediate actions are necessary to install rooftop PVs on existing and new buildings with energy efficiency improvements by construction industry and building owners. To facilitate such actions, national and local governments need to adopt appropriate policies.
How Environmental Regulation, Digital Development and Technological Innovation Affect China’s Green Economy Performance: Evidence from Dynamic Thresholds and System GMM Panel Data Approaches
Authors: Jia Lijiang , Hu Xiaoli , Zhao Zhongwei , He Bin , Liu Weiming
Published: January 2022

Based on the background of China’s “carbon neutral” policy and the booming digitalization, how does environmental regulation affect green economy performance? The existing literature has studied the impact of energy consumption on green economic performance. However, the literature has ignored the impact of carbon dioxide emissions on China’s green economy performance. In this regard, this research uses the non-radial distance function (NDDF) to calculate the green economic performance of China’s prefecture-level cities, and uses the dynamic panel threshold model and the systematic GMM method to study the nonlinear impacts and mechanisms of environmental regulation, digital development, technological innovation, and industrial structure upgrade on green economic performance. The panel data set contains 228 Chinese cities from 2003 to 2019. The following findings are established: first, after adding carbon dioxide emissions to China’s green economy performance, the environmental performance was reduced, and the green economy performance was also reduced. Second, the impact of environmental regulations on green economic performance has a double-threshold effect, with threshold values of −0.267 and 3.602, and this double-threshold effect has temporal and regional heterogeneity. Third, environmental regulations of different intensities have a single-threshold effect between digital development, technological innovation, and industrial structure upgrade, with threshold values of 2.955, 3.957, and 2.249, respectively. Fourth, digital development, technological innovation, and industrial structure upgrade promote green economic performance. Fifth, environmental regulation acts on green economic performance through the transmission of digitalization, technological innovation, and industrial structure upgrade. Based on these empirical findings, this research suggests that Chinese local governments should appropriately increase the intensity of environmental regulations, strengthen the digital application and technological innovation, and promote the upgrading of industrial structure to achieve the improvement of urban green economic performance.
Methods and Techniques for CO2 Capture: Review of Potential Solutions and Applications in Modern Energy Technologies
Authors: Madejski Paweł , Chmiel Karolina , Subramanian Navaneethan , Kuś Tomasz
Published: January 2022

The paper presents and discusses modern methods and technologies of CO2 capture (pre-combustion capture, post-combustion capture, and oxy-combustion capture) along with the principles of these methods and examples of existing and operating installations. The primary differences of the selected methods and technologies, with the possibility to apply them in new low-emission energy technologies, were presented. The following CO2 capture methods: pre-combustion, post-combustion based on chemical absorption, physical separation, membrane separation, chemical looping combustion, calcium looping process, and oxy-combustion are discussed in the paper. Large-scale carbon capture utilization and storage (CCUS) facilities operating and under development are summarized. In 2021, 27 commercial CCUS facilities are currently under operation with a capture capacity of up to 40 Mt of CO2 per year. If all projects are launched, the global CO2 capture potential can be more than ca. 130–150 Mt/year of captured CO2. The most popular and developed indicators for comparing and assessing CO2 emission, capture, avoiding, and cost connected with avoiding CO2 emissions are also presented and described in the paper.
Editorial Note from the EiC
Authors: Sciubba Enrico
Published: January 2022

The material published in this “Discussion”—and the very reason for which we decided to publish it—requires a clarification on the part of the journal Management; therefore, I advise readers to peruse this foreword before embarking in the task of studying the often polemical statements and counter-statements contained in the Seibert and Rees paper, in the Diesendorf and Fthenakis et al [...]
Using Wood-Based Waste from Grapevine Cultivation for Energy Purposes
Authors: Maj Grzegorz , Klimek Kamila , Kapłan Magdalena , Wrzesińska-Jędrusiak Edyta
Published: January 2022

This paper presents the possibility of the energetic utilization of biowaste in the form of lignified one-year shoots from the cultivation of grapevines of the Seyval Blanc (WSBL), Solaris (WSOL), Regent (WREG) and Rondo (WRON) varieties, grown in temperate climate zones. A technical analysis, an elemental analysis and the determination of the highest heat value and lowest heat value were performed to define the quality parameters of waste as fuel. In addition, the emission factors of SO2, NOx, CO, CO2 and dust were estimated to demonstrate the impact of potential biowaste from combustion. Based on the stoichiometric equations, the exhaust gas composition, the theoretical oxygen demand and the total flue gas volume were evaluated. The study showed that the material with the highest energy potential was WREG (LHV-16.19 MJ·kg−1), with an ash content of 3.68%, while the lowest potential was found for WRON (LHV-15.88 MJ·kg−1), with an ash content of 4.21%. The study showed that the use of the studied viticulture waste instead of hard coal could reduce CO emissions by 26–27%, CO2 by 24–26%, NOx by 55–56%, SO2 by 96–97% and dust by 77–80%.
Numerical Modeling of Energy Systems Based on Micro Gas Turbine: A Review
Authors: Reale Fabrizio , Sannino Raniero
Published: January 2022

In the context of the great research pulse on clean energy transition, distributed energy systems have a key role, especially in the case of integration of both renewable and traditional energy sources. The stable interest in small-scale gas turbines can further increase owing to their flexibility in both operation and fuel supply. Since their not-excellent electrical efficiency, research activities on micro gas turbine (MGT) are focused on the performance improvements that are achievable in several ways, like modifying the Brayton cycle, integrating two or more plants, using cleaner fuels. Hence, during the last decades, the growing interest in MGT-based energy systems encouraged the development of many numerical approaches aimed to provide a reliable and effective prediction of the energy systems’ behavior. Indeed, numerical modeling can help to individuate potentialities and issues of each enhanced layout or hybrid energy system, and this review aims to discuss the various layout solutions proposed by researchers, with particular attention to recent publications, highlighting the adopted modeling approaches and methods.
Soil Remediation: Towards a Resilient and Adaptive Approach to Deal with the Ever-Changing Environmental Challenges
Authors: Grifoni Martina , Franchi Elisabetta , Fusini Danilo , Vocciante Marco , Barbafieri Meri , Pedron Francesca , Rosellini Irene , Petruzzelli Gianniantonio
Published: January 2022

Pollution from numerous contaminants due to many anthropogenic activities affects soils quality. Industrialized countries have many contaminated sites; their remediation is a priority in environmental legislation. The aim of this overview is to consider the evolution of soil remediation from consolidated invasive technologies to environmentally friendly green strategies. The selection of technology is no longer exclusively based on eliminating the source of pollution but aims at remediation, which includes the recovery of soil quality. “Green remediation” appears to be the key to addressing the issue of remediation of contaminated sites as it focuses on environmental quality, including the preservation of the environment. Further developments in green remediation reflect the aim of promoting clean-up strategies that also address the effects of climate change. Sustainable and resilient remediation faces the environmental challenge of achieving targets while reducing the environmental damage caused by clean-up interventions and must involve an awareness that social systems and environmental systems are closely connected.
Development and Validation of a 36K SNP Array for Radiata Pine (Pinus radiata D.Don)
Authors: Graham Natalie , Telfer Emily , Frickey Tancred , Slavov Gancho , Ismael Ahmed , Klápště Jaroslav , Dungey Heidi
Published: January 2022

Radiata pine (Pinus radiata D.Don) is one of the world’s most domesticated pines and a key economic species in New Zealand. Thus, the development of genomic resources for radiata pine has been a high priority for both research and commercial breeding. Leveraging off a previously developed exome capture panel, we tested the performance of 438,744 single nucleotide polymorphisms (SNPs) on a screening array (NZPRAD01) and then selected 36,285 SNPs for a final genotyping array (NZPRAD02). These SNPs aligned to 15,372 scaffolds from the Pinus taeda L. v. 1.01e assembly, and 20,039 contigs from the radiata pine transcriptome assembly. The genotyping array was tested on more than 8000 samples, including material from archival progenitors, current breeding trials, nursery material, clonal lines, and material from Australia. Our analyses indicate that the array is performing well, with sample call rates greater than 98% and a sample reproducibility of 99.9%. Genotyping in two linkage mapping families indicated that the SNPs are well distributed across the 12 linkage groups. Using genotypic data from this array, we were also able to differentiate representatives of the five recognized provenances of radiata pine, Año Nuevo, Monterey, Cambria, Cedros and Guadalupe. Furthermore, principal component analysis of genotyped trees revealed clear patterns of population structure, with the primary axis of variation driven by provenance ancestry and the secondary axis reflecting breeding activities. This represents the first commercial use of genomics in a radiata pine breeding program.
Wind Damage and Temperature Effect on Tree Mortality Caused by Ips typographus L.: Phase Transition Model
Authors: Soukhovolsky Vladislav , Kovalev Anton , Tarasova Olga , Modlinger Roman , Křenová Zdenka , Mezei Pavel , Škvarenina Jaroslav , Rožnovský Jaroslav , Korolyova Nataliya , Majdák Andrej , Jakuš Rastislav
Published: January 2022

The aim of this study was to develop methods for constructing a simple model describing tree mortality caused by Ips typographus L. using a minimum number of variables. We developed a model for areas spanning natural mountain forests in the Tatra National Park (Slovakia) and the Šumava National Park (Czech Republic), and in managed Czech forests located in four areas varying in environmental conditions. The model describes the time series of tree mortality dynamics caused by I.typographus using two submodels: a long-term dynamics submodel, and a short-term dynamics autoregressive distributed lag(ADL) model incorporating a two year delay and temperature variable averaged over the April-May period. The quality of fit for our models (R2 value) ranged from 0.87 to 0.91. The model was formulated to capture the average monthly temperature effect, a key weather factor. We found that for high-elevation stands located at least 1000 ma.s.l., forest damage was predominantly influenced by May temperatures. For lower-elevation managed forests with warmer climates, the weather effect was insignificant.
Effects of Farmland Conversion to Orchard or Agroforestry on Soil Organic Carbon Fractions in an Arid Desert Oasis Area
Authors: Wang Weixia , Ingwersen Joachim , Yang Guang , Wang Zhenxi , Alimu Aliya
Published: January 2022

In southern Xinjiang province, northwest China, farmland is undergoing rapid conversion to orchards or agroforestry. This has improved land-use efficiency but has also caused drastic ecological changes in this region. This study investigated the effects of farmland conversion to orchard or agroforestry on soil total organic carbon (TOC) and several soil labile fractions: readily oxidizable carbon (ROC), light fraction organic carbon (LFOC), and dissolved organic carbon (DOC). Soil samples were collected from seven cropping treatments: a monocultured wheat field (Mono), a 5-year-old jujube orchard (5 J), a 5-year-old jujube/wheat alley cropping system (5 JW), a 10-year-old jujube orchard (10 J), a 10-year-old jujube/wheat alley cropping system (10 JW), a 15-year-old jujube orchard (15 J), and a 15-year-old jujube/wheat alley cropping system (15 JW). The results show that the ROC concentrations varied from 0.17 ± 0.09 g/kg to 2.35 ± 0.05 g/kg across all land-use types and soil depths studied. It was higher in the 0–10 cm and 10–20 cm layers of treatment 10 JW than in other treatments and significantly greater than in the Mono treatment. The highest value of DOC was reached at 593.04 mg/kg in the 15 JW treatment at 0–10 cm. Labile organic carbon decreased with increasing depth in all treatments. The proportion of ROC and LFOC to TOC decreased with increasing soil depth. In all treatments, the ratio of DOC to TOC generally decreased initially and then increased again with increasing depth. Correlation analysis showed that ROC, LFOC, and DOC were closely correlated with TOC (p < 0.01). The ROC, LFOC, and DOC concentrations were significantly correlated with each other (p < 0.01). Following conversion of farmland to jujube orchard or agroforestry, the content and activity of soil organic carbon tended to increase due to augmentation of plant residues. Thus, jujube orchards and agroforestry systems are effective methods to restore soil organic carbon.
Bioactivity, Physicochemical and Sensory Properties of Probiotic Yoghurt Made from Whole Milk Powder Reconstituted in Aqueous Fennel Extract
Authors: Atwaa El Sayed Hassan , Shahein Magdy Ramadan , El-Sattar El Sayed Abd , Hijazy Hayfa Hussin Ali , Albrakati Ashraf , Elmahallawy Ehab Kotb
Published: January 2022

Fermented dairy products have long been associated with positive health benefits. The present study was undertaken to evaluate the physicochemical and sensory properties, viable probiotic counts, antioxidant activity and total phenolic content of probiotic yoghurt made by reconstituting of whole milk powder in aqueous fennel seed extract. Different concentrations of fennel aqueous seeds extract (2%, 4% and 6% w/v) were used as a substitute for water to reconstitute whole milk powder in formulations of yoghurt as functional additives. Interestingly, the use of aqueous extract of fennel seeds in the reconstituted yoghurt milk did not affect yoghurt composition (moisture, protein, fat and ash contents) compared to plain yoghurt. The titratable acidity significantly decreased after using aqueous fennel seed extract in the yogurt manufacture. In this regard, the titratable acidity value was 0.85 in the control yogurt at the fresh period and 1.14 after 21 days of storage, while this value significantly decreased in the yogurt treatments with 2%, 4% and 6% aqueous fennel seed extract to 80, 0.77 and 0.72, respectively, at fresh period and reached 1.03, 0.96 and 0.94, respectively, after 21 days of storage (p < 0.05). Conversely, the pH values significantly increased (p < 0.05) following the addition of aqueous fennel seed extract in the yogurt manufacture. Moreover, the total phenolic content significantly increased (p < 0.05) from 38.60 (mg GAE/L), in fresh plain yogurt, to 44.80, 53.20 and 64.30 (mg GAE/L), in 2% fennel extract yoghurt (FEY2), 4% fennel extract yoghurt (FEY4) and 6% fennel extract yoghurt (FEY6), respectively. Likewise, the antioxidant activity significantly increased (p < 0.05) from 0.11 (mM TE) in fresh plain yogurt to 0.18, 0.26 and 0.32 (mM TE) in (FEY2), (FEY4) and (FEY6), respectively. The survival of Lactobacillus acidophilus, Streptococcus thermophilus and Bifidobacterium bifidum decreased during storage time in all yoghurt treatments, although it stood at recommended levels for health effects (at least 106 cfu/mL in traditional yoghurt). For sensory evaluation, FEY4 was more acceptable, followed by FEY6, FEY2 and PY, respectively. Collectively, the present study provides useful information about the bioactivity, physicochemical and sensory properties of probiotic yoghurt made from whole milk powder reconstituted in aqueous fennel extract.