Potential Cost Reduction Research Articles

Decarbonization through smart energy management: Climate control in building-integrated rooftop greenhouses for urban agriculture across various climate conditions

This paper investigates the potential benefits of integrating rooftop greenhouses (RTGs) with buildings to reduce energy and CO2 costs, contributing to urban decarbonization efforts. This integration not only advances sustainable urban agriculture but also aligns with the United Nations Sustainable Development Goal 7 (SDG7) - Affordable and Clean Energy, and Sustainable Development Goal 11 (SDG11) - Sustainable Cities and Communities, through its energy-efficient, low-carbon approach. We hypothesize that this integration can significantly lower energy use in integrated RTGs (i-RTGs) and set out to validate this through dynamic models for both building and i-RTG climates, focusing on CO2 concentration, humidity, and temperature. Central to our approach is the implementation of a nonlinear model predictive control (NMPC) framework, which utilizes these dynamic models to make control decisions aimed at minimizing total control costs. This framework operates in a receding horizon procedure, regulating climate factors within the i-RTG and building using various actuators. We validate our approach by simulating an i-RTG atop a building in eleven different cities, demonstrating interactions such as energy, moisture, and CO2 exchange. Significantly, our study reveals that integrating i-RTG with buildings under the NMPC framework leads to a 15.2% reduction in control costs. Additionally, we find that the i-RTG model is adaptable to different climates, with colder regions showing greater cost reduction potential. Our study underscores the viability and advantages of integrating i-RTGs with buildings, offering a sustainable, decarbonizing solution for urban agriculture and building management that contributes to the fulfillment of SDG7 and SDG11.

Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios

AbstractRecent water infrastructure planning models demonstrate that explicitly accounting for hydrological changes in long‐term water planning reduces costs and increases system robustness. However, current models do not consider the effects of other changes occurring in the system over long time horizons, namely technology and policy innovation. By leveraging state‐of‐the‐art dynamic control techniques, we propose a suite of tools that explicitly relate hydrologic change, technology innovation, and policy interventions to system‐level water costs. We design robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states, for example, treatment cost and diversification improvements, deployment times, and demand reduction campaigns. Our approach circumvents the need to pre‐assign probabilities to innovation scenarios and, instead, directly calculates the effects of technology, policy, and hydrology variations on system cost and planning strategies to identify avenues of impactful innovation. These tools can support technology development hubs, urban, state, and federal water planners in anticipating cost implications of technology and policy innovation at the local level, and prioritizing high‐impact innovation goals based on quantitative targets. Results for the case study of Santa Barbara, California identify high‐value innovation attributes for the city as well as combinations of innovation attributes across technologies and policies, and quantify their potential utility cost reductions.

Advancing thermochemical storage: synthesis and characterization of cement-based composite materials

Thermal Energy Storage (TES) is crucial for sustainability of the energy sector, yet the development of cost-effective, robust materials remains a significant challenge. This study aims at exploring the synthesis and thermal characterization of cement-based composites for seasonal thermochemical energy storage, with the goal to harness the high energy density of hygroscopic salts while mitigating their limitations. We investigate composites with several cement matrices to improve salt-cement compatibility. Furthermore, we investigate the possible incorporation of porous low-cost compounds to enhance porosity and improve economic aspects. As far as the characterization aspects are concerned, we show experimental adsorption isotherms at different temperatures to estimate key material properties like isosteric heat and water uptake, along with the relevant figures of merit such as energy density. Our research leverages on adjustable porosity and affordability of cement as a host matrix for the ‘active phase’. We studied two synthesis approaches: traditional dry impregnation and an in-situ technique suitable for cements. The in-situ method, being straightforward and reproducible, permits greater control over salt content. Preliminary cost analysis positions these composites competitively in the market. Although we are still at sub-optimal stage, potential cost reduction of some less popular cement matrices suggests an opportunity for improvement.

Benchmarking L-PBF Systems for Die Production: Powder, Dimensional, Surface, Microstructural and Mechanical Characterisation

While conventional die manufacturing techniques often lead to limitations in production speed and design intricacy due to labour-intensive procedures like machining and casting, Additive Manufacturing (AM) emerges as a key player offering substantial potential for cost reduction and process improvement in mass production. This study benchmarks four leading Laser Powder Bed Fusion (L-PBF) systems for producing maraging steel (EN 1.2709) dies. Despite the shared material and technology, variations in dimensional accuracy, surface finish, and microstructure were observed among the maraging steel parts. SEM/EDS, EBSD, hardness testing, and dimensional analysis revealed system-specific performance differences. Additionally, select parts underwent heat treatment and tensile testing, demonstrating the impact of post-processing on mechanical properties. These results offer valuable guidance for industrial stakeholders considering AM, highlighting the importance of supplier selection and process optimisation for achieving consistent part quality and unlocking the full potential of AM technologies.

Biomass to green surfactants: Microwave-assisted transglycosylation of wheat bran for alkyl glycosides production

Depolymerization of carbohydrate biomass using a long-chain alcohol (transglycosylation) to produce alkyl glycoside-based bio-surfactants has been gaining industrial interest. This study introduces microwave-assisted transglycosylation in transforming wheat bran, a substantial agricultural side stream, into these valuable compounds. Compared to traditional heating, microwave-assisted processing significantly enhances the product yield by 53 % while reducing the reaction time by 72 %, achieving a yield of 29 % within 5 h. This enhancement results from the microwave's capacity to activate intermolecular hydrogen and glycosidic bonds, thereby facilitating transglycosylation. Life-cycle assessment and techno-economic analysis demonstrate the benefits of microwave heating in reducing energy consumption by 42 %, CO2 emissions by 56 %, and equipment, operational and production costs by 44 %, 35 % and 30 %, respectively. The study suggests that microwave heating is a promising approach for efficiently producing bio-surfactants from agricultural wastes, with potential cost reductions and environmental benefits that could enhance industrial biomass conversion processes.

CO2 Capture Cost Reduction Potential of the Coal-Fired Power Plants under High Penetration of Renewable Power in China

With a significant share of renewable power generation integrated into the power supply, it is crucial to timely adjust the regulating peak load for coal-fired power plants equipped with CO2 capture to ensure the stable operation of the multi-energy supply system. In this paper, the effects of varying boiler loads on the techno-economic performance of the retrofitted power plant were studied. Furthermore, the potential for reducing the cost of CO2 capture was investigated, and early opportunities for demonstration were discussed. Results showed that when the boiler load decreased from 100% turbine heat acceptance condition to 50% turbine heat acceptance condition, the cost of CO2 capture increased from 37.0 $/t CO2 to 57.0 $/t CO2, cost contribution of energy penalty and extra capital investment also increased from 20.6 $/t-CO2 to 25.7 $/t-CO2, and from 16.4 $/t-CO2 to 31.3 $/t-CO2, respectively. Furthermore, by improving separation efficiency from 0.15 to 0.5, a 25% to 30% reduction in CO2 capture cost can be achieved. The cost of CO2 capture could decrease by 42.2–50.5% when the cumulative capacity reaches 250 GW under the high investment learning rate scenario. According to the distribution of coal prices and renewable energy sources in China, the early demonstration projects of multi-energy supply systems should prioritize the northern region. The results of this work can provide informative references for making roadmaps and policies for CO2 emission reduction toward carbon neutrality.

Decision Making on a Software Upgrade or Decommission with Data Mining and Machine Learning Techniques in Information Technology Industry

The Organizations have been investing more in Technology and Infrastructure spends like software upgrades, software renewals, software replacements, platform migrations etc., apart from investment in Business, People, and Processes. In this context, it is not an easy task for stakeholders to decide whether to go for a software upgrade or to replace it with another software. There is no unified approach or solution to consolidate data and relationships of Information Technology Assets, Software Upgrades, Software costs, Software defects, Software Performance Metrics, Security issues, IT system versions, service level objectives etc. Due to this, the decision making of software upgrades and software decommissioning is a tedious process and takes more time and effort. There is a need to build a solution that can integrate and validate the information like software assets, software upgrade success and failure likelihoods, cost benefit analysis of Cloud Computing, software metrics for fault prediction, software maintainability prediction results, Digital Transformation readiness and other related factors. There is an opportunity to apply Machine Learning techniques in defining and deriving the success likelihoods on the following data: Systems and data integration, software assets compatibility, operational service level agreement breaches, quality assurance metrics, security issues, number of open defects, number of defect fixes, number of priority incidents, mean time to resolve critical incidents, expected cost increase in software maintenance, potential cost reduction with the software or hardware replacement etc. This Research Proposal outlines the above mentioned to build a recommendation system aka decision tree namely Software Upgrades or Decommissions Life Cycle.

Challenges and Opportunities for the Development of Inland Waterway Transport in Brazil

Despite the presence of numerous navigable rivers in Brazil, they remain underutilized for Inland Waterway Transport (IWT). Given the recent changes in transport systems which aim to reduce reliance on highways due to their high cost and lack of sustainability, it becomes crucial to explore new transport models in Brazil, shifting part of the transport from roads to railways and mainly to waterways. To fill this gap in Brazil’s transport system, it was decided to check why waterways are little used and what challenges cause them to be underutilized and, additionally, what opportunities could leverage their use in the country. In this sense, in this study, we identify the biggest challenges and opportunities faced by IWT in Brazil. To achieve this objective, interviews were conducted using content analysis with managers who work in public and private IWT organizations active in Brazil. Results show that IWT has seen a recovery in interest in recent years due to the need for cheaper and greener logistics. It was also found that the main challenges that IWT faces are a lack of public policies followed by precarious infrastructure of waterways, ports and locks, as well as modest integration with other transport modes. Conversely, the most significant opportunity lies in the potential reduction in transport costs, coupled with the enhanced sustainability of transport activities via the utilization of IWT, thereby fostering greener transport practices. These results can contribute to a better understanding of practical and theoretical approaches related to IWT in Brazil, and they can serve as a reflection for new research focusing on the development of IWT especially in other emerging countries facing similar issues.

Cost of Low-Value Imaging Worldwide: A Systematic Review.

Imaging with low or no benefit for the patient undermines the quality of care and amounts to vast opportunity costs. More than 3.6 billion imaging examinations are performed annually, and about 20-50% of these are of low value. This study aimed to synthesize knowledge of the costs of low-value imaging worldwide. This systematic review was based on the PRISMA statement. The database search was developed in Medline and further adapted to Embase-Ovid, Cochrane Library, and Scopus. Primary empirical studies assessing the costs of low-value diagnostic imaging were included if published between 2012 and March 2022. Studies designed as randomized controlled trials, non-randomized trials, cohort studies, cross-sectional studies, descriptive studies, cost analysis, cost-effectiveness analysis, and mixed-methods studies were eligible. The analysis was descriptive. Of 5,567 records identified, 106 were included. Most of the studies included were conducted in the USA (n = 76), and a hospital or medical center was the most common setting (n = 82). Thirty-eight of the included studies calculated the costs of multiple imaging modalities; in studies with only one imaging modality included, conventional radiography was the most common (n = 32). Aggregated costs for low-value examinations amounts to billions of dollars per year globally. Initiatives to reduce low-value imaging may reduce costs by up to 95% without harming patients. This study is the first systematic review of the cost of low-value imaging worldwide, documenting a high potential for cost reduction. Given the universal challenges with resource allocation, the large amount used for low-value imaging represents a vast opportunity cost and offers great potential to improve the quality and efficiency of care.

Determining the Availability of Continuous Systems in Open Pits Using ANFIS and a Simulation Model

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits.

Evaluation of the Impact of Letrozole in Combination with the GnRH Antagonist Ovarian Stimulation Protocol in Patients Expected to Have a Poor Ovarian Response (POSEIDON Groups 3 and 4).

Background and Objectives: The objective of this study was to evaluate the impact of adjuvant letrozole administration during ovarian stimulation using the gonadotropin-releasing hormone (GnRH) antagonist protocol on treatment outcomes in women categorized into POSEIDON groups 3 and 4. Materials and Methods: This retrospective cohort study analyzed data from patients classified into POSEIDON groups 3 and 4 who underwent fresh embryo transfer subsequent to intracytoplasmic sperm injection following a GnRH antagonist stimulation protocol between January 2017 and December 2021. Patients were divided into two groups: the GnRH-LZ group, who received letrozole at a dosage of 5 mg/day for five consecutive days, and the GnRH-ant group, who did not receive adjuvant letrozole. The primary outcome measure of the study was a comparative analysis of live birth rates between the two groups. Results: A total of 449 patients were deemed suitable for final analysis and were allocated into two groups: 281 patients in the GnRH-ant group and 168 patients in the GnRH-LZ group. Live birth rates were found to be comparable in both groups (11% vs. 9%, p = 0.497). Letrozole administration significantly reduced the total amount of gonadotropins required (2606.2 ± 1284.5 vs. 3097.8 ± 1073.3, p < 0.001), the duration of ovarian stimulation (11.2 ± 3.9 vs. 10.2 ± 3, p = 0.005), and the serum peak estradiol concentration (901.4 ± 599.6 vs. 463.8 ± 312.3, p < 0.001). Conclusions: Adjuvant letrozole administration did not demonstrate a significant impact on live birth rates among women categorized into POSEIDON groups 3 and 4. However, this approach may offer potential cost reductions by diminishing the necessity for exogenous gonadotropins and shortening the duration of ovarian stimulation.

Diagnostics and characterization of a novel multi gas layer RF atmospheric pressure plasma jet for polymer processing

The quest to employ cold plasma sources at atmospheric pressure in polymer processing has emerged as a potent driving force behind their development. Atmospheric pressure operation of plasma jets provides potential cost reductions as well as easier handling and maintenance. In addition, their unique advantage of remote operation allows the substrate to be placed outside the source boundaries. This latter feature makes it easier to process complex three-dimensional objects and to integrate plasma jets into existing production lines. Although conventional atmospheric pressure plasma jet (APPJ) sources have undergone significant advancements in their design and construction, they have reached their technical and technological thresholds in several domains, thereby also impeding further enhancements in material processing applications. To cope with this issue, this work introduces a promising APPJ (named MPPJ3) working in a three co-axial gas layer geometry, incorporating the capability of aerosol and shield gas introduction leading to a configuration rich in reactive plasma species with controllable size and suitable temperature for polymer processing. A parametric study on the novel MPPJ3 device is carried out and plasma characteristics, such as reactive plasma species and temperatures, are determined by means of optical emission spectroscopy (OES), laser scattering, and infrared (IR) camera imaging whereas the fluid dynamics are analyzed using computational fluid dynamics (CFDs) and Schlieren imaging. The obtained promising results clearly show the flexibility and adaptability of the MPPJ3 device for polymer processing applications.

Optimal trade execution in cryptocurrency markets

Novel technologies allow cryptocurrency exchanges to offer innovative services that set them apart from other exchanges. In this paper we study the distinct features of cryptocurrency fee schedules and the implications for optimal trade execution. We formulate an optimal execution strategy that minimizes the trading fees charged by the exchange. We further provide a proof for the existence of an optimal execution strategy for this type of fee schedule. The optimal strategy involves both market and limit orders on various price levels. The optimal order distribution scheme depends on the market conditions expressed in terms of the distribution of limit order execution probabilities and the exchange’s specific configuration of the fee schedule. Our results indicate that a strategy kernel with an exponentially decaying allocation of trade volume to price levels further away from the best price provides superior performance and potential reduction of trade execution cost of more than 60%. The robustness of these results is confirmed in an empirical study. To our knowledge, this is the first study of optimal trade execution that takes into consideration the full fee schedule of exchanges in general.

Urban Electric Bus Fleet Transition Research Based on Eco-Impact Valuation Model and Discounted Cash Flow Analysis

This paper investigates the transition to an all-electric bus fleet as a strategy for sustainable urban development, focusing on its financial and environmental impacts. Utilizing the Eco-impact Valuation Model, Discounted Cash Flow Analysis (DCF), and the E-bus Replacement Model, the study assesses the feasibility and benefits of replacing conventional diesel buses with electric buses. Firstly, the Eco-impact Valuation Model analyzes and translates the environmental costs of diesel and electric buses into monetary social costs, evaluating the potential cost reduction to society offered by electric buses. Secondly, the DCF is used to demonstrate the potential cost-saving superiority of electric buses over diesel buses within a single investment period, providing a financial perspective on the transition. Lastly, the E-bus Replacement Model plans the phased introduction of electric buses and updates bus routes over the next ten years, based on air quality severity in different city zones. The severity of pollution is ranked using the TOPSIS evaluation model, with influencing factors weighted by the Analytic Hierarchy Process (AHP). The models are applied to three cities, including Houston, Buenos Aires, and Shenzhen, offering insights into the ecological, financial, and practical feasibility of electric buses for policymakers.

The role of robots in the service industry: Factors affecting human-robot interactions

Robot use in the service industry has been gaining momentum, not only for potential cost reduction reasons, but to allow establishments to improve their service quality. However, little work has been conducted on customers’ intention to dine at a restaurant based on the congruency of the robots and the establishments, the task complexity and the likeability of the robots. Three studies were conducted through an experimental design. We investigated the mediating role of anthropomorphism on customers’ intention to dine (Study 1), and the role of service establishment type (Study 2). We also considered task complexity to be delivered by robots (Study 3ab). We find that customers prefer human-delivered services but are willing to dine at a casual service establishment that uses robots. Furthermore, customers favor the use of robots as an opportunity for human employees to level up their job rather than as a substitute.

Identification and characterization of a potential strain for the production of polyhydroxyalkanoate from glycerol.

While poly (3-hydroxybutyrate) (PHB) holds promise as a bioplastic, its commercial utilization has been hampered by the high cost of raw materials. However, glycerol emerges as a viable feedstock for PHB production, offering a sustainable production approach and substantial cost reduction potential. Glycerol stands out as a promising feedstock for PHB production, offering a pathway toward sustainable manufacturing and considerable cost savings. The identification and characterization of strains capable of converting glycerol into PHB represent a pivotal strategy in advancing PHB production research. In this study, we isolated a strain, Ralstonia sp. RRA (RRA). The strain exhibits remarkable proficiency in synthesizing PHB from glycerol. With glycerol as the carbon source, RRA achieved a specific growth rate of 0.19 h-1, attaining a PHB content of approximately 50% within 30 h. Through third-generation genome and transcriptome sequencing, we elucidated the genome composition and identified a total of eight genes (glpR, glpD, glpS, glpT, glpP, glpQ, glpV, and glpK) involved in the glycerol metabolism pathway. Leveraging these findings, the strain RRA demonstrates significant promise in producing PHB from low-cost renewable carbon sources.

Influence of Anode Flow-Field Channel Distance on the Performance of Polymer Electrolyte Membrane Water Electrolyzers

Polymer electrolyte membrane water electrolysis (PEMWE) is well suited for flexible and efficient hydrogen production based on electricity from renewable energy sources [1]. Of all PEMWE stack components, flow-fields (FF) or bipolar plates (BP) are currently among the most expensive parts: In an analysis from 2020, FF/BP are reported to account for more than half of current PEMWE stack costs with medium potential for cost reduction towards the next-generation [2]. Another recent study attributes only 28% of current PEMWE stack costs to FF/BP, but claims that next-generation bipolar plates will be 3 times less expensive [3]. In any case, the optimization of flow-fields represents an important lever to improve the economic competitiveness of PEMWE. Although sophisticated designs are reported in the literature, commercial flow-fields tend to follow simpler approaches [4]. For classic design patterns like serpentine or parallel channels, studies compared different channel patterns or assessed the influence of the channel width [5]. Nevertheless, systematic investigations on the influence of the channel distance (FF land width) on the PEMWE performance have not been reported so far. Recently, an optimal FF land width of 4 times the thickness of the porous transport layer (PTL) was postulated [6]. However, it remains unclear if this ratio is universally valid, because only one specific FF configuration and only one PTL type (with variable PTL thickness) was investigated in the study.In this work, we analyze the influence of the anode side flow-field channel distance (land width) on the cell performance of 5 cm2 PEMWE single-cells. Different single-channel serpentine flow fields with land widths ranging from 0.7 mm to 6.2 mm and a constant channel width of 1 mm are characterized as a function of PTL type (powder-sintered- as well as fiber-based titanium PTL). For all FF/PTL combinations, polarization curves up to 6 A/cm2 are performed with electrochemical impedance spectroscopy (EIS) measurements at each current step. The anode proton sheet resistance is evaluated by EIS fitting during blocking conditions. On one side, a voltage loss analysis reveals that mass transfer losses in PEMWE cells are very small for the best suited FF/PTL combinations (<15 mV at 6 A/cm²). On the other side, for large land widths in combination with certain PTL types, severe mass transport losses are observed at high current densities (increased cell as well as iR-free cell voltage, cf. figure 1a), accompanied by a partial dry-out of the membrane that is reflected by an increased high-frequency resistance (HFR, cf. figure 1b). For this case, the remaining water content in the membrane will be estimated. Porosity and pore structure of the PTL used in this study are analyzed ex-situ through mercury intrusion porosimetry (MIP). The PTL samples cover a broad range of pore sizes (≈15-60 µm) and porosities (≈30-70 %). Further analysis will be conducted to elucidate the contribution of PTL bulk properties such as their in-plane permeability to the observed mass transport losses for large flow-field land widths.

Recovery of antioxidative protein hydrolysates with functional properties from fermented brewer's spent grain via microwave-assisted three phase partitioning

The protein shortage for the world's population in the near future has prompted scientists to develop novel methods for the sustainable production of dietary proteins from various alternative sources. In this study, the application of the bioseparation technique known as microwave-assisted three phase partitioning (MATPP) was explored to simultaneously extract and separate proteins from brewer's spent grain (BSG) after fungal fermentation. The results of the study indicated that MATPP (82.2%) recovered twice the amounts of proteins from fermented BSG compared to three phase partitioning (TPP) (41.8%). Besides, no significant differences (p > 0.05) were observed in terms of amino acid composition, protein pattern, and some functional properties between the fermented BSG proteins (FBPs) obtained via TPP and MATPP. Additionally, MATPP was found to increase the antioxidant activities of FBPs. These findings suggest that MATPP holds great potential for industrial-scale protein recovery attributed to its effectiveness, simplicity, and speed. Industrial relevanceMicrowave-assisted three phase partitioning (MATPP) is an emerging bioseparation technique that could simultaneously extract, separate, and partially purify proteins from protein-rich plant materials effectively within a relatively short timeframe. The fact that the microwave used does not significantly alter most of the physicochemical properties of the plant protein hydrolysates certainly supports the adoption of the technique in industry settings. MATPP demonstrates significant potential for industrial-scale utilization due to its efficiency, simplicity and potential cost reduction in production.

Прогнозирование переизлученного шума и вибрации, создаваемых вблизи железнодорожных линий

Purpose: To analyze a ScopeRail model capable of predicting re-radiated noise and vibration in structures located in close proximity to rail lines. To compare the obtained results with an alternative, widely used model for accuracy assessment and the potential cost reduction of assessing the impact of vibrations on residential areas for new railway lines. Methods: To perform statistical analysis of the obtained data for modeling vibration of different types of ground. To calculate simulation results in order to create a database of vibration characteristics for different ground conditions, train speeds and distances from the track. Results: The results obtained have been analyzed and compared with an alternative, widely used model for determining accuracy. It is found that the ScopeRail model yields higher prediction accuracy, which can potentially reduce the cost of assessing the impact of vibrations on residential areas for new rail lines. A model is obtained which can instantly predict the vibration and re-radiated noise levels for different types of soil at different speeds of passing trains. Practical significance: Re-radiated vibration and noise model for the spaces in buildings immediately adjacent to the railroad track has been developed using a set of empirically obtained factors. Vibration and noise impacts have also been modeled using additional vibroacoustic mitigation measures (slabs and ballast mats) as well as vibration excitation parameters (switches, crossings and wheel stoppers).

Energy, Exergy, Economic and Exergoeconomic Analyses of Chemical Looping Combustion Plant Using Waste Bark for District Heat and Power Generation with Negative Emissions

The greenhouse gas emissions from the boiler of pulp and paper industries can be minimized by adapting chemical looping combustion (CLC) technology. This work aims to analyze the energy, exergy, economic, and exergoeconomic performance of an industrial scale CLC plant for district heat and electricity generation using waste bark from the paper and pulp industry. The CLC plant with one natural ore and one industrial waste oxygen carrier (OC) is modeled using Aspen Plus. The performance of the CLC plant has been compared to Örtofta combined heat and power plant without CO2 capture and with post‐combustion CO2 capture as the reference cases. Results showed that the CLC‐based power plant is energetically, exegetically, and economically efficient compared to the reference cases. The circulating fluidized bed boiler unit contributes the highest exergy destruction (about 50–80%). Among the CO2 capture plants, the CLC plant with ilmenite has the lowest levelized cost of district heat (4.58 € GJ−1), and a payback period (9.69 years) followed by the CLC plant with LD slag (5.91 € GJ−1 and 11.84 years), and the plant with PCC (6.94 € GJ−1 and 13.58 years). The exergoeconomic analysis reveals that the CLC reactors have the highest cost reduction potential, followed by the steam turbine.