Academic literature on the topic 'Eco-efficient control strategies'

PurposeThe purpose of this study is to predict the antecedents of consumers' purchase intention of energy-efficient home appliances. This study incorporated two additional constructs (knowledge of eco-labels and knowledge of eco-labels) in the model of the theory of planned behavior. Consumers' enhanced trust for energy-efficient products is crucial to purchase intention. The second construct is consumers' knowledge of eco-labels. Knowledge of eco-labels would help to assess consumers' tendency toward environmental problems and intention to purchase energy-efficient home appliances.Design/methodology/approachThis study used a quantitative approach using a survey (questionnaire) method to collect data of respondents. Non-probability quota based on age and convenience sampling techniques were employed to select the participants of this study.FindingsThe findings of the study revealed that consumer knowledge of eco-labels, green trust, subjective norm, attitude and perceived behavioral control have positive influence on purchase intention of energy-efficient home appliances.Originality/valueEco-labels are served as a marketing tool to distinguish producer's products from others. Prior studies have only focused on consumers' general knowledge. This study helps marketers to understand and design strategies to generate more value for green consumers. This study also contributes to the literature on green marketing by employing the theory of planned behavior.

In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model.

The development of more sustainable urban transportation is prompting the need for better energy management techniques. Connected electric vehicles can take advantage of environmental information regarding the status of traffic lights. In this context, eco-approach and departure methods have been proposed in the literature. Integrating these methods with regenerative braking allows for safe, power-efficient navigation through intersections and crossroad layouts. This paper proposes rule- and fuzzy inference system-based strategies for a coupled eco-approach and departure regenerative braking system. This analysis is carried out through a numerical simulator based on a three-degree-of-freedom connected electric vehicle model. The powertrain is represented by a realistic power loss map in motoring and regenerative quadrants. The simulations aim to compare both longitudinal navigation strategies by means of relevant metrics: power, efficiency, comfort, and usage duty cycle in motor and generator modes. Numerical results show that the vehicle is able to yield safe navigation while focusing on energy regeneration through different navigation conditions.

Calculating the environmental benefits of energy saving systems in dwellings in a life cycle assessment (LCA) has two major issues, namely: how to deal with the customer behaviour and how to deal with rebound effects. Both issues are important for sustainable strategies. From a user-centred design perspective, two fundamentally different strategies are observed, namely: a ‘passive’ end-user, who invests in insulating the building and maintaining their preferred behaviour routines, versus an ‘active’ end-user; who must change his or her behaviour in order to save energy. A combined analysis of cost, (market) value, and eco-burden is used to compare and evaluate the two strategies; by applying the methods of eco-costs/value ratio (EVR) and eco-efficient value creation. Simulation software is applied to calculate the results for the active end-user approach (by means of home energy management systems [HEMS]). The energy savings for a passive user approach (applying thermal insulation) are calculated with straightforward heat loss calculations. The rebound effect of energy savings is taken into consideration. From the environmental point of view, the optimal insulation thickness is calculated, by comparing the energy savings with the environmental burden of the insulation materials. This analysis shows that HEMS are effective for poorly insulated houses, but not for well insulated houses. Governmental policies that focus only on insulation, however, lack the urgency of greenhouse gas reduction; the HEMS for existing houses is an indispensable tool for a fast transition to less domestic energy consumption.

Objectives: To validate the ecological modification of the Papanicolaou stain (Eco-Pap) for the diagnosis of cervical cancer. Study Design: A prospective study was performed at the Mother and Child “San Bartolomé” Hospital, Lima, Peru. Reagent handling strategies were divided into three phases: we used (1) Harris progressive hematoxylin (for nuclear staining), (2) a polychromatic solution (a mix of EA-36/Orange G-6 to suppress the use of several alcohol baths), and (3) direct mounting (with Entellan® solution). The cellular details were analyzed by the staining quality index, an external quality control, and the Bethesda System 2014. Results: We evaluated 72,901 cervical smears stained with the Eco-Pap. The validation of the Eco-Pap against the conventional Pap stain was optimal (κ = 0.89; 95% CI: 0.87–0.92), showing a sensibility and specificity of 88.3% (95% CI: 85.1–90.0) and 98.7% (95% CI: 98–99.2), respectively. The Eco-Pap dramatically reduced the environmental pollution caused by 72 L of xylene, hydrochloric acid, and ammonia (6 L each) and mercury oxide. Conclusion: The Eco-Pap is an innovative and efficient staining method reducing the use of toxic reagents with carcinogenic potential during cervical cancer screening by exfoliative cytology.

Late blight of potato caused by fungus Phytophthora infestans responsible for Irish famine in the year 1845, is one of the most dramatic episode caused by plant pathogen in human history. One million people died due to famine in Ireland. So eco-friendly management of potato late blight disease is a necessary goal to be accomplished.During last many years, management strategies solely relied upon the application of fungicides due to rapid development of late blight epidemics. However, indiscriminate use of fungicide posesses a serious threat to the environment and human health. It is also responsible for built up of resistance in the pathogen and have adverse effect on beneficial organisms such as nitrogen fixers, resident antagonism and mycorrhizal fungi. So to minimize the fungicide use, eco-friendly means for late blight management are required on a priority basis. In recent years, significant changes in isolates of late blight fungus have been recorded including changes in aggressiveness to the crop also. Since, late blight is a community disease so, effective eco-friendly management must be adopted by the all producers, farmers, gardeners and growers with the help of government agencies, extension specialist and crop consultants etc. The strategy to control late blight is the prevention of establishment of Phytophthorainfestans in potato crop. In this context, disease management by cultural practices is the first line of defense while forecasting system, physiological strategies, biological control, host plant resistance and bio-technological approach are essential for efficient, effective and eco-friendly management of late blight of potato.

This systematic review explores the intricate relationship between environmental sustainability and infection control in healthcare. A comprehensive examination of twelve selected studies reveals key themes, including the pivotal role of leadership in motivating sustainable practices within healthcare facilities and the integration of sustainable design strategies for effective infection prevention and control. The review emphasizes the significance of strong leadership in driving a culture of environmental responsibility, fostering staff engagement, and ensuring the success of sustainability initiatives. Sustainable design strategies, such as energy-efficient building practices and eco-friendly materials, emerge as essential components of both environmental sustainability and infection control. By creating synergy between these objectives, healthcare facilities can simultaneously reduce their environmental footprint and enhance patient safety. This study underscores the importance of leadership commitment and sustainable design in shaping the future of healthcare toward a more environmentally responsible and infection-resistant paradigm.

Peach leaf curl disease (PLCuD) is a devastating fungal disease that poses a significant threat to peach production globally, and its impact is also evident in Pakistan's fruit industry. The disease is caused by phyto-parasitic fungi from the Taphrinaceae family, primarily the genus Taphrina. Chemical fungicides are the most common method for controlling the disease; however, their use presents health and environmental concerns and can lead to resistance over time. As a result, alternative control strategies that are both cost-effective and environmentally friendly are essential. Unfortunately, there is a significant gap in knowledge about PLCuD in Pakistan, and the actual cause of the disease remains unidentified, making management impossible. Therefore, discovering novel biological control methods is crucial to combat this disease effectively. Recent advances in biotechnology have shown promising results in developing biological control agents, such as microbial inoculants, bio-fungicides, and bio-pesticides. These agents can specifically target the fungi responsible for the disease, leading to more efficient and sustainable control measures. The review highlights the urgent need to develop sustainable and effective biological control methods to combat PLCuD in Pakistan and to provide innovative and eco-friendly solutions for managing this devastating disease and ensuring the long-term sustainability of the peach industry in Pakistan.

Buoyancy control is a fundamental aspect of aquatic life that has major implications for locomotor performance and ecological niche. Unlike terrestrial animals, the densities of aquatic animals are similar to the supporting fluid, thus even small changes in body density may have profound effects on locomotion. Here, we analysed the body composition (lipid versus lean tissue) of 32 shark species to study the evolution of buoyancy. Our comparative phylogenetic analyses indicate that although lean tissue displays minor positive allometry, liver volume exhibits pronounced positive allometry, suggesting that larger sharks evolved bulkier body compositions by adding lipid tissue to lean tissue rather than substituting lean for lipid tissue, particularly in the liver. We revealed a continuum of buoyancy control strategies that ranged from more buoyant sharks with larger livers in deeper ecosystems to relatively denser sharks with small livers in epipelagic habitats. Across this eco-morphological spectrum, our hydrodynamic modelling suggests that neutral buoyancy yields lower drag and more efficient steady swimming, whereas negative buoyancy may be more efficient during accelerated movements. The evolution of buoyancy control in sharks suggests that ecological and physiological factors mediate the selective pressures acting on these traits along two major gradients, body size and habitat depth.

Sustainable product design uses methodologies focused on eco-effectiveness and eco-efficiency for the proposal of innovative technological solutions and for the control of environmental impacts during the product life cycle. One of the main drawbacks of such techniques is their qualitative nature, associated with a decision-making process that is sometimes arbitrary, or with unverifiable data; this means that several complementary tools are currently being used to reduce the error in the results obtained. This situation makes the unification of procedures necessary. In this context, this research develops a methodology for the sustainable design of industrial products that integrates life cycle assessment (in its environmental, economic and social application) and cradle-to-cradle techniques. For this purpose, a new assessment process is proposed, based on damage, developing LCA+C2C endpoint indicators. The methodology is subsequently verified in a case study of products for sustainable mobility (city trike electric). The results show that an integrated LCA+C2C assessment can help to propose more balanced sustainable strategies and would be a suitable method to measure tradeoffs between economic, social and environmental results, for practical purposes and future redesigns. The unified method provides a procedure to design a solution with a trade-off between eco-efficient and eco-effective criteria; it also simplifies the design phases, facilitates the interpretation of the results and provides a quantitative scope to the cradle-to-cradle framework.

L’émergence de pathogènes végétaux s’accélère dans le monde entier, menaçant la sécurité alimentaire. Il est urgent de concevoir des outils innovants de protection des plantes, en associant des stratégies de surveillance à des stratégies de lutte précoce contre les maladies, afin de garantir la sécurité alimentaire tout en assurant la viabilité environnementale des pratiques agricoles. Dans ce contexte, les pathogènes aériens représentent un enjeu majeur, car ils peuvent se propager sur de longues distances. Dans cette thèse, je propose un cadre de modélisation pour concevoir des stratégies basées sur les réseaux complexes pour la surveillance et le contrôle des pathogènes des plantes se déplaçant dans les masses d’air. Je prends comme sujets d’étude le pathogène fongique Puccinia graminis, agent causal de la rouille noire du blé, et Monilinia fructicola, agent causal de la pourriture brune des pêches. Tout d’abord, je présente la modélisation des interactions entre hôte et pathogène sous forme de réseaux complexes et je retrace la manière dont les scientifiques ont utilisé les propriétés des réseaux pour élaborer des stratégies de protection contre les maladies. Ensuite, jereconstruis le réseau épidémique mondial de la rouille noire du blé, où les régions productrices de blé sont reliées par des connexions potentielles de transport de pathogènes. J’estime ces connexions à l’aide d’un modèle aérobiologique basé sur des simulations de trajectoires Lagrangiennes. Je montre comment un algorithme basé sur les réseaux complexes peut aider à identifier les meilleures sentinelles, c’est-à-dire les endroits où une épidémie peut être détectée rapidement. Troisièmement, j’intègre le modèle aérobiologique dans un cadre épidémiologique métapopulationnel afin de simuler la propagation spatiale d’une épidémie de maladie des plantes. En particulier, je couple un modèle dépendant du climat décrivant la susceptibilité de l’hôte et son épidémiologie à l’intérieur des vergers avec des simulations de trajectoires Lagrangiennes déterminant les transports des pathogènes entre les vergers. J’utilise la pourriture brune des pêches en France comme cas d’étude, pour lequel je produis des cartes de risque épidémiologique afin de faciliter le développement des stratégies de protection. Enfin, j’évalue la perte globale d’efficacité de la surveillance due au manque de communication et coordination entre les pays dans le cas des maladies transfrontalières. J’utilise le réseau épidémique mondial de la rouille du blé comme cas d’étude. J’évalue les efforts de surveillance (c’est-à-dire le nombre de sentinelles) déployés par chaque pays pour atteindre un objectif de surveillance donné dans un scénario de coopération (c’est-à-dire sans tenir compte des frontières) puis dans un scénario où chaque pays est indépendant. Compte tenu de la forte densité du réseau épidémique mondial de Puccinia, il est possible de trouver un ensemble restreint de sentinelles (1% du réseau) qui surveillent indirectement la moitié des régions productrices de blé (50% du réseau). Je démontre que la connectivité basée sur les masses d’aire aide la reconstruction des observations de l’incidence de la pourriture brune en France, et identifie les endroits les plus à risque dans la vallée du Rhône. Les avantages d’une stratégie coopérative, qui interprète correctement l’échelle de dispersion de la maladie, sont évidents pour les maladies transfrontalières, mais sont répartis de manière hétérogène entre les pays : des mécanismes de compensation devraient être mis en œuvre pour obtenir un soutien unanime en faveur d’un système de surveillance coopératif international<br>Rates of emergence of pathogens accelerates worldwide, threatening food security. Designing innovative crop protection tools, coupling surveillance strategies with timing control of diseases, is a main issue to ensure food security while restoring environmental viability offarming practices. In this context, airborne pathogens represent a challenging case study, as they may be spread over long distances.In this thesis I propose a modelling framework to support network-based surveillance and control strategies for airborne plant pathogens. I consider the fungal pathogen Puccinia graminis, causal agent of stem rust of wheat, and Monilinia fructicola, causal agent of brown rot of peaches, as case studies. First, I introduce the representation of host-pathogens interactions in networks, and I investigate how scientists have used network properties to elaborate disease protection strategies. Secondly, I reconstruct the global epidemic network for stem rust of wheat, where worldwide wheat-producing regions are connected via potential pathogen transport events. I compute such connections using an aerobiological model based on Lagrangian trajectory simulations. I show how a network-based algorithm may help identifying thebest sentinels, i.e. those locations, to be frequently monitored, where an outbreak may be early detected. Thirdly, I integrate the aerobiological model within an epidemiologicalmetapopulation framework to simulate the spatial spread of a plant disease outbreak. In particular, I couple a climate-dependant model describing host susceptibility and in-orchard epidemiology with Lagrangian trajectory simulations determining transport of pathogens between orchards. I use brown rot of peach crops in France as a case study, for which I produce maps of epidemiological risk to inform protection strategies. Finally, I assess the global loss of surveillance efficiency due to lack of communication and cooperation among countries in designing surveillance strategies for transboundary diseases. I use the global epidemic network for stem rust of wheat as a case study. I assess the surveillance efforts (i.e. the number of sentinels) deployed by each country to reach a given monitoring target in a cooperative scenario (i.e. regardless of country border) or each country alone. Given the high density of the worldwide Puccinia epidemic network, it is possible to find a narrow set of sentinels (1% of the network) which indirectly monitor half of the wheatproducing regions (50% of the network). I show that wind-driven connectivity helps reconstructing observations of brown rot incidence in France, and help identifying the most risky locations in the Rhône Valley. Benefits of a cooperative strategy, which correctly interpret the dispersal scale of a disease, are evident for transboundary diseases, but are heterogeneously distributed among countries: compensation mechanisms should be implemented to gain unanimous support for an international cooperative surveillance system

Environmental regulations demand efficient and eco-friendly ways of power generation. Coal continues to play a vital role in power generation because of its availability in abundance. Power generation using coal leads to local pollution problems. Hence this conflicting situation demands a new technology - Integrated Gasification Combined Cycle (IGCC). Gasifier is one of the subsystems in IGCC. It is a multivariable system with four inputs and four outputs with higher degree of cross coupling between the input and output variables. ALSTOM – a multinational and Original Equipment Manufacturer (OEM) - developed a detailed nonlinear mathematical model, validated made this model available to the academic community and demanded different control strategies which will satisfy certain stringent performance criteria during specified disturbances. These demands of ALSTOM are well known as “ALSTOM Benchmark Challenges”. The chapter is addressed to solve Alstom Benchmark Challenges using Proportional-Integral-Derivative-Filter (PIDF) controllers optimised by Genetic Algorithm.

Environmental regulations demand efficient and eco-friendly ways of power generation. Coal continues to play a vital role in power generation because of its availability in abundance. Power generation using coal leads to local pollution problems. Hence this conflicting situation demands a new technology - Integrated Gasification Combined Cycle (IGCC). Gasifier is one of the subsystems in IGCC. It is a multivariable system with four inputs and four outputs with higher degree of cross coupling between the input and output variables. ALSTOM – a multinational and Original Equipment Manufacturer (OEM) - developed a detailed nonlinear mathematical model, validated made this model available to the academic community and demanded different control strategies which will satisfy certain stringent performance criteria during specified disturbances. These demands of ALSTOM are well known as “ALSTOM Benchmark Challenges”. The chapter is addressed to solve Alstom Benchmark Challenges using Proportional-Integral-Derivative-Filter (PIDF) controllers optimised by Genetic Algorithm.

Buildings consume nearly one-third of global energy and are responsible for one-fourth of CO2 emissions, thereby playing a crucial role in polluting the earth. Cities are more vulnerable as there are more buildings and a huge population due to employment opportunities. Hence, there is a need for the transformation of cities into smart cities with viable environments by making buildings smart. Smart cities with energy-efficient buildings can improve the economy and reduce pollution effects, thereby improving the quality of city life. As human errors and carelessness jeopardise energy conservation and eco-friendly initiatives in traditional buildings, automatic internet of things (IOT) monitored building control, also known as a smart building, is a need of the hour if the world is to advance toward smart cities. The management of the cities should estimate their energy consumption in advance and plan strategies that will help in reducing the energy consumption of both commercial and residential buildings towards creating a pollution-free smart city. The IOT sensors produce continuous streaming data, which necessitates big data analysis to improve the performance of building in terms of energy consumption. Big data analysis based on machine learning techniques is currently being employed for such an automatic analysis and management of buildings based on IOT sensor data. This chapter focuses on bringing out the commercially available IOT sensors for collecting building data, their efficiencies, extracted features and the commonly used machine learning techniques, their strengths, and drawbacks and also identifies the research gap and work to be done for further improving big data analysis of smart energy management.

Nowadays in many industrial applications, i.e. electrical household appliances, it is necessary to have a robust and safe control for some variables involved in the analysis of the performances of different products. In addition, the recent eco-design directives require products increasingly eco-friendly and eco-efficient, preserving high-performance but a low power consumption. For these reasons, the physical prototypes of products require many expensive and complex tests in term of time, resources and qualified personnel involved. To overcome these limitations, the proposed approach is focused on the use of virtual prototyping tools, which support and reduce the expensive physical experiments. The main objective of this paper is the development, implementation and testing of an innovative methodology, which could be an improvement for the sustainable design of induction hobs. Induction heating applied to the domestic cooking has significantly evolved since the first cooking hobs appeared. Different issues such as maximum power available for heating a pot, dimensional compactness of the hobs, or inverter electronics efficiency have achieved a great development. The proposed methodology provides the development of a multi-physic model which is able to estimate the efficiency of the induction hobs starting from the design data of the project. In particular, the multi-physic model is composed by an electromagnetic simulation and a thermal simulation. The electromagnetic simulation, starting from electrical values such as voltage, current and frequency, is able to simulate the eddy current induced in the bottom of the pot, and resistance leads to the Joulean heating of the material. The thermal simulation is able to measure the energy consumption during the operational phase and the temperature reached by the materials. Therefore, the thermal power obtained by the Joulean heating is, at the same time, the output of the electromagnetic simulation and the input of the thermal one. The proposed model can be applied to design product and simulate the performance considering different operating conditions such as different types of cookers, different coils and different materials. Through the use of virtual prototyping tools is possible to control the heat flux on the whole system (stove, pot, water), and to evaluate the energy efficiency during the operational phase. The proposed tool makes the product-engineer more aware about decision-making strategies in order to achieve an energy saving, calculated over the whole life cycle.

An observable trend nowadays is the change in the prime movers of mobile heavy machinery to electric alternatives to achieve more eco-friendly equipment. These solutions often require large and heavy batteries with limited capacity, making the research of more efficient components and the development of different system architectures an important topic of study. Hydraulic actuation is still a relevant application for these vehicles because of its reliability, controllability, and high power density. The electrification and digitalization of mobile machinery allow for innovative designs and control strategies to be implemented that take advantage of electro-hydraulic systems and their characteristics. Similar research has shown that a higher number of degrees of freedom allow for the system to operate with higher total efficiency. This paper introduces a novel actuation architecture that combines multiple fixed displacement hydraulic pumps and on/off directional valves to control the position and force of two hydraulic actuators for the working functions of a mobile machine. Each pump is powered by a variable speed electric drive so that each one can be operated independently, and together with the set of directional valves, allows the selection of different combinations of pumps and flow sharing between the actuators’ chambers to achieve the desired flow and pressure on each cylinder. The multi-pump system favours the use of smaller pumps, and the possibility of combining their flows reduces the need to operate the components at lower efficiency points such as partial displacement. At the same time, controlling the pumps’ flow through the variable-speed electric motors means that throttling valves are not needed. The development of this architecture will allow for its use in mathematical models to analyse its behaviour and efficiency and to obtain insights regarding points of improvement in the system architecture.

Abstract Due to the effect of global warming, navigation on the Northern Sea Route (NSR) has become a more economical and reliable choice for international cargo transportation. In some ways, global warming has increased the opportunity of shipping activities in the Arctic region and hence the need for ice-capable vessels. NSR shipping provides benefits for international trade, but challenges still exist. Although conventional direct drive propulsion system connected to 2 stroke marine engine is normally considered the most efficient approach for long-range transport, for icebreaking operation which requires prime movers to work at partial load, conventional mechanical propulsion systems generally have poor fuel efficiency and high emissions. Moreover, the harmful gases produced by ships trading in NSR have a significant impact on the Arctic climate. Moreover, a traditional mechanical drive icebreaker with a diesel engine is required to operate at high torque, low rpm during icebreaking operation. Thus conventional diesel engine that isn’t optimised to operate at this point would be inefficient and would produce black carbon due to incomplete combustion, which has the potential to cause ice, snow, and cloud albedo out of proportion with normal pattern, thus lead to serious impacts on the Arctic environment and eco-system. Arctic ship propulsion systems have been developing since the 19th century, with modifications such as the use of diesel electric propulsion systems and nuclear power propulsion systems which can ideally meet the requirements of ice breaking operation (low speed and high torque), however, drawbacks still exist in these systems, such as poor fuel efficiency at low speeds for diesel electric propulsion and for nuclear power, there are limitations such as high initial cost, management of nuclear waste and the fact that the required deep knowledge of nuclear technology is mastered by few countries. Hybrid propulsion is a new technology for ice-capable ships, which can address the partial loading efficiency problem in diesel-electric propulsion by charging and discharging a battery energy storage unit which can allow the ship to work in zero-emission mode in some sensitive areas. In this paper, detailed modelling, primary control strategies (voltage and frequency stability) and efficiency analysis of system components such as the motor, generator, battery and conversion devices etc. are and implemented in software, and then the whole power system is simulated with a secondary control strategy (load power sharing and battery aging concern) in both ice and open water load conditions. The results from the diesel electric system and hybrid system total fuel consumption within a target journey are compared to investigate the advantage of the hybrid system, which show up to a 40% fuel consumption reduction for hybrid propulsion arrangement. A tertiary control strategy for energy management is analysed and implemented in the system to further reduce system fuel consumption.