Energy Savings Research Articles

A Comparative Study of CPU and GPU Power Consumption while using Open-Source and Proprietary Media Players

This study presents a comparative analysis of power consumption between open-source and proprietary media players when playing open-media format videos (.webm). As media consumption grows, energy-efficient software is critical for both environmental sustainability and device performance. Using tools like HWiNFO, key metrics such as GPU and CPU power consumption, memory usage, and efficiency were evaluated for popular open-source (e.g., VLC, Kodi) and proprietary (e.g., GOM Player, KMPlayer) players. The results reveal that open-source players generally consume less GPU power but more CPU resources, while proprietary players balance CPU and GPU usage with higher memory demands. The findings suggest that careful selection of media players can lead to significant energy savings over time, offering insights for developers and users focused on energy-efficient computing.

Web Server Based Electrical Control System Analysis for Smart Buildings

Energy management in smart buildings still faces challenges in optimizing energy use, particularly for high-load devices, such as HVAC systems and lighting. Conventional control systems are often inadequate for optimizing energy usage based on the operational needs of the building. This study aims to develop and analyze a web server-based electrical energy control system that can be accessed in real time to improve the energy efficiency of smart buildings. This study employed a quasi-experimental method by implementing a web server-based control system in a smart building and comparing the energy consumption before and after the application of the system. The results show that the system reduces the energy consumption by up to 25%, particularly for HVAC systems and lighting. The most significant energy savings occurred during off-peak hours, when the system automatically reduced power for unnecessary devices. The implications of this research suggest that a web server-based control system not only enhances energy efficiency and reduces operational costs, but also provides greater flexibility in energy management through more adaptive and responsive remote control. This research contributes to the development of more sustainable energy management technologies for smart buildings, with wide potential applications in commercial and institutional building scenarios

Artificial Neural Network to Predict Curvature Light Shelf Design Related Daylighting Optimization on Office Spaces

Energy Optimization in building design field now has been revolutionized due to AI and machine learning applications. Leveraging daylight to reduce artificial lighting consumption holds promise for significant energy savings, yet the nonlinear nature of daylight patterns poses challenges in prediction and optimization. This study proposes a novel approach to automated light shelf design using machine learning algorithms, specifically artificial neural networks (ANNs) such as recurrent neural networks (RNN) by long short term memory (LSTM), to accelerate daylighting simulation and optimization processes. The methodology employed two distinct approaches: Firstly, we employed the theoretical-analytical approach to explore methods for utilizing machine learning in natural lighting and light shelf parameters. Second, the practical and applied method involved creating a predictive model for designing the light shelf using appropriate AI and ML techniques. This model is based on an office geometry model at the El Arish weather file in Egypt, four-dimensional training room models with three internal zones-oriented south. Rhinoceros and Grasshopper, two parametric simulation tools, are used to normalize and optimize light shelf parameters like geometry cross-section, curvature surface, width, height position, depth, tilt angle, and reflectance materials. Then, the Galapagos plug-in and Colibri2 are used for dataset creation and optimization. The results demonstrate that automated light shelf operation has a significant impact on internal daylighting quality. RNNs enable rapid prediction of optimization models, reducing time consumption in the early design phase. ML facilitates decision-making by generating evaluative criteria from user-selected design options. RNNs were classified as good and bad and used LSTM to enhance prediction accuracy for efficient illuminance values metric in zones 1 and 2. Challenges include increasing the simulation procedure's efficiency. The results of model accuracy reached 99%. Hence, future research should prioritize resolving the previously identified concerns. In conclusion, this study underscores the importance of ML-driven approaches in early design phases to optimize building energy consumption and pave the way for sustainable architectural practices.

Evaluating passive PCM performance in building envelopes for semi-arid climate: Experimental and numerical insights on hysteresis, sub-cooling, and energy savings

This study evaluates the performance of macro-encapsulated Phase Change Materials (PCMs) integrated into building envelopes for semi-arid climates, focusing on typical Moroccan construction using hollow concrete blocks. The primary objective is to assess the discrepancies between experimental and numerical analyses, particularly in hysteresis, sub-cooling, and energy savings. Given the widespread reliance on numerical tools like EnergyPlus for PCM simulations, the accuracy of manufacturer-provided latent heat values is investigated. The methodology involves constructing two identical test buildings, one equipped with PCM panels and another as a reference. Experimental data were collected in June 2023, assessing temperature fluctuations and energy savings. Differential Scanning Calorimetry (DSC) tests at varying scanning rates were conducted to analyze PCM behavior, including hysteresis and sub-cooling effects. Numerical simulations were then performed to compare energy performance. Besides, the results reveal that sub-cooling significantly limits PCM efficiency, with only 43 % of the PCM's latent heat capacity utilized. At the same time, hysteresis was found to be negligible in the field test. Cooling energy consumption was reduced by 20 %, with a corresponding 2.3 °C reduction in temperature fluctuations. However, the PCM's latent heat potential is underutilized due to sub-cooling. This research underscores the need for conducting DSC measurements at specific scanning rates to reflect regional climate conditions and suggests that simulation models should adjust latent heat utilization of the PCM. The study advocates for the use of composite PCMs, which could mitigate sub-cooling and enhance overall performance. These findings contribute to improving PCM integration in passive building designs, offering practical recommendations for better energy efficiency in semi-arid climates.

A multi-objective indirect neural adaptive processes control design for minimization of energy consumption: An experimental validation on a transesterification reactor

Nowadays, energy management environment is a very important issue that technologies have focused on in order to save costs and minimize energy waste. This objective can be achieved by means of an energy resource management approach through an appropriate optimization technique. However, energy savings can conflict with other objective functions, to solve the problem a multi-objective optimization that considers the minimization of the control energy can be adopted. In this paper, we propose to use a multi-objective indirect neural adaptive control concept for nonlinear systems with unknown dynamics. The control scheme consists of an adaptive instantaneous neural emulator and neural controller built on fully connected real-time recurrent learning networks (RTRL). The multi-objective particle swarm optimization (MOPSO) algorithm is used as a mechanism to find NE and NC adaptive learning rates that optimize the proposed objective functions: control energy minimization and closed-loop preservation. Comparative studies and experimental validation on a semi-batch reactor, used to generate cleaner biofuels, are performed to confirm the effectiveness of the proposed strategy.

The Regulation of Temperature Fluctuations and Energy Consumption in Buildings Using Phase Change Material–Gypsum Boards in Summer

This study examined the thermal performance of Comfortboard23, a commercial gypsum board from Knauf infused with phase change material (PCM). Structural characterization using XRD and SEM confirmed the presence of microencapsulated PCM within the gypsum matrix. The study does not provide a direct comparison between Comfortboard23 and other PCM-integrated gypsum boards on the market. This is a limitation of the research. A comprehensive comparison would involve testing multiple products under identical conditions, and evaluating factors such as thermal performance, cost-effectiveness, durability, and ease of installation. Thermal characterization involved a novel low-scale thermal chamber to measure U-value, thermal conductivity, heat storage capacity, and dynamic thermal response. Results showed incorporating PCM decreased the U-value by 2% compared to standard gypsum boards. Additionally, PCM inclusion increased heat storage capacity by around 45% and improved dynamic thermal characteristics by decreasing thermal stability coefficient from 0.92 to 0.76 and increasing thermal lag from 0.27 to 0.49 h. The 45% increase in heat storage capacity of Comfortboard23 could lead to a 10–20% reduction in heating and cooling energy consumption, improved thermal comfort, and potential HVAC downsizing. Exact benefits depend on climate, building design, and occupancy patterns, necessitating further research in diverse real-world settings. The findings demonstrate Comfortboard23’s potential for enhancing thermal energy storage in buildings, contributing to energy savings, improved thermal comfort, and reduced temperature fluctuations across varying daily temperatures. Overall, the study highlights the promise of Comfortboard23 as an energy-efficient PCM-integrated building material.

Innovative passive techniques and PCM integration in building envelopes for enhanced energy efficiency in desert regions

Rising energy demands in buildings for heating, cooling and operating appliances underscore the importance of implementing energy-efficient solutions. Passive cooling techniques provide a sustainable alternative to conventional, energy-intensive cooling systems, promising reduced energy consumption in buildings. Using a dynamic heat transfer model validated with ANSYS Fluent, this study examined three configurations: integrating phase change materials at the brick's centerline with cavities filled with air, EPS insulation, and emissivity coating. Additionally, the benefits of combining all three passive methods were evaluated. Results indicated that among the evaluated PCMs, capric acid demonstrated superior performance. While each passive method studied offers distinct advantages in enhancing thermal performance and achieving energy efficiency, assessing their combined effects revealed significant insights. Specifically, integrating capric acid at the brick's centerline, while simultaneously configuring EPS insulation in the upper cavities and emissivity coating in the lower cavities, yielded superior performance. This configuration significantly reduced inner surface temperature by approximately 6.6 °C and minimized heat flux by about 58.4 % compared to traditional bricks. Achieving energy savings of 56.24 %, this configuration shows potential to enhance both thermal comfort and energy efficiency in building applications.

Enhancing shipboard waste heat management with advanced technologies

The complexity of the energy systems onboard ships, combined with the different operating/weather conditions and the availability of cutting-edge technologies, makes analyses for improving the energy and environmental performances of ships time consuming and challenging. From this point of view, this article provides new criteria for the sustainable design and management of energy systems of existing or new ships. In particular, the impact of the adoption of organic Rankine cycle units, wet steam volumetric expanders, and single or double effect absorption chillers is here investigated. Two types of ships are examined as suitable case studies, evaluating the impact of each technology and their combinations by varying the shipping cruises. By using a dynamic simulation approach, potential savings and optimal solutions are assessed for different energy system layouts by also comparing their economic, energy and environmental impact performance. Results are reported in specific performance matrices for helping stakeholders in preliminary energy efficiency analyses.In particular, outcomes show that high cooling demands of ships in the Caribbean Sea enable primary energy savings close to 4.5 %, compared to 3.5 % in the Mediterranean Sea and 3 % in the North Sea. In the latter case, cooling needs can be almost fully balanced through the examined energy recovery technologies. Screw expanders integrate best in all operating conditions with short paybacks, whilst organic Rankine cycles (with electrical efficiency above 8%) are advantageous especially in cold climate routes. Benefits on environmental impact are significant, with avoided CO2 emissions around 6 kt/y, depending on the selected ship cruise.

Exploratory Analysis of a Novel Modular Green Wall’s Impact on Indoor Temperature and Energy Consumption in Residential Buildings: A Case Study from Belgium

One possible solution that mitigates the effects of climate change is the implementation of vertical greenery systems, which have the potential to reduce the need for cooling and provide energy savings for heating. This paper evaluates the effects of an innovative modular green wall on indoor temperature and energy use in a residential case study building. This research was carried out on a residential house in the city of Ghent, Belgium, whose southwest facade is covered with a specific type of modular green wall (a structure with a specific substrate and plants that have the ability to purify water so that it can be reused in the house). The monitoring process included four different temperatures (in front of and behind the green wall, in the substrate, and on the wall without greenery) during winter and summer periods. To analyze the effect on the internal temperature and energy use, a DesignBuilder simulation model was built and validated against these experimental results. This green wall has proven to have the greatest effect during the hottest summer days by reducing the indoor temperature by up to 3.5 °C. It also effectively increases the indoor temperature by up to 1.4 °C on a cold winter day, leading to energy savings of 6% on an annual basis.

Cooling Effectiveness of the Sustainable Cooling Solution for Cattle: Case Study in Poland

Recently, the dairy sector has been ever more affected by global warming. This study aimed to test a novel conductive cooling system for cattle that was successfully implemented and evaluated under summer thermally challenging weather conditions in Poland. The system consists mainly of the chiller, tank, and chilled water-driven mattress, designed to prioritize animal well-being. The experimental evaluation was carried out on three Friesian dry cows, housed on different types of bedding—commercial water mattress, straw, and cooling water mattress—and supplied with water at 10 °C (day) and 16 °C (night). The cooling water mattress’ surface temperature was twice as low as that of the commercial water mattress. The animal’s thermal comfort was assessed with physiological and behavioral reactions. The cooling effect on animals’ bodies was demonstrated with a lower reticulorumen temperature of the cooled cow (p < 0.05) than the reference ones. The local effect of cooling was proved with an 8 °C-lower skin temperature after the cow’s resting period. The presented study opens a new research direction toward dairy cattle’s welfare, sustainability, and the food–energy–water nexus, based on potential energy and water savings.

Assessing the Influence of Occupancy Factors on Energy Performance in US Small Office Buildings

Office buildings are responsible for about 35% of the total electricity in the US and over 70% of building energy consumption occurs during occupancy periods. Therefore, understanding occupancy behavior is crucial for reducing building energy consumption. However, given the stochastic nature of occupant behavior, identifying which occupancy parameters have the most impact on energy consumption poses a considerable challenge. This study aims to investigate and quantify the impact of various occupancy parameters on the energy performance of a US small-sized office building using an EnergyPlus-based nationwide energy simulation. First, dynamic occupancy schedules are created based on different occupancy parameters using an agent-based model. Next, the generated dynamic occupancy schedules are integrated into a small office building model from the Department of Energy’s prototypes. This creates a dataset of occupancy parameters and building energy performance across various climate zones. Finally, various feature selection and statistical analysis methods are applied to the generated dataset. This helps identify significant occupancy parameters and quantify their impact on building energy performance across different climate zones. According to the results of the study, buildings located in cool marine, mixed marine, and warm marine climate zones had lower total energy consumption compared to other zones. Additionally, feature selection methods identified “Occupant Density” as the primary significant variable impacting energy consumption, across all climate zones. These findings offer valuable insights into the influential occupancy parameters across various climate zones, highlighting the importance of tailoring occupancy schedules to enhance energy efficiency. They provide practical guidance that can be directly applied to optimize energy consumption and achieve significant energy savings in small office settings with different weather conditions.

Amino acids could sustain fungal life in the energy-limited anaerobic sediments below the seafloor.

In the depths beneath the ocean floor, where darkness, anaerobic conditions, and energy scarcity prevail, life persists against all odds. This study illuminates the pivotal role of amino acids, the fundamental building blocks of life, as a vital energy for deep subseafloor fungi. Our research uncovers how these fungi not only rely on amino acids for survival but also utilize them to reproduce, forming fruit bodies in environments deprived of oxygen and energy. This revelation not only elucidates the mechanisms enabling fungal survival in extreme conditions but also hints at the essentiality of amino acids as nutrients for other deep-sea microbes. By unraveling these mysteries of the hidden biosphere, our study opens new frontiers in understanding the resilience and adaptation of life in the most inhospitable environments on our planet.

Optimising Energy Efficiency in Offshore Buildings: Supporting SDG 7 - Clean and Affordable Energy

The offshore oil and gas sector faces significant challenges in reducing its carbon footprint while meeting global energy demand. Offshore structures consume up to 500 MW of energy per day. Despite the potential for 30-40% energy savings with efficiency technologies, only 25% of global platforms implement integrated energy management systems. This study aims to optimize energy efficiency in offshore structures to support SDG 7 - Affordable and Clean Energy. The study uses a multi-method approach, analyzing data from 10 offshore platforms, conducting energy modeling, and cost-benefit analysis. The results show variability in daily energy consumption (423.7 ± 32.5 MW) with key factors such as hydrocarbon production and environmental conditions. Energy efficiency technologies such as hybrid power generation systems and Integrated Energy Management Systems (SMET) show significant potential for savings. The optimization model shows a total potential energy savings of 37.2 ± 2.1%. Economic analysis using Monte Carlo simulations confirms the feasibility of investment with positive NPV for all evaluated technologies. SMET has the most favorable risk-return profile with a mean NPV of 5.8 ± 0.7 million USD. These findings provide important insights for operators and policymakers, emphasizing the importance of a holistic approach to energy management in offshore structures. Implementation of the proposed energy efficiency strategies can contribute significantly to climate change mitigation and the achievement of SDG 7.

Utility optimization for computation offloading and splitting in time-varying HAP and LEO satellite integrated MEC networks

To provide ubiquitous and low-latency communication and computation services for remote and disaster areas, high altitude platform (HAP) and low earth orbit (LEO) satellite integrated multi-access edge computing (HLS-MEC) networks have emerged as a promising solution. However, most current studies directly assume that the number of connected satellites is fixed and neglect the modeling of the time-varying multi-satellite computing process. Motivated by this, we establish an M/G/K(t) queuing model to illustrate task computation on satellites. To evaluate the efficiency and quality of computation offloading and splitting, we develop a utility model. This model is defined as a difference between a value function that assesses the trade-offs of task offloading, considering latency reductions and energy savings, and a cost function that quantifies expenses related to latency and energy consumption. After formulating the utility maximization problem, we propose the deep reinforcement learning-based offloading and splitting (DBOS) scheme that can overcome the time-varying uncertainties and high dynamics in the HLS-MEC network. Specifically, the DBOS scheme can learn the best computation offloading and splitting policy to maximize the utility by sensing the number of connected satellites, the distance between the HAP and satellites, the available computing resources, and the task arrival rate. Finally, we evaluate and validate the computational complexity and convergence property of the DBOS scheme. Numerical results show that the DBOS scheme outperforms the other three benchmarks and maximizes the utility under time-varying dynamics.

Revolutionizing Textile Manufacturing: Sustainable and Profitable Production by Integrating Industry 4.0, Activity-Based Costing, and the Theory of Constraints

The textile industry, a cornerstone of daily life and a highly globalized sector, faces significant environmental challenges due to its high water and energy consumption and extensive chemical usage. This study proposes a comprehensive green production planning and control model integrating Industry 4.0 concepts, activity-based costing (ABC), and the theory of constraints (TOC). The model utilizes mathematical programming to optimize product mix, maximize profitability, and minimize environmental impact. It leverages real-time sensing technologies and ERP systems to facilitate waste recovery, reduce carbon emissions, and achieve energy savings. Various carbon emission cost models, including continuous and discontinuous tax functions, are explored to balance corporate profitability with environmental sustainability. The findings demonstrate the model’s potential in optimizing resource utilization, reducing the environmental footprint, and enhancing profitability.

Energy-Efficient Architectural Design of a Banquet Hall with Integrated Tunnel Ventilation: Monitoring Performance During the Transitional Season in China

The construction industry, a significant contributor to global energy consumption and greenhouse gas emissions, is under considerable pressure to adopt transformative approaches. Public buildings, which account for a substantial portion of total energy usage, must balance high standards of thermal comfort with ventilation efficiency. In China, many public buildings are part of urban landscapes, where façade designs often limit natural ventilation. Consequently, technologies like earth-to-air heat exchangers and wind towers are increasingly essential for enhancing natural ventilation. However, research on the efficacy of these systems remains sparse. This study examines the transitional seasonal environment by evaluating the thermal-humidity index of a banquet hall equipped with an earth-to-air heat exchanger system. Using DeST software [DeST 2.0], the study simulates indoor natural ventilation, calculates ventilation rates, and assesses residual heat removal efficiency. The system’s performance is also modeled under various thermal design zones. Results demonstrate that under natural ventilation, the system can achieve a residual heat removal efficiency of up to 490%. Simulations across different climate zones indicate that the system performs best in regions with extreme temperature fluctuations, particularly those with hot summers and warm winters. In these areas, the system reduces the annual temperature difference by up to 56.7%, significantly improving thermal comfort and reducing dependency on air conditioning. In contrast, performance in milder regions like Kunming achieves only a 37.5% reduction in temperature difference. Overall, this study provides valuable insights into energy-efficient design strategies and thermal optimization for banquet halls, with significant potential for energy savings and enhanced occupant comfort.

Neuron-Inspired Flexible Phase Change Materials for Ambient Energy Harvesting and Respiration Monitoring.

The global energy crisis and climate change pose unprecedented challenges. Wearable devices with personal thermoregulation and energy harvesting hold great promise for achieving energy savings and human thermal comfort. Here, inspired by neurons, a novel phase change material (PCM) is reported for efficient energy harvesting and respiratory monitoring via a self-assembly strategy. The use of gum arabic (GA) enabled the encapsulation of polyethylene glycol (PEG) and the targeted distribution of carboxylated multi-walled carbon nanotubes (cMWCNTs) simultaneously in poly (ethylene vinyl acetate) (EVA) matrix. The material exhibits an outstanding toughness value of 14.88MJ m-3 and high elongation at a break of 565.67%, exhibiting remarkable flexibility. The material with sufficient melting enthalpy (71.11 J g-1) demonstrates high photothermal conversion efficiency (95.27%) under 808nm laser irradiation (105mW cm-2). In addition, due to the synergistic effect of GA and PEG, especially the formation of microdome structures on the surface, the material demonstrates ultrasensitive humidity responsiveness for respiratory monitoring with high precision, excellent repeatability, and fast response/recovery time (50.4/50.5ms). Notably, it shows great potential for moisture-electric generators (MEGs) with the function of non-contact sensing. This material opens the path toward next-generation wearable devices in energy conversion and health monitoring.

Synthesis of tin selenide nanoparticles using Polygonum avicular extract decorated on graphitic carbon nitride for enhancing photodegradation of amoxicillin trihydrate and photoproduction of hydrogen peroxide

In this research, tin selenide nanoparticles (SnSe-NPs) were synthesized using Polygonum avicular extract via the hydrothermal method and decorated on graphitic carbon nitride (g-C3N4) by the simple sonicated method to produce SnSe/g-C3N4 composites. The characterization and properties of the SnSe/g-C3N4 composites, as compared to pristine SnSe and g-C3N4, were determined by Fourier-transform infrared spectroscopy, X-ray powder diffraction, scanning electron microscope, transmission electron microscopy, field emission scanning electron microscopy, X-ray photoelectron spectroscopy, ultraviolet–visible diffuse reflectance spectroscopy, Mott-Schottky, and electrochemical impedance spectroscopy. As a result, the SnSe-NPs possessed the rod-like shape and after the decoration onto the g-C3N4 sheet surface, it reduced the bandgap energy of the g-C3N4 from 2.58 downward 1.43 eV. Besides, the photoactivities of the 10-SnSe/g-C3N4 catalyst were investigated via both sides of amoxicillin trihydrate (AMXT) photodegradation and hydrogen peroxide (H2O2) photoproduction, in which the results were achieved 87.84 % AMXT and 85.48 μM H2O2, respectively, under visible light. Furthermore, the photodegradation was consistent with the pseudo-first-order kinetics and it performed the highest photodegradation at pH ∼5, while the importance of isopropyl alcohol as a trapping agent and •O2− radicals was affirmed in the H2O2 photoproduction. Moreover, the photoproduction of H2O2 was remained after 4 cycles achieved at 62.70 % in the final cycle, which demonstrated the stability and reusability of the 10-SnSe/g-C3N4. These aforementioned results demonstrate that the SnSe/g-C3N4 material is a promising candidate for addressing environmental pollution and energy scarcity issues.

Influence of Substrate on Sb2Se3/CdS Heterojunction Thin Film Solar Cells and Evaluation of Their Performance by Dark J‐V Analysis

ABSTRACTA simple binary antimony selenide (Sb2Se3) absorber is evolving as an alternative photovoltaic material in thin film solar cells because of its unique properties and easy processing. Sb2Se3 thin films having good crystalline quality are grown via versatile thermal evaporation from pre‐synthesized near stoichiometric compound material on molybdenum‐coated soda lime glass (SLG) and borosilicate glass (BG) substrates. Following the systematic characterizations on the absorber films, substrate configured Sb2Se3/CdS heterojunction devices were fabricated and their photovoltaic characteristics have been studied using current density vs. voltage (J‐V), dark J‐V modeling, external quantum efficiency and capacitance vs. voltage measurements. The power conservation efficiency values of 4.88% and 5.04% were achieved for the devices fabricated on SLG and BG substrates, respectively with deficit in open circuit voltage. The obtained values are higher in comparison to the reported device efficiencies in substrate configured Sb2Se3 solar cells, in which the absorber is prepared through thermal evaporation. To understand the loss in open circuit voltage, a compact equivalent circuit model was considered and identified the contribution of different shunt leakage paths in the devices. In addition to that, the device fabricated on the SLG was stable with minimal changes in its photovoltaic performance for a period spanning over 200 days. The results obtained are encouraging with scope for improving the device performance through interface engineering and back surface passivation strategies.

Experimental study of preservation of probiotic lactic acid bacteria in freeze-dried yogurts

This article presents research results on the relationship between the survival rate of lactic acid bacteria and the content of neurotransmitters in freeze-dried yogurt and yogurt with the addition of 15% pumpkin puree as a cryoprotectant. The decrease (p < 0.05) in the survival rate of lactic acid bacteria up to 52% and a predominance of norepinephrine (660–680 pmol/g) was noted in yogurt without cryoprotectant. In yogurt containing pumpkin puree, the survival rate of lactic acid bacteria was 25–28% higher. The content of serotonin and dopamine in freeze-dried yogurt with puree increased (p < 0.05) to 120–130 and 350–360 pmol/g, respectively. The use of pumpkin puree affects the content of neurotransmitters and allows the preservation of lactic acid bacteria cells if a sufficiently high primary drying temperature is used. The higher primary drying temperature and the use of cryoprotectant results in decreased (p < 0.05) drying time, energy savings, and an average of 20% in carbon footprint.