Indoor Temperature Research Articles

The Impact of Residential Building Insulation Standards on Indoor Thermal Environments and Heat-Related Illness Risks During Heatwaves: A Case Study in Korea

This study investigates the impact of building insulation standards on indoor thermal environments and the risk of heat-related illnesses during heatwaves in South Korea. Indoor temperatures were measured in residential buildings located in Chuncheon and Gwangju during the 2022 heatwave, with outdoor temperature data sourced from the Korea Meteorological Administration. Probability distribution fitting was used to estimate the likelihood of indoor temperatures exceeding the critical threshold of 27 °C. Additionally, a linear regression analysis was conducted to examine the relationship between the probability of exceeding the threshold and heat-related illness data from 2017 to 2023 provided by the Korea Disease Control and Prevention Agency. The findings reveal significant variations in indoor thermal conditions during heatwaves, influenced by factors such as building type, year of construction, and climate region, which affect the thermal insulation performance. Buildings with a lower thermal insulation performance were associated with higher indoor temperatures, increasing the likelihood of exceeding the critical threshold and contributing to a higher incidence of heat-related illnesses, particularly in provincial non-metropolitan areas. These results underscore the need for region-specific building insulation standards that address both winter energy efficiency and summer heatwave resilience. Enhancing thermal insulation in vulnerable regions could significantly reduce the risk of heat-related illnesses and improve public health resilience to extreme heat events.

Design and development of geothermal-based cooling system for human comfort

In this study, a geothermal cooling system is developed to address extreme heat conditions in regions like Nawabshah, Pakistan, by utilising the earth’s stable underground temperature. This system uses ground-source cooling, powered by a 12V solar PV system or battery, as a low-energy alternative for areas with a limited electricity supply. The experiment demonstrates that a geothermal cooling system could help redress indoor temperatures by up to 16°C during peak summer, resulting in a lower grid-connected or fossil fuel-based cooling system requirement. The results obtained through this study suggest a significant reduction in indoor temperature, ultimately enhancing comfort levels and reducing the reliance on conventional cooling systems like air conditioning. Moreover, the system design is easily adaptable to other regions with similar climates, highlighting its potential for widespread use. However, pipe configuration optimisation is needed to minimise costs and maximise heat transfer rate. This research emphasises geothermal technologies' potential as a cost-effective cooling system, ultimately reducing carbon emissions and improving energy efficiency.

Health Impacts and Coping Strategies for Extreme Indoor Temperatures in Vulnerable Urban Communities in Sekondi-Takoradi, Ghana

Health Impacts and Coping Strategies for Extreme Indoor Temperatures in Vulnerable Urban Communities in Sekondi-Takoradi, Ghana

Indoor environmental conditions and likelihood of reported violence and aggression in a purpose-built residential dementia hospital

This study, conducted on purpose-built NHS dementia wards, investigates correlations between patient aggression and indoor temperature and humidity. Temperature and humidity, measured at 3-min intervals, on male and female wards, over 12–15 months, were compared against staff-recorded incidents (n = 299; females n = 100; males n = 199). Linear regression was used to assess potential correlations. Binomial analysis measured relative risk of incidents outside comfortable thermal (22–24 °C) and humidity (30%–60%) ranges. Temperatures ranged from 17 to 27oC and humidity ranged from 16 to 70%. On the male ward, both extremes of temperature were correlated with increased incident likelihood (R2 = 0.473) and relative risk of incidents was 1.89 (p = 0.0015) at temperatures <22oC and 1.73 (p < 0.001) at temperatures >24oC. On the female ward, increasing temperature was correlated with increased incident likelihood (R2 = 0.568) and relative risk of incidents was 1.99 (p < 0.001) at temperatures >24oC. Strong associations between relative humidity levels and incidents were not identified. Extreme temperatures were associated with significantly increased risk of incidents of agitation, suggesting relevance of environmental conditions in the formulation of agitation in dementia.

Summer Energy Use and Comfort Analysis in Rural Chinese Dwellings: A Case Study of Low-Income Older Populations in Shandong

This paper aims to investigate the indoor environmental conditions and energy use behaviours of older individuals in rural cold climates of China, with a specific focus on cooling practices during the summer months in the Shandong region. This study employs a mixed-method approach, combining quantitative indoor environmental monitoring with qualitative interviews and observations, to explore the relationship between environmental factors, household living conditions, and energy use patterns across five types of elderly households: three generations living together, older people living with grandchildren, older people living with children, older couples living together, and older people living alone. Data collection was conducted over five weeks during the summer of 2023 using HOBO UX100-003 data loggers, while external weather conditions were monitored by the China Meteorological Administration. Face-to-face interviews were conducted to gain deeper insights into daily cooling behaviours and energy use. The results reveal that cooling practices and indoor environmental conditions vary significantly among the different household types. Multigenerational households showed more complex energy use dynamics, with younger family members frequently operating high-energy appliances like air conditioners, while older individuals tended to rely on natural ventilation and electric fans to reduce energy costs. In contrast, older couples and solitary older individuals demonstrated more conservative cooling behaviours, often enduring higher indoor temperatures due to limited financial resources and a desire to minimize energy expenditures. Despite the high energy use intensity in some households, many homes failed to achieve comfortable indoor environments, particularly in dwellings with minimal insulation and older building materials. This study concludes that economic status, household structure, and building characteristics play crucial roles in shaping cooling behaviours and indoor comfort during the summer.

Exploring Biomaterial-Based CoolRoofs: Empirical Insights into Energy Efficiency and CO2 Emissions Reduction

The Cool Roof concept, known for its efficiency in summer due to high temperatures during this period, employs a light coating that covers the roof to prevent the absorption of heat and maintain lower indoor temperatures. This study integrates a chemical component with biomaterials to enhance performance and reduce CO2 emissions. The composition investigated in this research is recognized for its durability and ability to lower outside temperatures, thereby mitigating the urban heat island effect. This experimental study evaluates the sustainability of CoolRoofs in a cold room located in Signes, France. Temperature measurements are conducted from 25 September 2023 to 27 July 2024, both with and without the coating, to assess energy performance and CO2 emissions. The selection of the building type ensures optimal performance in both summer and winter. Results show that the maximum outside and inside surface temperatures for a Cool Roof are 48.7 °C and 25.6 °C, respectively, compared to 72.9 °C and 32.2 °C for an uncoated roof. Additionally, implementing a CoolRoof reduces thermal load through the cold room by 56%, while CO2 emissions can be reduced by up to 27.31 kg CO2/m2 over a 20-year period. This study presents a solution for enhancing energy and environmental performance year-round using a resilient composite.

Development of a Bayesian calibration framework for archetype-based housing stock models of summer indoor temperature

Archetype-based housing stock models of summer indoor temperature can support the development of policies to manage the climate change-driven increase in cooling demand and heat-related health impacts. Calibration can reduce the performance gap of such models, however, work on this topic is limited. Motivated by the growing importance of this underexplored research area, this paper introduces a framework for the Bayesian calibration of archetype-based housing stock models of summer indoor temperature. The framework includes data-driven procedures to classify dwellings into homogeneous groups and specify prior probability distributions. To demonstrate its application, an established bottom-up model based on EnergyPlus was calibrated using data collected from 193 dwellings monitored during the 2009 4M survey in Leicester, England. Post-calibration, the root-mean-square error reduced from 2.5°C to 0.6°C and remaining uncertainties were quantified. The application of this modular framework may be extended to models of energy use and other indoor environmental parameters.

Effectiveness of a dynamic living wall system of plants on indoor thermal environment in summer - an experimental study

Optimizing vertical greening systems to reduce their negative impact on buildings is important to reduce energy consumption. To reduce the long-term effects of fixed living plant walls on building facades, this study proposes an optimization scheme for dynamic living plant walls (DLWS). By combining dynamic building facades with living plant walls, this study analyzes the effectiveness of DLWS, fixed living plant walls (LWS), and dynamic shading sails (DSS) in regulating indoor temperature and humidity through controlled experiments. The results showed that DLWS and LWS had the same effect on cooling, reducing the average indoor temperature by 3.6°C during the daytime. Further, DLWS was able to increase the indoor air humidity within the appropriate range, which was lower than the LWS humidity by 6.9 RH. DLWS had a better cooling effect compared to DSS, and DLWS can reduce the indoor temperature by 2.7. The results authenticate the performance advantages and the possibility of applying dynamic plant living walls in practice.

Flexible regulation of airport air-conditioning systems: Impact of cooling load variations on temperature stability

The integration of renewable energy sources has led to notable supply-demand imbalances due to their intermittent nature. Air-conditioning systems, as significant energy consumers with considerable flexibility, play a crucial role in integrating renewable energy and regulating power systems. This paper delves into the capability of air-conditioning systems in airports to flexibly adjust, particularly examining how varying cooling loads impact indoor temperatures. The energy flexibility of the air-conditioning system is evaluated based on three fundamental cooling load variations (incremental, translational, and discrete), and several evaluation parameters are defined. For areas with smaller cooling load fluctuations, there is a greater adjustment margin, but long adjustment periods should be avoided. For areas with larger fluctuations, the original cooling load curve should be considered in the adjustment strategy. The simulation results show that advancing or delaying the supply by 1 hour during peak cooling load periods can ensure indoor temperature stability, and step-type cooling load curves do not adversely affect indoor comfort levels. Practical case studies further demonstrate that utilizing water storage as an active regulation strategy can reduce operational costs by 26%, and with flexible adjustments, this reduction can increase to 35-54%. The study offers a framework to optimize air-conditioning flexibility in airports, facilitating better renewable energy integration and grid stability, which holds significant potential to reduce costs and improve energy efficiency, thus contributing to sustainable energy management.

Study of thermal and humidity environment and prediction model in impinging jet ventilation rooms based on thermal and moisture coupling

Variations of indoor humidity have significant influence on thermal comfort, calculation accuracy of air-conditioning load and selection of design parameters. As one of the most promising advanced ventilation strategies, impinging jet ventilation (IJV) has received much attention. However, few study concerned its coupled indoor thermal and humidity environment and there is also no complete mathematical model for the IJV to synchronously predict its indoor temperature and humidity distributions. Therefore, this study first simulated the thermal and humidity environment in IJV rooms with considering the coupled thermal and moisture transfer effect. The results demonstrate a significant correlation between temperature and humidity distributions in IJV, with a correlation coefficient of approximately 0.4. Then, a simplified theoretical model for predicting temperature and humidity distributions in the IJV was established based on the theory of nodal model, and the key parameters within the model that are influenced by indoor airflow pattern were also identified. Next, the model results were compared with the simulation ones and showed that the proposed model is with a mean absolute error of 0.4°C for the prediction of temperature distribution and of 0.21g/kg for the prediction of humidity distribution. These discrepancies are sufficiently minor to validate the accuracy of the proposed model. Last, the potential application value of the proposed model was discussed. Overall, the current study contributes to extend the application of the existing coupled thermal and humidity models to IJV scenarios, and provides a robust theoretical foundation for the more rational design and practical application of the IJV.

Design of heat-resilient housing in hot-arid regions

Extreme heat events in urban areas increasingly challenge the capacity of electrical distribution systems to serve building cooling equipment under peak loads and, when power is interrupted, the thermal response of buildings that can delay the onset of dangerously high indoor temperatures. The design of new buildings and their operation can mitigate the risks of intense heatwaves, but architects and planners face a myriad of choices about what measures to select, and how best to estimate their individual and collective performance. To aid the design and operation of heat-resilient buildings, this paper takes a multidisciplinary approach that is novel in two key aspects. First, it evaluates the individual and aggregated impact of factors associated with architectural and urban design, equipment technologies, and human behavior. Second, its valuation metrics include the magnitude of peak electrical load, appropriate for assessing active measures aimed at reducing peak power, and the time after a power outage for indoor temperatures to reach levels associated with heat stress, an indication of the efficacy of passive (no power) measures. The application of the method in the Middle East North Africa (MENA) region, where growing populations and demand for space cooling make it particularly relevant, relies on knowledge of building codes and local construction practice. Single-factor testing shows that pre-cooling produces the largest reduction in peak electrical load during a simulated four-day heatwave, followed by building adjacency, maximum temperature set point and equipment loads. A combination of all considered factors reduces peak power by 70% and shifts the reduced peak to a later hour. In response to a power outage, the incorporation of architectural factors (roof, wall and window thermal resistance above code minima, increased thermal mass, reduced glazing solar heat gain coefficient and window shading) reduces the time above a Heat Index of 28 °C (caution) in a week-long test period in which the power failure occurs at hour 40 from 119 to 53 h. The presented methodology applies broadly to other building types and to regions affected by very hot weather.

Development of a high-strength lightweight geopolymer concrete for structural and thermal insulation applications

Investigating the thermal insulation properties of lightweight geopolymer concrete is essential. This paper aims to develop a lightweight aggregate geopolymer concrete (LWAGC) with good density, compressive mechanical and thermal insulation properties. The dry density of LWAGC was adjusted by incorporating expanded perlite (EP). The variation in physical and mechanical properties of LWAGC with different EP content was discussed, including dry density, P-wave velocity, ultimate compression strength and elastic modulus. Based on infrared thermal imaging technology, a rapid measurement method was proposed to simulate the indoor temperature change of buildings at high ambient temperatures. The thermal insulation performance of the LWAGC with different EP contents was further evaluated. The findings show that as the EP content in LWAGC increases, there is a corresponding decrease in P-wave velocity, dry density, ultimate compressive stress, and elastic modulus. The lowest dry density of LWAGC reaches 1209kg/m3 while the ultimate compressive stress is still larger than 25.0MPa, which can used as LC25 building materials in load-bearing structures. The results also show that the addition of EP can improve the thermal insulation properties of LWAGC. The LWAGC with 50% EP content has the highest reduction rate of temperature and can maintain the indoor temperature lower than 35 °C under high ambient temperature, which have potential application prospects in the load-bearing structures and thermal insulation of tall buildings.

Data-enhanced convolutional network based on air conditioning system start/stop time prediction

Most enterprise workshop operators frequently adjust the start/stop time of air conditioning systems based on indoor and outdoor temperatures and humidity to accommodate changing demand and weather conditions. However, relying on personal subjective experience for these adjustments often leads to operational delays or energy waste due to the lack of precision in determining optimal timing. Predicting air conditioning system start and stop times is crucial for energy consumption and savings in HVAC systems. Traditional data-driven methods have been insufficient in this regard, as they mainly focus on feature mapping and overlook the dynamic coupling relationships of process variables, resulting in subpar predictions. In response to this challenge, the paper introduces a novel approach known as the Periodicity and Long-Term Convolutional Neural Network (PLCNN). This method converts one-dimensional regression prediction data into two-dimensional data containing time series features to capture the dynamic coupling characteristics of the air conditioning system while maintaining the independent variation relationships of features. Experimental results using real factory floor data have demonstrated the superior performance of the PLCNN method. Specifically, this method achieved a 14.96% lower error rate compared to the traditional method and an 8.18% improvement compared to the deep learning method. Moreover, the implementation of the PLCNN method in the optimal control of air conditioning systems led to a significant 19.43% reduction in total monthly energy consumption. In conclusion, the proposed method offers a promising alternative to traditional approaches to forecasting and provides a solution to the common challenges encountered in traditional prediction tasks.

Thermal performance of a double-layer pipe-embedded phase change wall system in wood structures coupled with solar energy

In this study, we propose a dual-layer, pipe-embedded phase change wall system for wooden structures that integrates sky radiation cooling and solar heat collection for cross-seasonal operation. This system harnesses renewable energy and reduces the operational energy consumption of buildings. The primary focus of this study is the performance improving of the system during winter conditions. In winter, the system captures solar energy for daytime indoor heating and load reduction and stores excess heat in phase-change material (PCM) embedded within the wooden wallboard. The stored heat is then released at night to further reduce building loads. To assess the thermal performance of the proposed wall system under winter conditions, experiments were conducted across four different scenarios and a reference system was established for comparative analysis. The results indicate that the proposed wall system significantly improves the indoor thermal environment. Specifically, this integration increased the average indoor air temperature by 6.0 °C compared to the reference system and substantially increased the temperature of the wallboard. The inclusion of PCM notably enhanced the thermal performance by reducing nighttime heat loss. Consequently, the average indoor temperature in systems equipped with PCM-enhanced wallboards was 3.0 °C higher than that in the reference system.

Thermal performance analysis of a domestic-size absorption cooling system incorporating nanofluid with thermal insulation in hot climate of Algeria

The increased demand for energy consumption for air conditioning, due to rising temperatures, has created challenges related to thermal comfort in residential environments .In the present study, a simulation of an air conditioning system for a small building was conducted, considering various absorption cooling scenarios to assess system performance through dynamic and economic analysis. The proposed system employs a parabolic trough collector in conjunction with a storage tank, designed to cool a 12 m² room in Adrar, Algeria. The study aims to identify the optimal scenario based on temperature, heat, and system coefficient of performance indicators. A computer program was developed using characteristic equations and finite difference methods to analyze the system's behavior with different nanofluid concentrations and thermal insulation. Simulation results show that scenario with nanofluid and insulation the best performance is achieved with a 4% nanofluid concentration, a 9 m² solar collector, a 0.3 m³ storage tank, and 0.05 m thick polystyrene insulation. The system can operate for 9 h, maintaining an indoor temperature of 27°C with a peak cooling load of 3 kW. The economic analysis estimates an investment cost of 4535.4$ and Net Present Value 3,370.40$ with a payback period of 12 years and 3 months.

Hygrothermal performance of hybrid multi-storey buildings under future climate scenarios

Climate change, energy efficiency, and carbon footprint objectives pose significant challenges to the hygrothermal performance of building structures in climates with extreme temperature variations. To meet long term sustainability targets, buildings designed for a lifespan of up to 100 years must exhibit resilience not only to current climate conditions but also to projected future scenarios. This study evaluated the hygrothermal performance of a hybrid log-concrete multi-storey building, combining the structural strength of concrete with the sustainable, moisture-regulating properties of wood, to address energy efficiency and moisture control challenges in subarctic climates. Onsite measurements were validated using numerical simulations to assess hygrothermal performance of log wall structure under climate change scenarios. Results showed minimal mould growth risk under present conditions, while future climate projections (RCP8.5 for 2080) indicated a maximum mould index of 1.32 near the exterior log surface. These findings highlight the resilience of log-based structures in cold climates and underscore the need for proactive moisture management under warmer, more humid future scenarios. Stable ideal indoor temperatures (averaging 21.56 °C to 22.09 °C) and effective moisture control (with a maximum average moisture excess of 0.89 g/m3) over the measurement period further demonstrate the suitability of hybrid log-concrete buildings for energy-efficient, moisture-regulating construction in cold climates. The study recommends surface treatments that allow vapour diffusion while preserving wood’s hygroscopic qualities to enhance durability in changing climates.

Experimental study on the dynamic integration of PCM in building walls for enhancing thermal performance in summer condition

Passively integrating phase change material into the walls to enhance the thermal performance of the building has been a promising solution in recent years. As the PCM has a high latent heat capacity, it leads to damping the high variations of temperature and provides an obvious benefit in energy saving and indoor comfort. However, the traditional passive integration method of the PCM limited the utilization of the PCM. The thermal resistance between the PCM and the indoors restrains the thermal response of the PCM, and it between the PCM and the outdoors reduces the impact of outdoor heating or cooling on the PCM. In this study, a dynamic PCM integration in the building envelope method was proposed and experimentally investigated. A PCM layer and an air layer were combined to be integrated into the wall assembly, which allows the position of the PCM layer and the air layer could be changed to adjust the thermal resistance (air layer) between the PCM and indoors and outdoors. The results showed that this dynamic method can dramatically reduce the indoor temperature and the heat flux across the interior surface of the wall. Compared to the envelope with only static PCM layer configurations, the dynamic PCM provided a reduction of 9.1% in the indoor average temperature and a reduction of 116.0% in the peak heat flux during the experiment's three days, as well as the dynamic PCM, exploited more latent heat than the other static configurations. Considering the energy performance, the dynamic integration of PCM showed a 100% reduction in heat gain through the interior surface compared to the envelope with only a static PCM layer under summer conditions.

IAQ and ventilation measurements at the “ZEB Laboratory” office building in Norway

This study aims to assess indoor environmental quality (IEQ) within a Zero Emission Building (ZEB) office in Norway, focusing on occupant impact (CO2, temperature, humidity) and materials/substances influence (formaldehyde, particulate matter (PM2.5), total volatile organic compounds (TVOC)). It presents a detailed data collection spanning 14 months from March 30th, 2022, to June 1st, 2023.Occupancy varied significantly, affecting measured indoor air quality (IAQ) parameters, with the lowest temperatures recorded on the second floor and specific areas like the canteen experiencing temperature drops during low usage times. Relative humidity levels remained over 20% in winter despite the building's low occupancy, a notable aspect given Norway's dry winters. PM2.5 levels stayed below World Health Organization (WHO) guidelines, indicating effective pollution management.The study also evaluates the impact of reducing the ventilation rates on IAQ, noting no significant IAQ compromise. An analysis correlating IAQ measurements with building occupants' satisfaction post-intervention revealed that temperature is the most significant factor affecting satisfaction levels, excluding acoustic satisfaction. Occupants generally reported satisfaction with the indoor environmental quality (IEQ), with specific dissatisfaction tied to thermal environment and IAQ, suggesting the importance of temperature control in occupant perception.This research not only provides valuable insights into IEQ management in Zero Energy and Zero Emission office buildings but also emphasizes the critical role of indoor temperature and the potential of wooden structures to stabilize humidity levels, contributing to occupant comfort and satisfaction.

A hybrid mechanism-based and data-driven model for efficient indoor temperature distribution prediction with transfer learning

Efficient prediction of indoor temperature distribution (ITD) is crucial for various building-related applications, particularly in real-time thermal management. Despite efforts from both physics-based and data-driven perspectives, ITD prediction still faces challenges, particularly in balancing prediction accuracy with computational speed and addressing the need for extensive high-quality data in practical applications. To address these challenges, this study develops a hybrid temperature distribution prediction model (HTDPM) that integrates deep learning with physical mechanisms, enabling the effective capture of spatial-temporal dependencies and uncertainties with limited input parameters, achieving a balance between prediction accuracy and computational efficiency. Meanwhile, a novel transfer learning approach is applied to HTDPM (HTDPM-TL), significantly reducing data requirements and enhancing model generalization across various practical scenarios. Besides, orthogonal and randomized experiments are designed to simulate multiple real-world scenarios, thus constructing an extensive source domain dataset. The HTDPM-TL was tested in various real-world scenarios with several baseline methods, demonstrating an average RMSE of 0.794 ∘C, a computational time of 0.289 s, and limited data volume. The computational speed was improved by three orders of magnitude compared to CFD simulations, and the prediction resolution was enhanced threefold compared to traditional data-driven models. These results highlight the potential of HTDPM-TL to achieve an optimal trade-off between prediction accuracy, computational efficiency, and data requirement.

Thermal Management Enhancement of Building-Integrated Photovoltaic Systems using Coupled Heat Pipe and Evaporative Porous Clay Cooler

The building-integrated photovoltaic (BIPV) panel systems often lead to a notable decline in PV panels efficiency and lifetime due to their temperature rise because of inadequate cooling. This study investigates the performance of innovative cooling strategy of using a coupled heat pipes and porous clay cooler and compare it with other related three BIPV cooling systems configurations including a conventional BIPV cooling with and without air gap and a pure evaporative porous clay cooling. The aim is to improve the PV panel cooling, ultimately reduce the PV temperature and enhance the overall performance of the BIPV system as well as reducing the building indoor temperature and boosting energy efficiency within the building. The system model, comprising sets of transient equations for the different system configurations, was solved using MATLAB and confirmed with previous experimental findings. The results indicate that comparing with the traditional BIPV system, using BIPV/Clay cooling systems and the hybrid BIPV/Clay-heat pipe cooling systems achieved peak PV temperature reductions of up to 14 °C and 14.7 °C, respectively. Additionally, these cooling methods led to a maximum interior room temperature reduction of approximately 14°C and an average decrease of 8°C. Moreover, the hybrid BIPV/Clay-heat pipe cooling system demonstrates superior performance compared to traditional BIPV system, achieving the highest improvements in PV electrical efficiency, output power, and exergy efficiency, with gains of 7.8%, 6.4%, and 8.4%, respectively. Further, when the hybrid BIPV/Clay-heat pipe cooling system was employed, the clay cooling efficiency and clay exergy efficiency values improved on average by 30.2% and 29.7%, respectively, compared to the BIPV/Clay cooling system in addition to the increase of the lifetime of the PV panels due to isolating it from the contact with the water/water vapor of the clay cooling system. However, this hybrid approach resulted in a rise in electricity production costs from 0.077 $/kWh to roughly 0.138 $/kWh and extended the payback time from 7.38 years to 13.6 years. But, despite its initial economic drawbacks, the hybrid BIPV/Clay-HP cooling system demonstrates considerable effectiveness and long lifetime compared to other cooling configurations.