Average Temperature Research Articles

Integrating the Living Wall with Mechanical Ventilation to Improve Indoor Thermal Environment in the Transition Season

A living wall, when integrated with a mechanical ventilation system, can effectively improve the indoor thermal environment and reduce indoor CO2 concentration during the transition season. In this study, a control experiment was conducted to analyze the effect of a living wall integrated with mechanical ventilation (LW-V) on indoor air quality. During the experiment, indoor air temperature, relative humidity, indoor air speed, and CO2 concentration were measured, while the skin temperature was monitored and subjective questionnaires were administered to 60 subjects. The results show that the indoor environment was effectively improved by employing the LW-V system, with the average indoor temperature decreasing by 1.45 °C, while relative humidity increased by 19.1%. Due to the plant photosynthesis, CO2 concentrations were reduced by 13.83 ppm. Meanwhile, the mean skin temperature was reduced by 0.18 °C and was closer to the neutral mean skin temperature. Questionnaire analysis reveals the LW-V system improved overall air freshness sensation and thermal comfort level by 1.09 and 0.53, respectively. The LW-V system improved the indoor thermal environment as well as air quality during the transition season significantly.

Comparative analysis of CFD models to simulate temperature non-uniformity during hydrogen tank refuelling

This study compares four computational fluid dynamics (CFD) models, i.e. k-ε, RSM, SAS, and LES, to simulate temperature non-uniformity during hydrogen tank refuelling. Three grids with a total number of control volumes of 64k, 363k, and 2.9 M were used. The maximum dimensionless wall distances, y+, were 80, 5 and 2.5, respectively. The predictive capability of the models was assessed by recommended statistical indicators using ten thermocouple locations during 620 s of the experiment. The comparative analysis demonstrated a better predictive capability of temperature non-uniformity and stratification by the LES model and a shorter simulation time. It is concluded that meshes with y+ larger than 80 would overpredict the average hydrogen temperature while meshes with y+<5 provide a good simulation accuracy. The results underline the importance of the turbulence model choice and the numerical grid resolution for proper prediction of temperature non-uniformity during hydrogen tank refuelling.

Multi-Scale Habitat Selection by the Wintering Whooper Swan (Cygnus cygnus) in Manas National Wetland Park, Northwestern China

Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park’s wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans.

Impact of wall thickness on the tissue cooling effect of cryoballoon ablation.

Understanding of the tissue cooling properties of cryoballoon ablation during pulmonary vein (PV) isolation is lacking. The purpose of this study was to delineate the depth of the tissue cooling effect during cryoballoon freezing at the pulmonary venous ostium. A left atrial-PV model was constructed using a 3-dimensional printer with data from a patient to which porcine thigh muscle of various thicknesses could be affixed. The model was placed in a 37-°C water tank with a PV water flow at a rate that mimicked biological blood flow. Cryofreezing at the PV ostium was performed 5 times each for sliced porcine thigh muscle of 2-, 4-, and 6-mm thickness, and sliced-muscle cooling on the side opposite the balloon was monitored. The cooling effect was assessed using the average temperature of 12 evenly distributed thermocouples covering the roof region of the left superior PV. Tissue cooling effects were in the order of the 2-mm, 4-mm, and 6-mm thicknesses (Figure), with an average temperature of -41.4 ± 4.2 for 2 mm, -33.0 ± 4.0 for 4 mm, and 8.0 ± 8.7 °C for 6 mm at 180 sec (p for trend < 0.0001). In addition, tissue temperature drops were steeper in thin muscle (maximum temperature drop per 5 s: 5.2 ± 0.9, 3.9 ± 0.7, 1.3 ± 0.7 °C, p for trend < 0.0001). The cooling effect of cryoballoon freezing is weaker in the deeper layers. Cryoballoon ablation should be performed with consideration to myocardial thickness.

Effects of gravel-sand and plastic film mulching on soil water and temperature retention in cold and arid regions without irrigation

Gravel-sand mulch (GSM) and plastic film mulch (PFM) are important ways of farming in cold and arid regions without irrigation. Nevertheless, there has been a lack of studies of the system response to live weather conditions. To quantify the effects of GSM and PFM on soil moisture and temperature retention, in-situ monitoring experiments were carried out in the arid belt of central Ningxia, China, using continuous monitoring of the field soil water and meteorological conditions at a 30-mimute time-step under three treatments: a bare soil (CK), soil covered by a layer of GSM, and soil covered by GSM and a layer of plastic film (i.e., GSM + PFM). Results show that: (1) With a limited precipitation of 221 mm during the growing season, the average volumetric soil water content (SWC) in the top 30-cm soil layer was lowest for CK, medium high for GSM, and highest for GSM + PFM. Compared to CK, the soil water storage increased by 54 % under GSM and 75.2 % under GSM + PFM; (2) The most frequently occurring low-intensity rainfalls are more efficiently stored in soil under GSM + PFM; (3) Similarly, the soil temperature was significantly increased under GSM and GSM + PFM conditions. Compared to CK, the average soil temperature in the top 5-cm layer increased by 2.5 °C under GSM and 4.8 °C under GSM + PFM during the germination period, which had effectively extended the growing season for about 30 and 50 days, respectively; (4) Although dewfall is only 4 % of rainfall, the total number of dew day was more than twice that of rain day. Thus, dewfall is a more frequent and dependable source of water for native plants and animals. Our results demonstrate that the benefits of GSM and PFM can be applied globally where either insufficient rainfall or low temperatures are limiting factors.

The Rohingya refugee crisis in Bangladesh: assessing the impact on land use patterns and land surface temperature using machine learning.

Bangladesh, a third-world country with the seventh highest population density in the world, has always struggled to ensure its residents' basic needs. But in recent years, the country is going through a serious humanitarian and financial crisis that has been imposed by the neighboring country Myanmar which has forced the government to shelter almost a million Rohingya refugees in less than 3years (2017-2020). The government had no other option but to acquire almost 24.1 km2 of forest areas only to construct refugee camps for the Rohingyas which has led to catastrophic environmental outcomes. This study has analyzed the land use and land surface temperature pattern change of the Rohingya camp area for the course of 1997 to 2022 with a 5-year interval rate. Future prediction of the land use and temperature of Teknaf and Ukhiya was also done in this process using a machine learning algorithm for the years 2028 and 2034. The analysis says that in the camp area, from 1997 to 2017, percentage of settlements increased from 5.28 to 11.91% but in 2022, it reached 70.09%. The same drastically changing trend has also been observed in the land surface temperature analysis. In the month of January, the average temperature increased from 18.86 to 21.31°C between 1997 and 2017. But in 2022. it was found that the average temperature had increased up to 25.94°C in only a blink of an eye. The future prediction of land use also does not have anything pleasing in store.

Asymmetry of hemispheric climate during MIS 16 versus MIS 12

Marine isotope stage (MIS) 16 (676-621 ka) and MIS 12 (478-424 ka) stand out as two significant glacial periods during the late Quaternary, demonstrating consistent continental ice volume or sea level, as discerned from benthic δ18O records. Intriguingly, the average sea surface temperature (SST) during MIS 16 surpasses that of MIS 12 by approximately 0.54–0.79 °C, while the atmospheric CO2 concentration during MIS 16 is approximately 16 ppmv lower than that of MIS 12. The underlying mechanism driving these discrepancies remains enigmatic. In this study, we present new high-resolution X-ray fluorescence (XRF) and grain size records covering the interval from 700 to 400 ka from Ocean Drilling Program (ODP) Site 1090 in the South Atlantic Ocean. We also integrated benthic δ13C, ice-rafted debris (IRD) and carbonate ion concentration ([CO32−]) records globally, to elucidate the distinct climate evolution during the MIS 16 versus MIS 12. Our findings suggest that MIS 12 is distinguished by a more substantial Antarctic ice-sheet, coupled with a weakened and/or equatorward displacement of southern westerly winds, and expansion of southern source water (SSW) alongside contractive northern source water (NSW). Conversely, the opposite climate state can be observed in MIS 16. The elevated atmospheric CO2 in MIS 12 and diminished atmospheric CO2 in MIS 16 may be attributed to reconfigurations in the ocean carbon reservoir regulated by the reorganization of deep-water masses and meridional ocean circulation, as a result of the divergent evolution of bipolar ice-sheets. Our study underscores the critical role of the interplay between the two polar regions in modulating deep-sea carbon storage on the orbital timescale and atmospheric CO2. This interplay is essential for a comprehensive understanding of past and future carbon cycle adjustments in response to climate change.

Heat transfer enhancement of a Stirling engine heating tube with three-pronged slant rods under oscillatory flow

Heaters are crucial components in Stirling engines, where the working medium adsorbed heat from an external heat source. Enhancing heat transfer within the heater is essential for boosting the operational efficiency of the Stirling engine. In this study, a tube equipped with three-pronged slant rods was employed to improve the heat transfer within the heater under conditions of oscillatory flow. Three pairs of dynamic longitudinal vortices were generated and exhibited regular movement patterns with distinct phase angles. In comparison to the smooth tube configuration, the enhanced tube outlet exhibited a notable increase in the average working-medium temperature by 62 K and 46 K during the entry and return stages, respectively. The degree of heat transfer enhancement was found to be contingent upon the pitch, height, and inclination angle of the slant rod. Optimal heat transfer enhancement was achieved with slant rods featuring a pitch of 26 mm, a height of 3.5 mm, and an inclination angle of 45°. The performance evaluation criterion ranged from 1.29 to 1.81 of enhanced tube compared to smooth tube. These findings underscore the effective enhancement of heat transfer facilitated by the three-pronged slant rods within the Stirling engine's heater.

Using a Leroux-prior-based conditional autoregression-based strategy to map the short-term association between temperature and bacillary dysentery and its attributable burden in China

BackgroundIn China, bacillary dysentery (BD) is the third most frequently reported infectious disease, with the greatest annual incidence rate of 38.03 cases per 10,000 person-years. It is well acknowledged that temperature is associated with BD and the previous studies of temperature-BD association in different provinces of China present a considerable heterogeneity, which may lead to an inaccurate estimation for a region-specific association and incorrect attributable burdens. Meanwhile, the common methods for multi-city studies, such as stratified strategy and meta-analysis, have their own limitations in handling the heterogeneity. Therefore, it is necessary to adopt an appropriate method considering the spatial autocorrelation to accurately characterize the spatial distribution of temperature-BD association and obtain its attributable burden in 31 provinces of China.MethodsA novel three-stage strategy was adopted. In the first stage, we used the generalized additive model (GAM) model to independently estimate the province-specific association between monthly average temperature (MAT) and BD. In the second stage, the Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the association and characterize its spatial distribution. In the third stage, we calculate the attribute BD cases based on a more accurate estimation of association.ResultsThe smoothed association curves generally show a higher relative risk with a higher MAT, but some of them have an inverted “V” shape. Meanwhile, the spatial distribution of association indicates that western provinces have a higher relative risk of MAT than eastern provinces with 0.695 and 0.645 on average, respectively. The maximum and minimum total attributable number of cases are 224,257 in Beijing and 88,906 in Hainan, respectively. The average values of each province in the eastern, western, and central areas are approximately 40,991, 42,025, and 26,947, respectively.ConclusionBased on the LCAR-based three-stage strategy, we can obtain a more accurate spatial distribution of temperature-BD association and attributable BD cases. Furthermore, the results can help relevant institutions to prevent and control the epidemic of BD efficiently.

A generalized curvilinear solver for spherical shell Rayleigh-Bénard convection

Summary A three-dimensional finite-difference solver has been developed and implemented for Boussinesq convection in a spherical shell. The solver transforms any complex curvilinear domain into an equivalent Cartesian domain using Jacobi transformation and solves the governing equations in the latter. This feature enables the solver to account for the effects of the non-spherical shape of the convective regions of planets and stars. Apart from parallelization using MPI, implicit treatment of the viscous terms using a pipeline alternating direction implicit scheme and HYPRE multigrid accelerator for pressure correction makes the solver efficient for high-fidelity direct numerical simulations. We have performed simulations of Rayleigh-Bénard convection at two Rayleigh numbers Ra = 105 and 107 while keeping the Prandtl number fixed at unity (Pr = 1). The average radial temperature profile and the Nusselt number match very well, both qualitatively and quantitatively, with the existing literature. Closure of the turbulent kinetic energy budget, apart from the relative magnitude of the grid spacing compared to the local Kolmogorov scales, ensures sufficient spatial resolution.

Lithium-Ion Batteries (LIBs) Immersed in Fire Prevention Material for Fire Safety and Heat Management

Lithium-ion batteries (LIBs) have emerged as the most commercialized rechargeable battery technology. However, their inherent property, called thermal runaway, poses a high risk of fire. This article introduces the “Battery Immersed in Fire Prevention Material (BIF)”, the immersion-type battery in which all of the LIB cells are surrounded by a liquid agent. This structure and the agent enable active battery fire suppression under abusive conditions while facilitating improved thermal management during normal operation. Abuse tests involving a battery revealed that the LIB module experienced fire, explosions, and burnouts with the target cell reaching temperatures of 1405 °C and the side reaching 796 °C. Conversely, the BIF module exhibited a complete lack of fire propagation, with temperatures lower than those of LIBs, particularly 285 and 17 °C, respectively. Under normal operating conditions, the BIF module exhibited an average temperature rise ~8.6 times lower than that of a normal LIB. Furthermore, it reduced the uneven thermal deviation between the cells by ~5.3 times more than LIB. This study provides a detailed exploration of the BIF and covers everything from components to practical applications. With further improvements, this technology can significantly enhance fire safety and prevent the thermal degradation of batteries in the real world.

Temperature exposure and sleep duration: Evidence from time use surveys

The Earth’s climate is projected to warm significantly in the 21st century, and this will affect human societies in many ways. Since sleep is a basic human need and part of everyone's life, the question of how temperature affects human sleep naturally arises. This paper examines the effect of daily mean temperature on sleep duration using nationally representative Hungarian time use surveys between 1976 and 2010. Compared to a day with an average temperature of 5–10 °C, colder temperatures do not influence sleep duration. However, as daily mean temperatures rise, sleep duration starts to strongly decline. The effect of a hot (>25 °C) day is −13.3 minutes, but if preceded by a few other hot days, the effect is even stronger, −24.7 minutes. The estimated sleep loss is especially large on weekends and public holidays, for older individuals, and men. Combining the estimated effects with temperature projections of twenty-four climate models shows that the warming climate will substantially decrease sleep duration. The projected impacts are especially large when taking into account the effects of heatwave days. This study also shows that different groups in society are likely to be affected in significantly different ways by a warming climate.

Thermographic evaluation and sensible heat emission of quails (Coturnix coturnix japonica) kept at different temperatures

The aim of this research was to evaluate the surface temperature and sensible heat emission of Japanese quails kept in a climate chamber at different temperatures: 24.0, 27.0, 30.0 and 33.0°C. The surface temperature was obtained using thermographic images collected in five regions (head, wings, back, legs and crest), calculating the average surface temperature (ST), the gradient between ST and air temperature (AT) and heat emissions by convection and radiation. The experimental design used was entirely randomised, with four treatments and six replications. Surface temperature in all regions of the birds' bodies and ST rose as air temperature rose, and the gradient between ST and AT decreased as AT rose, a fact which can make it difficult for the animals to exchange sensible heat with the environment. The crest and feet had the highest and lowest ST values, respectively. The heat emitted by the birds through convection and radiation decreases as the ambient temperature rises, and of the total heat emitted, there was a predominance of convection.

Manure temperature prediction for slurry storage in Sweden: Model validation including effects of shading, snow cover and mixing

Measuring and modelling manure temperatures are crucial for estimating greenhouse gas emissions from liquid manure storage. The manure temperature was recorded at various depths in two swine slurry storage tanks situated in Vallentuna (VA) and Örsundsbro (OR) in Sweden. These data were used to assess the effectiveness of a revised mechanistic model for estimating manure temperatures, which incorporates the effects of wall shading, snow cover, and manure input mixing. The average manure temperatures were higher than air temperatures in the summer and fall. This indicated that using air temperature would result in an underestimation of methane emissions when applying the 2019 IPCC Refinement methodology. The revised model estimated manure temperatures for spring, summer, fall, and winter as 4.8, 16.1, 7.8, and 2.6 °C at the VA tank and 11.6, 17.1, 9.5, and 3.6 °C at the OR tank. The root mean square errors between daily simulated and observed temperatures in the summer decreased in both tanks due to incorporating shadow effect into the revised model. Fall estimates did not improve, possibly because of uncertainties from slurry removal and higher precipitation inputs. Sensitivity analysis indicated that solar radiative heat input was reduced with higher tank walls and smaller tank diameters when applying the revised model. Wall shading may influence manure temperatures in tanks with small diameters at high-latitude locations. This study offers insights into understanding the relationship between manure temperatures and its thermal balance influenced by latitude, storage design, snow cover and mixing, and its implications for accurately estimating methane emissions.

Land use inspection technique affects land surface temperature from satellite data

This research aims to present a land use inspection technique that affects land surface temperature from satellite data by using Maha Sarakham province, Thailand as a case study. Procedures: 1) Analyze land use from Sentinel-2 Satellite data that can be divided into 4 categories such as water, agriculture, forest, and urban, 2) Analyze land surface temperature from Sentinel-3 Satellite data. The study results found that urban area has the highest average surface temperature followed by forest area, water area, and agricultural area respectively. The analyzed data from the satellite found the highest average surface temperature is 32.20°C. The result shows that this inspection technique can analyze land surface temperature in other areas of the countryThis research aims to present a land use inspection technique that affects land surface temperature from satellite data by using Maha Sarakham province, Thailand as a case study. Procedures: 1) Analyze land use from Sentinel-2 Satellite data that can be divided into 4 categories such as water, agriculture, forest, and urban, 2) Analyze land surface temperature from Sentinel-3 Satellite data. The study results found that urban area has the highest average surface temperature followed by forest area, water area, and agricultural area respectively. The analyzed data from the satellite found the highest average surface temperature is 32.20°C. The result shows that this inspection technique can analyze land surface temperature in other areas of the country.

Warming effects on grassland soil microbial communities are amplified in cool months.

Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (p < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.

Deleterious Effects of Heat Stress on the Tomato, Its Innate Responses, and Potential Preventive Strategies in the Realm of Emerging Technologies.

The tomato is a fruit vegetable rich in nutritional and medicinal value grown in greenhouses and fields worldwide. It is severely sensitive to heat stress, which frequently occurs with rising global warming. Predictions indicate a 0.2 °C increase in average surface temperatures per decade for the next three decades, which underlines the threat of austere heat stress in the future. Previous studies have reported that heat stress adversely affects tomato growth, limits nutrient availability, hammers photosynthesis, disrupts reproduction, denatures proteins, upsets signaling pathways, and damages cell membranes. The overproduction of reactive oxygen species in response to heat stress is toxic to tomato plants. The negative consequences of heat stress on the tomato have been the focus of much investigation, resulting in the emergence of several therapeutic interventions. However, a considerable distance remains to be covered to develop tomato varieties that are tolerant to current heat stress and durable in the perspective of increasing global warming. This current review provides a critical analysis of the heat stress consequences on the tomato in the context of global warming, its innate response to heat stress, and the elucidation of domains characterized by a scarcity of knowledge, along with potential avenues for enhancing sustainable tolerance against heat stress through the involvement of diverse advanced technologies. The particular mechanism underlying thermotolerance remains indeterminate and requires further elucidatory investigation. The precise roles and interplay of signaling pathways in response to heat stress remain unresolved. The etiology of tomato plants' physiological and molecular responses against heat stress remains unexplained. Utilizing modern functional genomics techniques, including transcriptomics, proteomics, and metabolomics, can assist in identifying potential candidate proteins, metabolites, genes, gene networks, and signaling pathways contributing to tomato stress tolerance. Improving tomato tolerance against heat stress urges a comprehensive and combined strategy including modern techniques, the latest apparatuses, speedy breeding, physiology, and molecular markers to regulate their physiological, molecular, and biochemical reactions.

The Application of a Non-Intrusive Methodology to Estimate Particle Egress Rate and Advective Heat Losses of a Falling Particle Receiver During On-Sun Tests

Abstract The direct measurement of particle temperatures and advective losses from solid particle receiver has been a topic of necessary interest to de-risk the technology and improve its performance. Due to the flow's transient and stochastic nature, it has presented a challenge to traditional thermometry and metrology methods. In this work, a simplified quantitative non-intrusive imaging methodology previously developed is applied to Sandia's falling particle receiver during on-sun tests to collect image sets, which could help estimate the average particle temperature and particle egress rate from the system. Further additions to the technique are presented to permit the estimation of the plume (air and particles) egress rate and total advective heat losses during on-sun operation. The falling particle receiver testing campaign in 2020 and 2021 allowed the team to capture multiple flow configurations and environmental conditions used to build a large database of data captures with different characteristics. Finally, the results captured were used to complete a regression study to gain further insight into the factors which impact the particle egress and the receiver's efficiency. Particle temperature, receiver flow configuration, and wind speed were found to be the most impactful factors in the study.

Diversity of orchid types in the Oeluan Tourism Forest, Bijeli Village, Noemuti District, North Central Timor Regency

Indonesia as a mega biodiversity country has a variety of fauna and flora. One of the floras that is often found in Indonesia is orchids. Orchids have high economic value and are able to balance the ecosystem in their habitat. This study was aimed at determining the diversity of orchid species in the Oeluan tourism forest. The current study employed a quantitative descriptive study by using the transect and the purposive sampling method. The research was conducted in February at the Oeluan Tourism Forest. The results of this study indicated that there were four terrestrial orchid genera and three epiphytic orchid genera. The analysis of the diversity index of orchid species in the Oeluan tourism forest resulted in the diversity index of (H’) 1.0438 in the medium category. The measured environmental factors at the study site were an average soil pH of 7, an average humidity of 76.33% and an average air temperature of 27.400C. The diversity of orchid species in the Oeluan tourism forest, bijeli village, Noemuti district, North Central Timor regency, East Nusa Tenggara Province, was included in the medium category.

Performance assessment of packed bed systems for humidity control in greenhouse applications: An experimental-based AI modeling approach

Optimal humidity control is essential for enhancing crop yields and ensuring favorable growth conditions in greenhouse agriculture. Packed bed systems have emerged as effective tools for regulating humidity levels, yet accurately assessing their performance remains unexplored, especially for temperate oceanic climates. This paper presents a packed-bed system with water as the working fluid to increase the humidity level during the winter for greenhouse cultivation. Accordingly, an experimental setup is developed, and a detailed parametric study is conducted. Further, an artificial intelligence (AI)-based modeling approach is developed for evaluating the performance of packed bed systems for greenhouse applications under varying environmental conditions with various inlet air flowrates, such as 176 m³/hr, 286 m³/hr, 383 m³/hr, and 428 m³/hr. Operating with water at an average temperature of 15.7 °C and a flow rate of 12.8 kg/min, the system achieves a significant 50% increase in humidity ratio, transitioning from an inlet humidity ratio of 6 g/kgda to an outlet ratio of 9 g/kgda, indicating its efficiency in elevating air humidity levels. The multi-layer perceptron neural network, trained with 112 non-repeated datasets and employing a 2-10-10-1 topology, demonstrates high accuracy and resilience in estimating Δωa values for the packed bed system, with predictions closely aligning with experimental data and exhibiting a maximum discrepancy within ± 2.5%. This research contributes to the advancement of precision agriculture practices by providing a comprehensive framework for assessing and improving humidity control in greenhouse environments.