Surface Temperature Radiation Research Articles

Local thermal environment and thermal comfort of a novel low-temperature radiant structure using CFD simulation

A novel low-temperature radiant structure (LTRS) has been developed to create local thermal environment and thermal comfort. This design incorporates an air layer that separates the air-contact surface from the radiant cooling surface, which enables low-temperature radiant cooling, increases cooling capacity and reduces condensation risk. The study addresses the concern of whether the LTRS with low-temperature radiant cooling would degrade thermal comfort. Heat transfer models of the LTRS were developed, and agreed well with the experimental results with difference within ±0.3 °C. Four cases with radiant surface temperatures of 27.9, 15, 10 and 5 °C were investigated, and in all cases a consistent operative temperature was maintained. This study evaluated various parameters, including the air temperature and velocity distributions, mean radiant temperature, operative temperature, and thermal comfort indices. Results indicated that the application of the LTRS increased the supply air temperature by 1.6 °C, suggesting significant energy-saving potential ranging in 28.4 %–52.7 % compared to traditional all-air cooling systems. Moreover, both general and local thermal comfort under the regulation of the LTRS satisfied the criteria in the ASHRAE Standard 55. These findings demonstrate that the novel LTRS has the capability of improving energy efficiency while maintaining satisfactory levels of thermal comfort. This study provides valuable insights and serves as a reference for promoting the use of personalized radiant cooling systems and enhancing building energy efficiency.

Diatom-based inferences of environmental changes from an alpine lake on the southeast edge of the Tibetan plateau over the last 4000 years

To better understand how global and regional-scale climate has changed, high-resolution records for environmental changes are still needed in southwestern (SW) China during the Late Holocene epoch. This study presents a well-dated high-resolution diatom analysis from a 1.66-m-long sediment core taken from Lake Cuogeda (CGD) on the southeast (SE) edge of the Tibetan Plateau to document environmental changes over the past ∼4000 years. Diatom and other geochemical proxies show that, from 3850 to 3430 cal yr BP (before present, 0 BP=1950 AD, 1900 to 1480 BC), the environment of Lake CGD is acidic, oligotrophic, and enriched with humic acids. And the lake ice cover duration is short during this period. During 3430–1550 cal yr BP (1480 BC-400 AD), Lake CGD has less humic acid and a relatively high pH environment. The ice cover duration is longer, and the temperature drops during this period. Our multi-indicator recorded two environment fluctuations at ∼2800 cal yr BP (850 BC) and 2210–1950 cal yr BP (260 BC-0 AD). From 1550 to 3.6 cal yr BP (400–1946 AD), the lake ecosystem changed to a higher pH condition and had a prolonged freezing time. From 3.6 cal yr BP (1946 AD) to the present, Lake CGD’s water was acidic, with an environment of shorter duration of ice cover and stronger lake water turbulence. Comparisons between the CGD records and other climate reconstructions underscore the relevance of the CGD record for regional and global environments. Comparisons indicate that the environment evolution pattern of SW China during the Late Holocene was greatly affected by solar radiation and North Atlantic sea surface temperature.

Propagation Characteristics of Madden Julian Oscillation in the Indonesian Maritime Continent: Case Studies for 2020-2022

Madden-Julian Oscillation (MJO) can affect weather and climate variability in the Indonesian Maritime Continent. MJO propagation is not always the same, previous research has classified MJO into 4 categories: slow, fast, stand, and jump. The objective of this study is to investigate the differences in MJO propagation and the factors that impact it. Daily data for variables such as Outgoing Longwave Radiation (OLR), zonal wind, and sea surface temperature are utilized in this research. The collected data is processed using composite methods based on the 8 MJO phases, with a specific focus on the years 2020, 2021, and 2022. The research findings suggest that warm sea surface temperatures in the Pacific Ocean and zonal winds dominated by Kelvin waves are favorable for MJO propagation. Conversely, cooling sea surface temperatures in the Pacific Ocean and zonal winds dominated by equatorial Rossby waves can hinder MJO propagation. Future researchers are expected to examine the impact of MJO propagation during extreme rainfall occurrences in several regions of Indonesia, as well as the application of machine learning and deep learning methods to predict MJO propagation in the future.

Self-similar solutions for the non-equilibrium nonlinear supersonic Marshak wave problem

Similarity solutions to the nonlinear non-equilibrium Marshak wave problem with a time dependent radiation driving source are presented. The radiation transfer model used is the gray, non-equilibrium diffusion approximation in the supersonic regime. These solutions constitute an extension of existing non-equilibrium supersonic Marshak wave solutions, which are linear to the nonlinear regime that prevails in realistic high energy density systems. The generalized solutions assume a material model with power law temperature dependent opacities, a material energy density that is proportional to the radiation energy density, and a surface radiation temperature drive that obeys a temporal power law. The solutions are analyzed in detail, and it is shown that they take various qualitatively different forms according to the values of the opacity exponents. The solutions are used to construct a set of standardized benchmarks for supersonic non-equilibrium radiative heat transfer, which are nontrivial but straightforward to implement. These solutions are compared in detail to implicit Monte Carlo and discrete-ordinate transport simulations as well gray diffusion simulations, showing a good agreement, which demonstrates the usefulness of these solutions as a code verification test problem.

Enhancing the power generation performance of photovoltaic system: Impact of environmental and system factors

The rise in the surface temperature of a photovoltaic (PV) module due to solar heat significantly reduces the power generation performance of the PV system. Photovoltaic-Thermal (PVT) systems are being developed to overcome these limitations. The study discusses predicting power generation in PV and PVT systems. It identifies essential variables, such as solar radiation, relative humidity, and module surface temperature, that influence power generation. Regression equations were derived for PV and PVT. Results show that solar radiation plays a significant role in winter, while multiple factors affect summer power generation. The accuracy of power generation predictions using minimal variables is high, with PVT reaching 91.09%. The study also examines the effect of variables on power generation and the impact of environmental conditions, especially during summer and winter. It highlights the influence of flow rate on temperature and power generation in PVT systems. Overall, the research suggests that minimal variables can provide accurate power generation predictions, offering potential energy-saving strategies for buildings. The study emphasizes the significance of factors like solar radiation, surface temperature, and relative humidity in power generation and provides insights into predicting performance in different climates.

Impact of Soil Surface Temperature on Changes in the Groundwater Level

The relationship between the soil surface temperature and groundwater level is complex and influenced by various factors. As the soil surface temperature increases, water evaporates quickly from the soil, which can lead to a decrease in the groundwater level. In this study, we analyzed the impact of soil surface temperature on changes in the groundwater level in the Bukhara region of Uzbekistan using data from 1991 to 2020. The Bukhara region experiences regular water shortages, increased soil salinization, and inefficient energy in lift-irrigated areas, which is a typical constellation of challenges to the water–energy–food–environment (WEFE) nexus. The soil surface temperature data were collected from the Hydrometeorological Service Agency, whereas groundwater level data were obtained from the database of the Amelioration Expedition under the Amu-Bukhara Basin Irrigation Systems Authority. We used linear regression analysis and Analysis of Variance (ANOVA) tests to establish the significance of the relationship between the soil surface temperature and groundwater level, as well as the impact of the location of the groundwater level measurements. The results indicate that the model was a good fit to the data, and both the intercept and the soil surface temperature were significant factors that affected groundwater level. The results further suggest that the strength of the relationship between solar radiation and soil surface temperature is very high, with a correlation coefficient of 0.840. This means that when solar radiation increases, soil surface temperature also tends to increase. The analysis also showed that 53.5% of the changes in groundwater level were observed by the regression model, indicating a moderately correlated relationship between the groundwater level and soil surface temperature. Finally, higher solar radiation leads to higher soil surface temperature and higher evapotranspiration rates, which can lead to a decrease in groundwater level. As a result, we observe that the soil surface temperature determines changes in the groundwater level in the study region.

Study on predicting the radiant heat flow rate of floor surface of radiant floor heating

Radiant heat flow rate of radiant surface is crucial for radiant floor heating design and terminal selection. We found that the present empirical formula to predict radiant heat flow rate of radiant surface has limits under varied room size and surface emissivity circumstances. Wall insulation conditions also have substantial influences on the operating efficiency of floor radiant heating. Adopting machine learning algorithms and backward selection method, a two-layer Neural Network model was demonstrated to have good accuracy and requisite relevant features for new empirical formula was identified. The new formula containing the information of room depth, weighted radiant surface area, insulation conditions, indoor air temperature and radiant surface temperature as independent variables exhibits great accuracy with R-squared of 0.97 and RMSE of 2.74. The substitution of AUST with indoor air temperature can increase the prediction accuracy. Analysis reveals structural pattern and indicates interaction between wall insulation and non-radiative surface with low emissivity. We propose the use of non-radiant surfaces with low emissivity as a passive energy-saving technique for radiant floor heating. And the updated empirical formula can increase its application scenarios, and aid promote application of FRH and new passive technique.

How atmospheric humidity drives the outgoing longwave radiation–surface temperature relationship and inter-model spread

The Earth’s global radiation budget depends critically on the relationship between outgoing longwave radiation (OLR) and surface temperature (). Using the fifth generation of European ReAnalysis dataset, we find that although OLR appears to be linearly dependent on over a wide range, there are significant deviations from the linearity in the OLR– relationship for regions warmer than 270 K , which covers 89% of the surface of Earth. While the AMIP runs of CMIP6 models largely capture the overall OLR– relationship, considerable discrepancies are found in clear-sky OLR at given ranges. In this study, we investigate physical mechanisms that control the clear-sky OLR– relationship seen in reanalysis and CMIP6 models by using accurate radiative transfer calculations. Our study identifies three key mechanisms to explain both the linearity and departure from linearity of the clear-sky OLR– relationship. The first is a surface contribution, controlled by the thermal emission of the surface and the infrared opacity of the atmosphere, accounting for 60% of the observed clear-sky OLR– linear slope. The second is changes in atmospheric emission induced by a foreign pressure effect on water vapor and other greenhouse gases, which accounts for 30% of the linear slope in a clear-sky condition. The third is changes in atmospheric emission induced by variations in relative humidity (RH), particularly in the mid-troposphere (250 to 750 hPa), which determines the non-linearity in the clear-sky OLR– relationship and adds to the remaining 10% of the slope. The inter-model spread in mid-tropospheric RH explains a large fraction of the differences in clear-sky OLR across CMIP6 models at given surface temperatures. Furthermore, the three key mechanisms outlined here apply to the OLR– relationship in all-sky conditions: clouds disguise the surface contribution but increase the atmospheric contribution, retaining a similar linear slope to the clear-sky condition while amplifying the non-linear curvature.

An independent framework-based evapotranspiration model (IFEM) for dual-source: From field to regional scale

The triangle/trapezoid framework model (TFM) is a widely used approach for mapping regional evapotranspiration (ET) based on thermal infrared remote sensing imagery. However, the homogeneity assumption for meteorological forcing and surface properties involved in TFM contradicts the characteristics of heterogeneous regions, leading to high uncertainty at regional scale, especially under energy-limited or strong advection conditions. Therefore, this study examined the linear relationship between soil moisture availability (ΛSM), evapotranspiration efficiency (ΛET) and radiation surface temperature (Trad), and developed an Independent Framework-based dual-source ET Model (IFEM) for heterogeneous regions. By fixing two key meteorological forcing variables, air temperature (Ta) and vapor pressure deficit (VPD), and three surface characteristic parameters, aerodynamic resistance (ra), albedo (α) and the ratio of soil heat flux to net radiation (Γ), the IFEM constructs a uniform fractional vegetation cover (fc)- Trad space. In this uniform fc-Trad space, isolines of ΛSM and ΛET are aligned with those of Trad, and an independent trapezoid framework is constructed for each pixel of RS images. It avoids the systematic bias caused by the distorted trapezoid space involved in traditional TFMs. The proposed model was applied in a hydrologically semi-enclosed irrigation area, the Hetao Irrigation District, with Landsat and MODIS datasets from 2016 to 2020 to evaluate its performance at the field and region scales. Firstly, the IFEM was capable of retrieving latent heat with a mean absolute error (MAE) of 34.43 W m−2 and a mean absolute percentage error (MAPE) of 8.68%, compared with the measurements from flux towers. Secondly, the IFEM reasonably separated the soil (MAPE = 21.33%) and canopy (MAPE = 14.33%) components from ET, compared with the soil evaporation observed by micro-lysimeters and the plant transpiration calculated by sap velocity upscaling technology. Thirdly, the IFEM showed high accuracy in estimating annual total ET with a percentage error range within ±3.0%, compared against the regional water balance calculations. Overall, the IFEM demonstrated high robustness and accuracy for field-scale and regional-scale applications, validating its potential as a reliable method for mapping regional ET in heterogeneous regions.

Anti-Condensation Temperature Control Strategy of the Concrete Radiant Roof

Radiation cooling, as a new terminal mode that has been gradually emerging in recent years, has attracted more and more attention. However, the problem of condensation has become a vital bottleneck restricting the broad application of radiation-cooling technology. This paper used the numerical simulation method of Ansys Fluent to study the effect of different water supply parameters on the concrete radiant roof’s heat transfer performance, temperature uniformity analysis, and anti-condensation temperature control strategy. The accuracy of the simulation model was verified by comparing the numerical simulation values and measured values of temperature monitoring points. In thermal performance research, the inlet temperature significantly impacted the cooling capacity and radiant surface temperature compared with the inlet flow velocity. In the uniformity study, the distance between the serpentine pipes area and the concrete edge was easily neglected, which was also an important factor affecting the distribution of temperature uniformity. Regarding anti-condensation and performance improvement research, first supplying water at low temperatures and then dynamically adjusting high-temperature water could effectively avoid condensation and improve the radiant roof’s heat transfer performance. The research results could provide technical references for the practical application of radiation roof anti-condensation temperature control technology.

Influence of solar radiation on the surface loss of the painted statues in Grotto No. 3 of Maijishan Grottoes, China

The embedded hygrothermal environment of cultural heritages (solar radiation, temperature, humidity, etc.) plays a significant role in their conservation and survival, especially in the case of outdoor ones. The surface loss of painted statues is often related to fluctuations in the surface temperature caused by the ever-changing solar radiation; however, the quantitative relationship between them remains unclear. To clarify, in this paper, hygrothermal monitoring and numerical simulation were conducted on painted statues with an age of over 1400 years in the World Heritage Maijishan Grottoes. The results showed that the ruined eaves have led to significant differences in solar radiation intensity and surface temperature between the upper and lower statues, with maximum values of 598.7 W/m2 and 13.6 °C, respectively, corresponding to surface loss rates of nearly 15% and 50%. Under the influence of direct insolation, the thermal stress on the statue surface increased with decreasing height, resulting in a difference of 10.8 kPa between the highest and lowest points. Taking the tensile strength of clay (10 kPa) as a threshold of thermal stress, the yearly number of events exceeding this threshold at the upper and lower rows were 2819 and 3173, respectively. Overall, direct insolation has a significant effect on the temperature changes on painted statue surfaces, thus leading to greater thermal stress and greater degrees of surface loss. For heritages in open or semi-open environments, it is necessary and effective to evaluate their preservation conditions based on the threshold and then propose suitable conservation methods for preventive protection.

Global monsoon systems and their modulation by the equatorial Quasi-Biennial Oscillation

Monthly-mean data of ERA-Interim reanalysis, precipitation, outgoing longwave radiation (OLR) and sea surface temperature(SST) are investigated for 40 years (1979-2018) to reveal the modulation of the global monsoon systems by the equatorial quasi-biennial oscillation (QBO), focusing only on the neutral El Niño-Southern Oscillation (ENSO) periods (in total 374 months). First, the climatology of the global monsoon systems is viewed with longitude-latitude plots of the precipitation, its proxies and lower tropospheric circulations for the annual mean and two solstice seasons, together with the composite differences between the two seasons. In addition to seasonal variations of Intertropical Convergence Zones (ITCZs), several regional monsoon systems are well identified with an anti-phase of the annual cycle between the two hemispheres. Precipitation-related quantities (OLR and specific humidity), surface conditions [i.e., mean sea level pressure (MSLP) and SST] and circulation fields related to moist convection systems show fundamental features of the global monsoon systems. After introducing eight QBO phases based on the leading two principal components of the zonal-mean zonal wind variations in the equatorial lower-stratosphere, the statistical significance of the composite difference in the precipitation and tropospheric circulation is evaluated for the opposite QBO phases. The composite differences show significant modulations in some regional monsoon systems, dominated by zonally asymmetric components, with the largest magnitudes for specific QBO-phases corresponding to traditional indices of the equatorial zonal-mean zonal wind at 20 and 50 hPa. Along the equator, significant QBO influence is characterized by the modulation of the Walker circulation over the western Pacific. In middle latitudes during boreal summer, for a specific QBO-phase, statistically significant modulation of low-pressure cyclonic perturbation is obtained over the Northern-Hemisphere western Pacific Ocean associated with statistically significant features of heavier precipitation over the eastern side of the cyclonic perturbation and the opposite lighter precipitation over the western side. During boreal winter, similar significant low-pressure cyclonic perturbations were found over the Northern-Hemisphere eastern Pacific and Atlantic Oceans for specific phases.

Field-Layer Vegetation and Water Table Level as a Proxy of CO2 Exchange in the West Siberian Boreal Bog

The Mukhrino field station has participated in the national project on the inventory of carbon fluxes and pools in the terrestrial ecosystems of Russia since 2022. The development of a network of measurements of CO2 fluxes and phytomass covered six types of bog ecosystems typical to Western Siberia. The gross ecosystem exchange (GEE) of the field-layer vegetation (medians for the period from the end of May to the end of July, mgC m−2 h−1; see errors in Results section) decreased in series: Sphagnum bog with sparse low pine trees (“Open bog”), ridges in ridge-hollow patterned bogs (“Ridge”), pine-dwarf shrub-Sphagnum bog (“Tall ryam”), hollows in patterned bogs (“S.hollow”, “E.hollow”) and pine-dwarf shrub-Sphagnum bog (“Ryam”): −220, −200, −125, −120, −109 and −86, respectively. Ecosystem respiration (Reco) here was 106, 106, 182, 55, 97 and 136. The aboveground and belowground phytomass of mosses in this series varied between 368 ± 106–472 ± 184 and 2484 ± 517–6041 ± 2079 g/m2, respectively: the aboveground phytomass of vascular plants and plant litter—15 ± 7–128 ± 95 and 10 ± 6–128 ± 43, respectively. According to the results of mathematical modeling, the best proxy for GEE, in addition to photosynthetically active radiation and soil surface temperature, was the aboveground phytomass of vascular plants (PhV), and for Reco—PhV and the mass of the plant litter of vascular plants.

Evaluation and thermal performance of cool pavement under desert weather conditions: Surface albedo enhancement and carbon emissions offset

Surfaces such as pavement, buildings, and other heat-absorbing surfaces that store more heat than natural vegetation generate the Urban Heat Island (UHI) effect. Temperatures are known to be significantly higher in urbanized areas compared to rural ones.The application of a reflective surface treatment to the pavement improves its solar reflectivity while lowering the warmth of its surface. The main objective of this study is to assess the performance of a cool pavement in an educational complex parking area, under desert climatic conditions to reduce heat islands. White and high reflective material was applied to the tested parking pavement area. Various experimental techniques were used to assess the performance of non treated (baseline) and treated (cool) pavements including spectral radiation, reflectance (albedo), solar irradiance, and pavement surface temperature. The results show that the coated pavement has a 15 % reflectance in ultraviolet A (UVA) and the untreated pavement has a 17 % solar reflectance (baseline basement). There are no potential dangers to human health posed by the coated pavement's reflection of UVA (For visible wavelengths, coated pavement has a reflectance of roughly 70 %, while uncoated pavement has a reflectivity of only 24 %. Under desert climatic conditions, the results show a net decrease in surface temperature of the coated pavement by up to 15 °C compared to the uncoated one. In the summer, for example, raising the albedo of the pavement surface from 24 % to 70 % lowered the surface temperature from 60 °C to 47 °C. This represents a 22 % decrease in pavement surface temperature. The thermal performance analysis of the cool pavement technology reveals that the pavement surface albedo enhancement will help to increase surface reflectance while lowering pavement surface temperature and offsetting CO2 emissions. Increasing the pavement surface albedo by 192 % (from 24 % to 70 %) for the total treated surface area (81,000 m2) in the educational complex will offset 28,350 tons of CO2. The application of a white coating with a high reflective value on concrete and asphalt pavements will help to extend the life of the pavement, reduce the energy consumption of buildings and the emissions of greenhouse gases, minimize the emissions of carbon dioxide caused by the enhancement of albedo (a strategy for mitigating the effects of climate change), improve parking lot visibility, and deal with the effects of heat islands.

An exploratory, intra- and interindividual comparison of the deep neural network automatically measured calf surface radiation temperature during cardiopulmonary running and cycling exercise testing: A preliminary study

Non-invasive and contactless infrared thermography (IRT) measurements have been claimed to indicate acute neural, cardiovascular, and thermoregulatory adaptations during exercise. Due to challenging comparability, reproducibility, and objectivity, investigations considering different exercise types and intensities, and automatic ROI analysis are currently needed. Thus, we aimed to examine surface radiation temperature (Tsr) variations during different exercise types and intensities in the same individuals, ROI, and environmental conditions. Ten healthy, active males performed a cardiopulmonary exercise test on a treadmill in the first week and on a cycling ergometer the following week. Respiration, heart rate, lactate, rated perceived exertion, the mean, minimum, and maximum Tsr of the right calf (CTsr (°C)), and the surface radiation temperature pattern (CPsr) were explored. We executed two-way rmANOVA and Spearman’s rho correlation analyses. Across all IRT parameters, mean CTsr showed the highest association to cardiopulmonary parameters (E.g., oxygen consumption: rs = −0.612 (running); −0.663 (cycling); p < .001). A global significant difference of CTsr was identified between all relevant exercise test increments for both exercise-types (p < .001; η2p = .842) and between both exercise-types (p = .045; η2p = .205). Differences in CTsr between running and cycling significantly appeared after a 3-min recovery period, whereas lactate, heart rate, and oxygen consumption were not different. High correlations between the CTsr values extracted manually and the CTsr values processed automatically by a deep neural network were identified. The applied objective time series analysis enables crucial insights into intra- and interindividual differences between both tests. CTsr variations indicate different physiological demands between incremental running and cycling exercise testing. Further studies applying automatic ROI analyses are needed to enable the extensive analysis of inter- and intraindividual factors influencing the CTsr variation during exercise to allow determine the criterion and predictive validity of IRT parameters in exercise physiology.

Modeling the spatial distribution of the ctenophore Mnemiopsis leidyi A. Agassiz, 1865 in the Black Sea using a fuzzy rule-based system

Species distribution models can predict species occurrences in areas where no data is available by finding relationships between occurrences and environmental parameters. In this study, we applied a fuzzy rule-based system to model the spatial distribution of Mnemiopsis leidyi in the Black Sea and predict the probability of its presence throughout the sea. Six variables were used as predictors, including water turbidity, organic and inorganic particulate carbon, photosynthetically active radiation, light absorption by phytoplankton, sea surface temperature, and chlorophyll-a concentration. The results revealed a 0.807 accuracy of the model based on the confusion matrix. The results also showed that photosynthetically active radiation and sea surface temperature were the most important predictors shaping the distribution of this species. The findings also showed that the northern Black Sea was with the highest probability of presence, especially in Ukraine and Russia’s coastal areas. In the coastal areas of Turkey, the highest presence probability was found near Rize, Trabzon, Ordu, and from Sinop to Zonguldak. Therefore, continuous monitoring of the Turkish coastal area is crucial to better understanding the effects of climate change and anthropogenic influences on the further distribution patterns of this invasive ctenophore in the southeastern Black Sea.

Uncertainty analysis of photovoltaic cells to determine probability of functional failure

In engineering practice, extensive uncertainties exist in photovoltaic (PV) cell material parameters owing to manufacturing process errors and in PV cell working environment parameters owing to environmental uncertainties. Ignoring the uncertainty of these parameters will greatly reduce the reliability of photovoltaic cells. In this study, a PV cell model was used to conduct an uncertainty analysis based on functional failure. Functional failure is defined as output power fluctuation beyond the specified range, and functional safety region is defined as the allowable fluctuation range of output power during operation. A global sensitivity analysis method based on the Monte Carlo method was employed to study the influence of parameter fluctuation on the functional failure probability of a PV cell. An uncertainty analysis method based on Latin hypercube sampling was applied to study the influence of parameters on the probability of PV cell operation in the functional safety domain. The results indicate that the uncertainty of surface temperature had the most significant influence on the failure probability, followed by the ideality factor, radiation intensity, and current temperature coefficient, the series and parallel resistances had the smallest impact. Optimal values of 510.200 W/m2, 284.600 K, and 1.446 were obtained for radiation intensity, surface temperature, and ideality factor, respectively, which ensured that system functional failure probability remained in the safety zone with values of 93.763 %, 99.211 %, and 98.856 %, respectively. Additionally, the lower series resistance and the higher parallel resistance, the more likely the system to operate in the functional safety domain. The results of study expand the evaluation standard for PV cell operation and ensure the desired system output power.

Technological avenues and market mechanisms to accelerate methane and nitrous oxide emissions reductions.

Strategies targeting methane (CH4) and nitrous oxide (N2O) emissions are critical to meeting global climate targets. Existing literature estimates the emissions of these gases from specific sectors, but this knowledge must be synthesized to prioritize and incentivize CH4 and N2O mitigation. Accordingly, we review emissions sources and mitigation strategies in all key sectors (fuel extraction and combustion, landfilling, agriculture, wastewater treatment, and chemical industry) and the role of carbon markets in reducing emissions. The most accessible reduction opportunities are in the hydrocarbon extraction and waste sectors, where half (>3 Gt-CO2e/year) of the emissions in these sectors could be mitigated at no net cost. In total, 60% of CH4 emissions can be mitigated at less than $50/t-CO2. Expanding the scope of carbon markets to include these emissions could provide cost-effective decarbonization through 2050. We provide recommendations for carbon markets to improve emissions reductions and set prices to appropriately incentivize mitigation.

Potential of hybrid radiant cooling with infrared-transparent membranes to improve thermal comfort in hot and humid climate

• Condensation risk limits radiant cooling in a hot and humid climate. • Infrared-transparent membranes prevent condensation on radiant cooling surfaces. • Radiant surface at 4 °C below dew point reduced discomfort hours by 3–6%. • Experiments-modeling should target lower radiant surface temperatures. • Solar gains significantly affected radiant cooling effectiveness. Condensation risk has limited the deployment of radiant cooling systems for improving thermal comfort in hot and humid climates. Infrared-transparent membrane films emerged as a viable alternative to improve hybrid radiant cooling by preventing moisture condensation. This case study assesses the potential of membrane-assisted radiant cooling in a rural school building in Santa Lucia, Atlántico (Colombia), a location with a hot and humid tropical climate throughout the year. The study evaluates different cooling strategies, including natural ventilation, mechanical ventilation, hybrid radiant cooling, and membrane-assisted radiant cooling using EnergyPlus® software. Results for a radiant surface temperature of 4 °C below the dew point show that membrane-assisted radiant cooling could reduce annual discomfort hours by 3–6% compared to conventional radiant cooling. Further experimental and modeling studies should focus on the lowest achievable temperature below the dew point without condensation. Our results suggest that radiant cooling with infrared-transparent membranes is a potentially cost-effective alternative for improving thermal comfort in rural school buildings in hot and humid climates.

OPTIMIZATION MODEL FOR RESERVOIR WATER BODY SURFACE AREA USE IN THE FLOATING PHOTOVOLTAIC POWER PLANT

This research intends to optimize the use of reservoir inundation surface area as the Floating Photovoltaic Power Plant (PLTS). The research location is in the Waduk Jatigede, Cijeungjing Village-Jatigede District-Sumedang Regency, West Java Province, Indonesia. The Jatigede is a multi-function reservoir. This reservoir is used for raw water, irrigation, flood control, recreation, sport, and Floating Photovoltaic Power Plant (PLTS). Based on the data of solar radiation intensity, wind velocity, and surface temperature, this research intends to analyze the effect of EBT on the optimization model for using reservoir water surface.The methodology includes the optimization of reservoir water body surface area use for the Floating Photovoltaic Power Plant (PLTS) using Simplex Linear Programming. The optimization is implemented under the three scenarios as follows: 1) Design of floating PLTS island area with attending the bathymetry measurement; 2) Design of floating PLTS island area without attending the bathymetry measurement by the dimension is 160 m x 320 m; 3) Design of floating PLTS island area without attending the bathymetry measurement by the dimension is 320 m x 320 m. The results show that 1) The utilization of reservoir inundation surface area based on the optimization result is 16,703,000 m2 or 1,670.3 ha (42.25%) from the total of reservoir inundation surface area that is 3,953 ha with the electrical production of PLTS is 3,078 MWp or in average is 5,617 GWp per-year; and 2) the evaluation of Waduk Jatigede performance indicates that the operation pattern based on the simulation by using the Simplex Method can fulfil the demand. The last result of simulation has the reliability of 79.17%, the volatility is 80.00%, and the vulnerability is 28.74%. It means that the reservoir has the ability in amount of 79.17% for fulfilling the demand. Meanwhile the reservoir ability for returning back to the satisfied condition from the failure condition to fulfil the demand is 82.92%, and in the case of the failure, 28.74% of demand cannot be fulfilled with the average deficit is 7.67 million m3 per 15 days every failure event.