Search

• Twilight phenomena occurs in the thermosphere. • An equation has been derived to calculate diurnal atmospheric height using the twilight images analysis. • The diurnal atmosphere has estimated height ∼304 km above sea level. • Lower wind speeds and temperatures resulted in a higher thickness of diurnal atmosphere. • Higher relative humidity and dew point resulted in a higher thickness of diurnal atmosphere. • The first appearance of dawn twilight is at dip = ∼15°. An equation has been derived through which the height of the diurnal atmospheric layer (lower atmosphere) can be calculated using ground base twilight image analysis. This equation relies on the angular altitude of the twilight with the dip at that moment. Based on the images, it was found that true twilight of dawn occurs at a dip of 14.90° ± 0.17° as detected by the camera or ∼15° by considering the elevation above sea level (while it may be delayed to ∼14.7–14° with the naked eye), which is accompanied by an average twilight angular altitude of 2.66° ± 0.23°. From these values, the twilight height is estimated to be 303.80 ± 5.69 km above sea level. It is shown that the twilight region is the peak zone of the thermosphere. Its height also varies with time according to changes in various atmospheric parameters. Lower wind speeds, higher relative humidity, higher dew point, and lower temperatures resulted in a higher altitudinal angle of the atmosphere and consequently a greater diurnal atmospheric layer's thickness. Image analysis shows that the thermosphere always has a maximum value of light brightness during the night even before the appearance of twilight. Additionally, It defined the light source, shapes, and stages of twilights that detected by images. This implies that sky image analysis is an inexpensive method for understanding the properties and various parameters of the atmosphere. [ABSTRACT FROM AUTHOR]

The dew point pressure can be obtained by conventional condensate gas phase test in PVT cylinders. However, in condensate gas reservoirs, the fluid interacts with the fractured-vuggy porous media, which makes the depletion process of condensate gas in pores, fractures or vugs different from that in PVT cylinder. In order to study the mechanism of this difference, three different experimental models were made to carry out the condensate gas depletion production experiment. The results showed that the existence of fracture-vuggy porous media would affect the depletion production process. The pores, fractures and vugs increased the dew point pressure from 26.2 MPa to 26.6 MPa and decreased the condensate oil recovery from 72.8% to 70.7%. When the fractures, vugs and pores are filled with powered fine sand of carbonate rocks, the dew point pressure reaches 27.4 MPa and the condensate oil recovery reduces to 68.4%. The fractured-vuggy porous media will aggravate the retro condensation phenomenon, promote the accumulation of heavy hydrocarbon components on the pore surface and precipitate in the form of condensate oil and hinder the recovery of condensate oil. This work explains the mechanism of the influence of fractured-vuggy porous media on the phase behavior of condensate gas. [ABSTRACT FROM AUTHOR]

In current land surface models or satellite remote sensing retrievals, clear‐sky surface albedo (α) is usually assumed to be symmetrical and relies only on the solar elevation angle (SEA). Based on 1‐min high‐resolution measurements of surface radiation fluxes, this study demonstrated that the diurnal variations of clear‐sky surface albedo exhibited a significant asymmetrical pattern in both summer and winter seasons over a semi‐arid grassland of the China's Loess Plateau. The results indicated that α values in the morning were generally larger than those in the afternoon at the same SEA, and diurnal asymmetry of surface albedo was distinctly prominent with SEA <40° in summer (before 9:30 a.m.) or SEA <20° in winter (before 10:00 am), and tended to diminish at midday. The averaged morning/afternoon albedo differences under sunny days were 0.05 (30.4%) and 0.09 (37.8%) in summer and winter seasons, respectively. Air relative humidity was positively correlated with the diurnal asymmetry of surface albedo, ascribed to probable formation of dew in the morning. Depression of the dew point was negatively linked to the morning/afternoon albedo differences, which was attributed to the strong scattering of incident sunlight by dewdrops could enhance the morning surface albedo. Such diurnal asymmetry of surface albedo should be included in the parameterization scheme of mesoscale and region‐scale climate models in the semi‐arid areas of China's Loess Plateau. [ABSTRACT FROM AUTHOR]

The widespread adoption of utility-based real-time applications has placed the necessity of widescale deployment of edge computing infrastructure. Crowdsourced edge computing is deemed a suitable way out. On the other hand, a collection of today's powerful smart mobile devices (SMDs) can cumulatively offer high-performance computing. The public-owned SMDs are utilized opportunistically to form a dynamic ad-hoc computing grid known as mobile crowd computing (MCC). This paper aspires to establish a proof-of-concept for the feasibility and use of MCC as a sustainable edge computing solution (MCC-edge). A typical smart HVAC system of an office building has been considered for the experiment case. We aim to process the HVAC data in real-time using the MCC-edge setup within the building for auto adjustment of the AC controller and error notifications. To maintain the ideal comfort level of the occupants, we present an extensive calculation using the dew point and heat index of the room. A high-level layered architecture of the MCC-edge for HVAC is presented along with a general framework of the MCC-edge. We report the module-wise design and implementation procedures with exhaustive details. The performance of MCC-edge is statistically compared with the commercial edge and cloud computing solutions in terms of cost, energy consumption, latency, and environmental impact, showing a significant advantage over the two. Every procedural detail of each module's design, development, and implementation is meticulously presented, which would aid interested readers and researchers in rebuilding such an application. [ABSTRACT FROM AUTHOR]

An electrochemical hydrogen compressor (EHC) system capable of producing dry compressed hydrogen up to 10 MPa has been developed in this study. The drying system, located downstream of the compressor, consists of a passive countercurrent membrane water exchanger which dries the produced hydrogen flow while simultaneously humidifying the low-pressure hydrogen fed to the compressor. This highly flexible drying system can achieve a dew point temperature of less than −30 °C. A dryer structured in this way avoids conventional drying methods such as temperature and pressure swing adsorption cycles, which are very demanding in terms of power and heat rejection. Four proton exchange membranes of different thicknesses were investigated in this study. Hydrogen flows at 10 MPa in the range 0.1–1 mg s−1 have been obtained using a single EHC. The best performance was obtained with the thinnest membrane, Gore 18 μm, which allowed reaching a current density of 4 A cm−2 at 0.4 V and 35 °C, with pumped hydrogen flows greater than 0.8 mg s−1. The efficiency achieved with this system was around 60% at low voltages and current densities, at pressures between 7.5 and 10 MPa. The efficiency was found to decrease with the pumped flow, but the flexibility of this compressor, with its wide range of flow rates and total absence of vibration, should be highlighted. [Display omitted] • An electrochemical compressor of hydrogen up to 10 MPa has been developed • Dry high-pressure hydrogen has been produced (dew point < - 30 °C) • A current density of 4 A cm−2 at 0.4 V and 35 °C has been achieved • Efficiencies of around 60% have been achieved [ABSTRACT FROM AUTHOR]

Extensive research has delved into the impact of environmental circumstances on the pacing and performance of professional marathon runners. However, the effects of environmental conditions on the pacing strategies employed by marathon participants in general remain relatively unexplored. This study aimed to examine the potential associations between various environmental factors, encompassing temperature, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and the pacing behavior of men and women. The retrospective analysis involved a comprehensive dataset comprising records from a total of 668,509 runners (520,521 men and 147,988 women) who participated in the 'Berlin Marathon' events between the years 1999 and 2019. Through correlations, Ordinary Least Squares (OLS) regression, and machine learning (ML) methods, we investigated the relationships between adjusted average temperature values, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and their impact on race times and paces. This analysis was conducted across distinct performance groups, segmented by 30-minute intervals, for race durations between 2 hours and 30 minutes to 6 hours. The results revealed a noteworthy negative correlation between rising temperatures and declining humidity throughout the day and the running speed of marathon participants in the 'Berlin Marathon.' This effect was more pronounced among men than women. The average pace for the full race showed positive correlations with temperature and minutes of sunshine for both men and women. However, it is important to note that the predictive capacity of our model, utilizing weather variables as predictors, was limited, accounting for only 10% of the variance in race pace. The susceptibility to temperature and humidity fluctuations exhibited a discernible increase as the marathon progressed. While weather conditions exerted discernible influences on running speeds and outcomes, they did not emerge as significant predictors of pacing. [ABSTRACT FROM AUTHOR]

The Model for Prediction Across Scales-Atmosphere (MPAS) was used to simulate meteorological conditions for a two-week winter episode during 10–23 January 2013, and a two-week summer episode during 18–31 July 2016, using both as a global model and a regional model with a focus on California. The results of both global and regional applications of MPAS were compared against the surface and upper air rawinsonde observations while the variations of characteristic meteorological variables and modeling errors were evaluated in space, time, and statistical sense. The results of the Advanced Weather Research and Forecast (WRF-ARW, hereafter WRF) model simulations for the same episodes were also used to evaluate the results of both applications of MPAS. The temporal analyses performed at surface stations indicate that both global and regional applications of MPAS and WRF model predict the diurnal evolution of characteristic meteorological parameters reasonably well in both winter and summer episodes studied here. The average diurnal bias in predicting 2 m temperature by MPAS and WRF are about the same with a maximum of 2 °C in winter and 1 °C in summer while that of 2 m mixing ratio is within 1 g/kg for all three modeling applications. The rawinsonde profiles of temperature, dew point temperature, and wind direction agree reasonably well with observations while wind speed is underestimated by all three applications. The comparisons of the spatial distribution of anomaly correlation and mean bias errors calculated from each model results for 2 m temperature, 2 m water vapor mixing ratio, 10 m wind speed and wind direction indicate that all three models have similar magnitudes of agreement with observations as well as errors away from observations throughout California. [ABSTRACT FROM AUTHOR]

Fengyun-4A (FY-4A) is the latest generation of China's geostationary satellite. The Advanced Geosynchronous Radiation Imager (AGRI) onboard FY-4A can provide high-precision, high-frequency observation data, which makes a new possibility for estimating the downwelling surface longwave radiation (DSLR) with high spatial and temporal resolution. This work presents a new method for estimating DSLRs under all-sky conditions using a genetic algorithm–artificial neural network (GA-ANN) algorithm based on brightness temperature (BT) from the FY-4A AGRI infrared channels and near-surface air temperature and dew point temperature from ERA5 reanalysis data. Based on the verification results of two independent observation sites, it is shown that the bias and RMSE are - 4.31 W/m2 and 35.28 W/m2, respectively. Compared the CERES SYN all-sky DSLR product with the DSLR estimated by the new method, the bias and RMSE are 0.86 W/m2 and 26.87 W/m2, respectively, and the new method has a higher spatial resolution (4 km), which can display more details of spatial variation. [ABSTRACT FROM AUTHOR]

Deep condensate gas reservoirs exhibit highly complex and variable phase behaviors, making it crucial to understand the relationship between fluid phase states and flow patterns. This study conducts a comprehensive analysis of the actual production process of the deep condensate gas well A1 in a certain oilfield in China. Combining phase behavior analysis and CMG software simulations, the study systematically investigates phase transitions, viscosity, and density changes in the gas and liquid phases under different pressure conditions, with a reservoir temperature of 165°C. The research covers three crucial depletion stages of the reservoir: single-phase flow, two-phase transition, and two-phase flow. The findings indicate that retrograde condensation occurs when the pressure falls below the dew point pressure, reaching maximum condensate liquid production at around 25 MPa. As pressure decreases, gas phase density and viscosity gradually decrease, while liquid phase density and viscosity show an increasing trend. In the initial single-phase flow stage, maintaining a consistent gas-oil ratio is observed when both bottom-hole and reservoir pressures are higher than the dew point pressure. However, a sudden drop in bottom-hole pressure below the dew point triggers the production of condensate oil, significantly reducing subsequent gas and oil production. In the transitional two-phase flow stage, as the bottom-hole pressure further decreases, the reservoir exhibits a complex flow regime with coexisting areas of gas and liquid. In the subsequent two-phase flow stage, when both bottom-hole and reservoir pressures are below the dew point pressure, a significant increase in the gas-oil ratio is observed. The reservoir manifests a two-phase flow regime, devoid of single-phase gas flow areas. For low-pressure conditions in deep condensate gas reservoirs, considerations include gas injection, gas lift, and cyclic gas injection and production in surrounding wells. Additionally, techniques such as hot nitrogen or CO2injection can be employed to mitigate retrograde condensation damage. The implications of this study are crucial for developing targeted development strategies and enhancing the overall development of deep condensate gas reservoirs. [ABSTRACT FROM AUTHOR]

The transportation of CO2 from the capture site to the storage location is a crucial phase in carbon capture, utilisation and storage (CCUS) process. For offshore operations, ship transportation is considered a viable alternative, and this would entail operations at low temperatures (down to 223.15 K). A review of the literature revealed that there is limited experimental data on CO2‐rich systems at low temperatures, thus, the need to investigate the phase behaviour of CO2‐rich systems at these conditions. This study validated and compared the accuracies of Peng–Robinson (PR) equation of state (EoS) with three different mixing rules (the classical with original and adjusted binary interaction parameters, the Wong–Sandler, and the Orbey–Wong–Sandler mixing rules) against the multi‐fluid helmholtz energy approximation (MFHEA ‐ with original and adjusted binary‐specific reducing parameters) EoS in the prediction of bubble points of CO2‐rich binary systems (CO2‐CH4, CO2–O2, CO2–Ar, and CO2–N2) for CCUS applications. The experimental studies used for the validation of the models were conducted at low temperatures (228.15–273.15 K with overall uncertainties of 0.14 K) and for five different CO2 mole ratios (99.5, 99, 98.5, 98 and 95% with overall uncertainties of 0.032%) using the constant composition expansion method. The overall uncertainty of the pressure measurements was 0.03 MPa. From the study, it was observed that there was a significant effect of binary interaction parameters (BIP) adjustment on the performance of PR‐EoS with classical mixing rule, especially for the CO2–N2 system. For all the systems, the predictions of PR‐EoS with the classical mixing rules and the adjusted BIPs were the most accurate in terms of the average absolute deviations from the experimental data. The model also predicted the literature data well in comparison with the other models (with less than 5% deviations for all the data points). Further analysis also proved that the model dew point predictions were in reasonable agreement with the available literature data at the considered conditions. As a result, the model could be adopted to fill the existing knowledge gaps of the studied systems at conditions (143.15–223.15 K) where experimental studies were not feasible. © 2024 The Author(s). Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Abstract: This study addresses the current difficulties in accurately controlling the indoor temperature of double-skin facades (DSFs), and its optimization, with a focus on the window opening angles of double-skin facades. The Spearman correlation coefficient method was used to select the main meteorological factors, including outdoor temperature, dew point temperature, scattered radiation, direct radiation, and window opening angle. A modified random forest algorithm was used to construct the optimization model and 80% of the data were used for model training. In the experiments, the average accuracy of the optimization model was as high as 93.5% for all window opening angles. This study provides a data-driven method for application to double-skin facades, which can effectively determine and control the window opening angles of double-skin facades to achieve energy saving and emission reduction, reduce indoor temperature, improve comfort, and provide a practical basis for decision-making. Future research will further explore the applicability and accuracy of the model under different climatic conditions. [ABSTRACT FROM AUTHOR]

In the conservation of cultural relics, the application of Paraloid B72 in humid environments frequently results in the surface whitening of artifacts, which impairs their appearance and conceals important details. This study investigates the mechanisms underlying this phenomenon by examining the effect of ambient humidity, Paraloid B72 mass concentration, solution addition volume, and solvent type. To evaluate the microstructure, transmittance, and composition of the films, a range of analytical techniques were employed, including optical microscopy, scanning electron microscopy, a UV-Visible Spectrophotometer, and Fourier transform infrared spectroscopy. The findings indicate that higher ambient humidity, lower Paraloid B72 mass concentration, smaller solution addition volume, and solvents with higher volatility and water miscibility increase water content during curing, intensifying the whitening effect. These factors modify the interaction between water and solvent, altering the surface structure of Paraloid B72. The whitening mechanism is linked to the cooling effect of solvent volatility, which lowers the dew point temperature at the air–solution interface, causing moisture condensation. Moisture forms droplets that leave irregular pores upon volatility, resulting in surface roughness, optical heterogeneity, and a reduced refractive index, resulting in whitening. This study provides a theoretical basis for understanding and preventing the whitening of Paraloid B72. [ABSTRACT FROM AUTHOR]

Predictive information on plant diseases could help to reduce and optimize the usage of pesticides in agriculture. This research presents classification procedures with linear discriminant analysis to predict three possible severity levels of net blotch in spring barley in Finland. The weather data utilized for classification included mathematical transformations, namely features of outdoor temperature and air humidity with calculated dew point temperature values. Historical field observations of net blotch density were utilized as a target class for the identification of classifiers. The performance of classifiers was analyzed in sliding data windows of two weeks with selected, cumulative, summed feature values. According to classification results from 36 yearly data sets, the prediction of net blotch occurrence in spring barley in Finland can be considered as a linearly separable classification task. Furthermore, this can be achieved with linear discriminant analysis by combining the output probabilities of separate binary classifiers identified for each severity level of net blotch disease. In this case, perfect classification with a resolution of three different net blotch severity levels was achieved during the first 50 days from the beginning of the growing season. This strongly suggests that real-time classification based on a few weather variables measured on a daily basis can be applied to estimate the severity of net blotch in advance. This allows application of the principles of integrated pest management (IPM) and usage of pesticides only when there is a proven need. [ABSTRACT FROM AUTHOR]

The water potential in drying soils, comprising both matric potential and osmotic potential components, can be measured using the dew point method (DPM). By combining DPM data with retention curve data acquired from techniques such as the suction plate method or the simplified evaporation method (SEM), it becomes possible to determine the soil water retention curve across the entire moisture spectrum. However, as the latter methods only determine the matric potential, the osmotic potential component in DPM data must either be negligible or known so that osmotic and matric potential components can be separated. This study aims to critically analyse common approaches for calculating the osmotic potential. To achieve this, we measured the water retention properties of a silt loam, a sandy loam and a sand across the entire moisture range by combining SEM and DPM. By using almost salt‐free soil material, we characterized reference water retention curves with negligible osmotic potential components. The impact of salt on water potential was analysed by conditioning soils with MgCl2 solutions of different concentrations, drying them, and measuring the water potential at different water contents using the DPM. The resulting water potentials were compared to the reference potentials and differences were interpreted as the osmotic potential component. The DPM‐measured water potentials in drying soils can be significantly affected by osmotic potential, especially at higher matric potentials (low suctions). Two models accounting for ideal and one model accounting for non‐ideal electrolyte behaviour were used to compare osmotic potential predictions with measurements. At low to medium salt concentrations, all models performed fairly well. At high concentrations, only the model accounting for non‐ideal behaviour predicted the osmotic potential satisfactorily, whereas at very high concentrations, all models underestimated the impact of osmotic potential on water potential. This suggests that the surface properties of the soil matrix, such as the specific surface area and surface charges, may lead to a decrease in osmotic potential beyond what is expected in pure solutions. [ABSTRACT FROM AUTHOR]

Baking is a healthier alternative to frying, since texture, color, smell, and flavor are developed, without adding oil. The objective was to estimate the moisture content in potato slices, during baking using Fick's law of diffusion to model internal moisture transport and to assess the impact on quality attributes. Moisture transport kinetics were examined at three baking temperatures of 120, 130, and 140°C. Fick's law was employed to estimate average moisture content using different methods: considering both a constant (method of slopes by subperiods, MSS; and method of successive approximations, MSA) and a variable (represented as a quadratic function of time, QFT) behavior of effective diffusivity (De). Three quality variables were analyzed: water activity (aw, dew point hygrometry), total color difference (∆E, colorimetry), and fracturability (F, universal testing machine). The diffusivity estimated with the time‐varying De method provided a more realistic description of moisture migration during baking. The aw, ∆E, and F for baked potato slices ranged from 0.234 to 0.276, 17.9 to 24.6, and 5.20 to 5.49 N, respectively. These attributes imply improved stability and extended shelf life, showing typical colors and texture changes for baked snacks. These changes are linked to variations in diffusivity, influenced by the size and quantity of micropores within the food structure. This study could allow an accurate prediction of mass transfer by considering variable De, facilitating the optimization of baking conditions. Practical Application: The analysis of the moisture content using Fick's law, considering a time‐varying diffusivity, enables the optimization of the baking process for foods. This helps minimize the occurrence of defective products. [ABSTRACT FROM AUTHOR]

A single-temperature-based dew-point generator (DPG), capable of producing air with dew point temperatures ranging from 25 °C to 60 °C, has been developed at SNSU-BSN Indonesia. The air flows through the saturator in a single pass and is controlled by a flow meter to have a maximum flow rate of 1 lpm. The air saturation process is carried out using a bubble aerator capable of producing bubbles ranging in size from below 0.5 mm to several mm in diameter. A heat sink, placed inside the saturator, is used to prevent water splashes from entering the gas outlet and to stabilize the dew point temperature. The impact of the saturator load is also modeled and simulated. The saturator is then placed into a thermostatic bath where heating of the gas outlet tube is performed starting from 5 cm below the water surface to prevent condensation due to environmental temperature influences. This developed saturator system is simple and low cost. The performance test includes a comparison with a high-precision dew-point hygrometer (DPH) and an evaluation of saturator efficiency. The accuracy of the generated dew point temperature is determined by referencing the reference value from the APMP.T-K8 comparison results. The test results are presented in graphical and tabular format along with an example uncertainty budget. [ABSTRACT FROM AUTHOR]

Accurately predicting flight delays remains a significant challenge in the aviation industry due to the complexity and interconnectivity of its operations. The traditional prediction methods often rely on meteorological conditions, such as temperature, humidity, and dew point, as well as flight-specific data like departure and arrival times. However, these predictors frequently fail to capture the nuanced dynamics that lead to delays. This paper introduces network centrality measures as novel predictors to enhance the binary classification of flight arrival delays. Additionally, it emphasizes the use of tree-based ensemble models, specifically random forest, gradient boosting, and CatBoost, which are recognized for their superior ability to model complex relationships compared to single classifiers. Empirical testing shows that incorporating centrality measures improves the models' average performance, with random forest being the most effective, achieving an accuracy rate of 86.2%, surpassing the baseline by 1.7%. [ABSTRACT FROM AUTHOR]

The radon concentration activity in buildings is influenced by various factors, including meteorological elements like temperature, pressure, and precipitation, which are recognized as significant influencers. The fluctuations of indoor radon in premises are related to seasonal change. This study aimed to understand better the effects of environmental parameters on indoor radon concentration levels in the Aksu school. Indoor and outdoor temperature differentials heavily influence diurnal indoor radon patterns. The analysis indicates that the correlation between indoor radon and outdoor temperature, dew point, and air humidity is weak and negligible for atmospheric pressure, wind speed, and precipitation, as determined by the obtained values of R2 and the Chaddock scale. The multiple regression model is characterized by the correlation coefficient rxy = 0.605, which corresponds to a close relationship on the Chaddock scale. [ABSTRACT FROM AUTHOR]

Traditional air conditioning systems use lot of energy; thus, dew point evaporative air-cooling systems could be a good alternative. Many experts studied the impact of constructional and operating characteristics on Maisotsenko cycle (M-cycle) to improve its performance. Cooler performance is influenced by the heat exchanger. Heat exchangers were constructed using flat and corrugated plates. The present study proposes the use of geometrically modified trapezoidal corrugated plates for counter flow heat exchanger, which consists of alternate air and water flow passageways. The numerical model is developed to predict the performance under variety of inlet air conditions and channel dimensions. In the standard range of incoming air properties such as relative humidity, the performance parameters assist in making cooler recommendations. Comparison and validation of simulation results are done with published experimental data for corrugated and trapezoidal corrugated plate heat exchangers. For trapezoidal corrugated plates, simulation findings revealed 10% increase in wet bulb efficiency and 7% increase in dew point efficiency over corrugated plates. The efficiency of wet bulb and dew point decreases as channel gap widens. For trapezoidal corrugated plates, the larger channel spacing minimises pressure drop. [ABSTRACT FROM AUTHOR]

Two new cold plates manufactured via metal 3D printing were experimentally investigated for thermal performance analysis in indirect liquid cooling operations; then they were compared to the traditional cold plates. Experiments were performed with different coolant inlet temperatures (15.7 °C and 24.5 °C) and ambient air velocities (0.5 m/s and 3 m/s) at tropical conditions; hereby, the impact of high dew point temperatures at tropics was also investigated. Body-centered cubic (BCC) and pillar elements were applied in the cooling cavity of the cold plates. The results showed that the target surface temperature in both BCC- and pillar-filled plate designs was maintained below the limits at the lower inlet temperature. However, at the higher inlet temperature, the temperature was only maintained below the limit when the ambient air velocity was 3 m/s. The convective heat transfer coefficient at the inlet temperature of 15.7 °C was found 1.5 and 2.5 times higher than the convective heat transfer coefficient value at the inlet temperature of 24.5 °C for the pillar- and BCC-filled plates, respectively. The performance evaluation criterion values were found in the range of 1.2 − 2.4, which depended on the operating conditions and were already higher than the referenced studies in the literature. [ABSTRACT FROM AUTHOR]

Residential homes and apartments' cooling and heating needs account for 63% of total building energy consumption. Improvements in the properties of building envelopes are among the best ways to reduce their energy consumption. The project's general objective was to compare the performance of externally insulated and traditional envelopes of light wooden frame buildings at full scale. Two houses were constructed and equipped with relative humidity sensors and temperature probes to assess the physical properties of the building envelope. The first house was built according to the conventional method (insulation between the studs), and the second house was built according to the method with the insulation outside the wall (also known as the perfect wall). The results showed that external insulation effectively mitigates internal condensation risks by relocating dew points to the exterior surface, thereby enhancing structural durability and thermal stability. Thermographic imaging confirmed reduced thermal bridging and improved thermal performance in the externally insulated walls. Overall, this study supports, with a full-scale experiment, the adoption of external insulation as a viable strategy for enhancing energy efficiency, thermal comfort, and durability in residential buildings. [ABSTRACT FROM AUTHOR]

• Analyzed the impact of WD, WS, and temperature levels on O 3 concentration. • High performance CNN model was established for O 3 prediction based on monitoring data. • Meteorological disturbance are achieved to eliminate by variable control in O 3 prediction. • Explored the effects of individual variables and multifactorial coupling on O 3 formation. • The I R N O 2 were calculated under different meteorological conditions. Severe ground-level ozone (O 3) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution characteristics of ground-level O 3 and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021. Then, a high-performance convolutional neural network (CNN) model was established by expanding the moment and the concentration variations to general factors. Finally, the response mechanism of O 3 to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables. The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern. When the wind direction (WD) ranges from east to southwest and the wind speed (WS) ranges between 2 and 3 m/sec, higher O 3 concentration prone to occur. At different temperatures (T), the O 3 concentration showed a trend of first increasing and subsequently decreasing with increasing NO 2 concentration, peaks at the NO 2 concentration around 0.02 mg/m3. The sensitivity of NO 2 to O 3 formation is not easily affected by temperature, barometric pressure and dew point temperature. Additionally, there is a minimum I R N O 2 at each temperature when the NO 2 concentration is 0.03 mg/m3, and this minimum I R N O 2 decreases with increasing temperature. The study explores the response mechanism of O 3 with the change of driving variables, which can provide a scientific foundation and methodological support for the targeted management of O 3 pollution. [Display omitted] [ABSTRACT FROM AUTHOR]

Atmospheric Water Generation assumes substantial significance as an innovative remedy for addressing water scarcity and augmenting water resilience. This technology facilitates water extraction directly from the atmosphere, presenting a sustainable and decentralized approach to water supply. The investigation into the feasibility of attaining the dew point temperature for a heatsink operating in the climatic conditions of Basra was conducted using Fluent 22.1 software. The minimum dew point temperature under extreme conditions was determined to be 10.52℃. A thermoelectric device was a primary component in cooling the moisture-laden air to produce water from atmospheric air. Simulations were executed using two complementary and two integrated heatsinks under turbulent airflow conditions ranging from 4 to 20 m/s. The results indicated an inverse relationship between heat distribution within the heatsink and fluid flow velocity, emphasizing the crucial role of airflow passage arrangement in the condensation process. Enhancing the heatsink's surface area and reducing airflow quantity proved effective in achieving the dew point temperature. The lowest temperature attained was 9.2℃, featuring intersecting heat exchangers with a flow velocity of 4 m/s. The result indicated that altering the flow pattern affects the condensation process's surface temperature by as much as 38%, while the rise in pressure difference can reach 20%. Under the same operational conditions, the difference in thermal conductivity between two distinct heat exchanger configurations, attributed to pressure variations, is notably 8%. The study concludes that the Qurna region benefits from favorable weather conditions, encompassing temperature and relative humidity, thereby enabling water generation from atmospheric air, notwithstanding the consideration of the dew point temperature as a limiting factor.

In this study, concentrations of three different air pollutants (PM10, SO2, and NO2) were obtained from four air quality monitoring stations (AQMSs) over an 11-year period from 2013 to 2023. Meteorological variables (temperature, dew point temperature, wind speed, sea level pressure, and precipitation) were then obtained from the nearest European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) grid point to each station, and their relationships were analyzed. Homogeneity and normality tests were conducted for air pollutant concentrations and meteorological variables, followed by data preprocessing analyses using non-parametric tests. The ultimate aim of this study is to determine the effects of the presence and intensity of precipitation on pollutant concentrations. Analyses based on four different precipitation intensity categories (light, moderate, heavy, and severe) indicated that increasing precipitation intensity is associated with decreasing pollutant concentrations. Specifically, higher precipitation intensities were associated with a reduction in pollutant levels, with reductions ranging from 15% to 35% compared to dry conditions. This effect was particularly pronounced during the winter season, when PM10 concentrations decreased by up to 45% on wet days compared to dry days. This finding highlighted the importance of not only precipitation intensity but also the type of hydrometeor for air pollution. The significant decrease observed during winter is thought to be due to snowfall, which is believed to have a greater removal effect on air pollution compared to rain. [ABSTRACT FROM AUTHOR]

This paper optimizes a variable-frequency dehumidification system (VFDS) based on the principle of vapor compression refrigeration (VCR), wherein the compressor frequency and fan speed can be changed. The effect of the compressor frequency and fan speed on the operating parameters of the VFDS, including the evaporating temperature (Te), condensing temperature (Tc), superheating (ΔTsh), and subcooling (ΔTsc), is studied experimentally under three operating conditions. The effect of variable-frequency on the dehumidification performance is analyzed at the mechanistic level through two dehumidification performance indicators, namely, the dehumidification capacity (DC) and dehumidification energy efficiency (DEE). ΔTsh is primarily controlled by the capillary throttling effect, which always starts to cross the “0” point when the fan speed is 600 rpm under different conditions. An increase in the compressor frequency leads to the opposite trend for DC and DEE, but their corresponding optimal fan speeds are relatively close. At 27 °C/60%, the optimal fan speed intervals with DC and DEE as single optimization objectives are both [600 rpm, 700 rpm]. However, at 30 °C/80%, the overall difference between the optimal fan speed intervals with DC and DEE as optimization objectives is 50–100 rpm. Importantly, the risk of frost at 18.3 °C/60% can lead to a significant extension of the optimal fan speed interval, which is [500 rpm, 900 rpm], making it more difficult to control. The concept of the dehumidification operating temperature difference (ΔT) is proposed to comprehensively evaluate the dehumidification capacity and as a control index for variable frequencies. The relationships among the optimal ΔT and the ambient dew point temperature (Td) and compressor frequency are established through response surface methodology (RSM) with a maximum deviation of 5.97%. This work can provide an optimized variable-frequency solution for the VFDS and some guidance for the control logic development of the VFDS. [ABSTRACT FROM AUTHOR]

Site-specific weather forecasts are essential for accurate prediction of power demand and are consequently of great interest to energy operators. However, weather forecasts from current numerical weather prediction (NWP) models lack the fine-scale detail to capture all important characteristics of localised real-world sites. Instead, they provide weather information representing a rectangular gridbox (usually kilometres in size). Even after post-processing and bias correction, area-averaged information is usually not optimal for specific sites. Prior work on site-optimised forecasts has focused on linear methods, weighted consensus averaging, and time-series methods, among others. Recent developments in machine learning (ML) have prompted increasing interest in applying ML as a novel approach towards this problem. In this study, we investigate the feasibility of optimising forecasts at sites by adopting the popular machine learning model "gradient boosted decision tree", supported by the XGBoost package (v.1.7.3) in the Python language. Regression trees have been trained with historical NWP and site observations as training data, aimed at predicting temperature and dew point at multiple site locations across Australia. We developed a working ML framework, named "Multi-SiteBoost", and initial test results show a significant improvement compared with gridded values from bias-corrected NWP models. The improvement from XGBoost (0.1–0.6 °C, 4–27% improvement in temperature) is found to be comparable with non-ML methods reported in the literature. With the insights provided by SHapley Additive exPlanations (SHAP), this study also tests various approaches to understand the ML predictions and increase the reliability of the forecasts generated by ML. [ABSTRACT FROM AUTHOR]

This study examines mesoscale convective systems (MCSs) in relation to 1‐min automatic weather station data for 2 years over the city of Yaounde. The focus is on characterising the atmospheric variability associated with MCS activity while distinguishing the days with and without MCS activities. This paper aims to determine the diurnal cycles of occurrence frequencies and percentages of rainfall, relative humidity, dew point temperature, solar radiation, temperature, and wind speed for days with and without MCSs. There are more than 623 MCS events during the study period (over 150 events per rainy season). The link between MCS activity and regional‐scale circulation and atmospheric instability is investigated. The diurnal cycle of the number of MCSs shows a maximum in the afternoon (around 1,600–2,200 LT), a morning minimum (around 0700–1,300 LT), and substantial activity during the night. Surface relative humidity is 5% lower on non‐MCS days, surface dew point 2% higher on MCS days between 0700 and 1800 hr, and solar radiation higher on MCS days between 0500 and 1000 hr. The percentage of rainfall associated with MCSs can exceed 60% on an annual scale and up to 80% on a seasonal scale. MCS activity is associated with instability in the lower troposphere, and this convective instability is maximal during the peak of the MCS activity. [ABSTRACT FROM AUTHOR]

A corrosion inhibitor composite was developed for carbon dioxide corrosion and it was adapted to the requirements of dosage, protective capacity, temperature characteristics, and compatibility with other reagents. The development process and the main requirements, observance of which was monitored, are described stage-by-stage. The outcome of the conducted research was two grades of a carbon dioxide corrosion inhibitor based on an imidazoline derivative. The difference between the developed composites lies in the solvent type and, correspondingly, in the temperature characteristics (flash and dew points). The influence of the amount of the active base on the effectiveness of the composite was evaluated and the optimum content of the components in the corrosion inhibitor was found. The importance of flash and dew points for corrosion inhibitors is underscored and a way of controlling these composite indicators is proposed. [ABSTRACT FROM AUTHOR]

A mathematical model and a program for calculating heat exchange in a flow of combustion products cooled below the dew point in a condensation heat exchanger, in a gas exhaust pipe with a clamp lining have been created. Analytical dependences are presented making it possible to determine the temperature of the exhaust gases, as well as temperature fields and thermal stresses in the wall of the gas exhaust pipe depending on the proportion of bypassed uncooled gases, thermophysical characteristics of the materials of the pipe wall and combustion products, geometric parameters of the pipe, and the intensity of the impact of environment on it. Calculations of the processes of heat exchange of gases moving in a reinforced concrete chimney were carried out for the case of its protection from hydrate corrosion by the bypass method. It has been established that for a three-layer reinforced concrete chimney with a height of 180 m, the quantity of bypassed gases is 30–35% of the total amount of gases. If there is a condensing heat-utilization unit in the boiler plant, the temperature difference in the gas exhaust pipe, its free thermal deformation and thermal stresses in the structural elements of the pipe are reduced by 2.12–2.99 times, which increases the reliability of the pipe. [ABSTRACT FROM AUTHOR]

Drinking water is scarce in many regions of the world despite the omnipresence of water in the form of vapour in large quantities in the atmosphere. Currently, majority of water harvesters use vapour compression refrigeration cycle, which is inefficient. Thus, to reduce electrical energy consumption, the idea proposed in this study is to use a sorption-based atmospheric water generator (AWG) which works on low-grade heat energy. The key component of the proposed AWG is a desiccant-coated fin tube heat exchanger (DCFTHX) which humidifies and heats the air to such an extent that the vapour present in the air can be condensed by simply bringing it in thermal contact with a surface at atmospheric temperature. Thermodynamic modelling of the proposed AWG is first presented, followed by a systematic study under various weather conditions ranging from temperatures of 6 °C to 40 °C and specific humidity from 0.004 to 0.22 kg kg d.a.−1. Results indicate that water can be produced even for specific humidity of 4 kg kg d.a.−1 (near zero dew point temperature) if the ambient temperature is low (10 °C), at regeneration temperatures of 60 and 70 °C. The highest rate of water extraction and the highest yield is 10.9 g s−1 and 62.2 kg kWh−1, respectively, under ambient conditions of 26 °C and 0.02 kg kg d.a.−1. Under the winter (when the absolute humidity is at its lowest) weather conditions of Dubai, as much as 39.3 kg of water can be produced per kWh, which translates to only 0.59 cents per kg water produced. [ABSTRACT FROM AUTHOR]

The study introduces the Ant Lion Recurrent Climate Estimation (ALRCE) model for precise climate forecasting, emphasizing critical parameters like rainfall, humidity, temperature, wind speed, and dew point. Its primary goal is to mitigate natural hazard risks stemming from sudden climate shifts. Data from Surat city, Gujarat, including these features, is meticulously processed to train the ALRCE model. It employs an ant lion fitness function for analysis, particularly predicting rainfall and drought rates. Implemented in MATLAB, it demonstrates superior precision, accuracy, and risk reduction, validated for future climatic predictions from 2025 to 2050. Comparative analysis with existing techniques shows ALRCE outperforms, achieving 96.5% accuracy, 98% precision, 0.18838 RMSE, and 0.63 correlation coefficient. The study enhances accuracy by 2% post-optimization, highlighting ALRCE's potential to significantly improve climate prediction and mitigate risks associated with abrupt climate changes. [ABSTRACT FROM AUTHOR]

Typically, fruit cracking in sweet cherry is associated with the occurrence of free water at the fruit surface level due to direct (rain and fog) and indirect (cold exposure and dew) mechanisms. Recent advances in close range remote sensing have enabled the monitoring of the temperature distribution with high spatial resolution based on light detection and ranging (LiDAR) and thermal imaging. The fusion of LiDAR-derived geometric 3D point clouds and merged thermal data provides spatially resolved temperature data at the fruit level as LiDAR 4D point clouds. This paper aimed to investigate the thermal behavior of sweet cherry canopies using this new method with emphasis on the surface temperature of fruit around the dew point. Sweet cherry trees were stored in a cold chamber (6 °C) and subsequently scanned at different time intervals at room temperature. A total of 62 sweet cherry LiDAR 4D point clouds were identified. The estimated temperature distribution was validated by means of manual reference readings (n = 40), where average R 2 values of 0.70 and 0.94 were found for ideal and real scenarios, respectively. The canopy density was estimated using the ratio of the number of LiDAR points of fruit related to the canopy. The occurrence of wetness on the surface of sweet cherry was visually assessed and compared to an estimated dew point ( Y d e w ) index. At mean Y d e w of 1.17, no wetness was observed on the fruit surface. The canopy density ratio had a marginal impact on the thermal kinetics and the occurrence of wetness on the surface of sweet cherry in the slender spindle tree architecture. The modelling of fruit surface wetness based on estimated fruit temperature distribution can support ecophysiological studies on tree architectures considering resilience against climate change and in studies on physiological disorders of fruit. [ABSTRACT FROM AUTHOR]

Background/Aim: Chronic obstructive pulmonary disease (COPD) is a major public health concern, affecting over 200 million people worldwide in 2019. The prevalence of COPD has risen by 40% from 1990 to 2010 and continued to increase by 13% from 2010 to 2019, causing over 3 million deaths globally in 2019, ranking it as the third leading cause of death. This study explored how daily weather changes relate to the number of COPD-related emergency department (ED) visits. Materials and Methods: We collected data on daily COPD-related ED visits in 2017 in Pécs along with corresponding meteorological data to analyze this connection. Results: High diurnal temperature range (DTR) and day-to-day variability in dew point were linked to a 4.5% increased risk of more COPD-related ED visits. Notably, DTR had a stronger impact on males, contributing to a 6.3% increase, while dew point variability significantly affected males with an odds ratio (OR) of 1.083. (OR=1.083). Stratifying by age revealed heightened risks for those aged 30-39 (43.5% increase) and 50-59 (7.6% increase). Females aged 30-39 and 50-59 faced elevated risks of 42.7% and 9.1%, respectively, whereas males aged 60-69 showed a 9.8% increase. Conclusion: Our findings highlight the influence of weather variations on COPDrelated ED visits, with nuanced effects based on age and sex. [ABSTRACT FROM AUTHOR]

Vegetation is an important link between land, atmosphere, and water, making its changes of great significance. However, existing research has predominantly focused on long-term vegetation changes, neglecting the intra-annual variations of vegetation. Hence, this study is based on the Enhanced Vegetation Index (EVI) data from 2000 to 2022, with a time step of 16 days, to analyze the intra-annual patterns of vegetation changes in China. The average intra-annual EVI values for each municipal-level administrative region were calculated, and the time-series k-means clustering algorithm was employed to divide these regions, exploring the spatial variations in China's intra-annual vegetation changes. Finally, the ridge regression and random forest methods were utilized to assess the drivers of intra-annual vegetation changes. The results showed that: (1) China's vegetation status exhibits a notable intra-annual variation pattern of "high in summer and low in winter," and the changes are more pronounced in the northern regions than in the southern regions; (2) the intra-annual vegetation changes exhibit remarkable regional disparities, and China can be optimally clustered into four distinct clusters, which align well with China's temperature and precipitation zones; and (3) the intra-annual vegetation changes demonstrate significant correlations with meteorological factors such as dew point temperature, precipitation, maximum temperature, and sea-level pressure. In conclusion, our study reveals the characteristics, spatial patterns and driving forces of intra-annual vegetation changes in China, which contribute to explaining ecosystem response mechanisms, providing valuable insights for ecological research and the formulation of ecological conservation and management strategies. [ABSTRACT FROM AUTHOR]

Copyright of Corrosion & Protection in Petrochemical Industry is the property of Corrosion & Protection in Petrochemical Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A novel still design is proposed that employs a composite desiccant to adsorb atmospheric water vapor. The still has a pyramid design with two short windows and two large glass surfaces. The still is designed to be partially buried 15 centimeters into the ground for passive cooling of the condensing glass surfaces to improve condensation efficiency. An experimental setup is developed with a mud platform to study the performance of the still. A pyramid-shaped still of dimension 30cm x 30cm x 45cm (LxWxH) is fitted with thermocouples, humidity sensors, and a pyranometer to record the global irradiance. The data for two days, one with a buried still and the other unburied, of similar irradiance, are recorded from 6 am to 6 pm with a beaker containing water placed at the stage in the still. The results indicate a drop in glass temperature of about 10.42% in the buried setup compared to the unburied structure. This also resulted in the dew point being maintained for only 35% of the time in the unburied still compared to the buried still. [ABSTRACT FROM AUTHOR]

The hot‐dip galvanizing behavior of an advanced high‐strength steel DP980 is investigated, focusing on selective oxidation and reactive wetting, as compared with interstitial‐free (IF) steel. The steels are annealed with varying dew points of −50, −25, and 0 °C, and then immersed in a galvannealing bath containing 0.13 wt% dissolved Al. The results show that higher concentrations of Mn and Si elements in DP980 steel result in an increase of nonwettable Mn2SiO4/MnSiO3. The increase in dew point does not promote the internal oxidation of alloying elements in DP980 as in IF steel, and DP980 displays the lowest external oxidation at −50 °C. After galvanizing, Mn and Si oxides are observed above the inhibition layer, which is due to the oxide cracking caused by the mismatch of thermal expansion coefficient between the surface oxides and the steel, and then the oxide flaking and incorporation are caused by the interfacial infiltration through cracks and the formation of intermetallic crystals of Fe–Al and subsequent Fe–Zn. Therefore, IF steel maintains good wetting in the presence of external oxides, while DP980 steel exhibits more external film oxides and poor coating quality at high dew points. [ABSTRACT FROM AUTHOR]

At an energy flux imbalance of about 1 W m−2, the ocean stores 90% of the heat accumulating by global warming. However, neither the causes of this nor the responsible geophysical processes are sufficiently well understood. More detailed investigations of the different phenomena contributing to the oceanic energy balance are warranted. Here, the role of low-level marine clouds in the air–sea interaction is analysed. TEOS-10, the International Thermodynamic Equation of State of Seawater—2010, is exploited for a rigorous thermodynamic description of the climatic trends in the lifted condensation level (LCL) of the marine troposphere. Rising sea surface temperature (SST) at a constant relative humidity (RH) is elevating marine clouds, cooling the cloud base, and reducing downward thermal radiation. This LCL feedback effect is negative and counteracts ocean warming. At the current global mean SST of about 292 K, the net radiative heat flux from the ocean surface to the LCL cloud base is estimated to be 24 W m−2. Per degree of SST increase, this net flux is expected to be enhanced by almost 0.5 W m−2. The climatic LCL feedback effect is relevant for the ocean's energy balance and may be rigorously thermodynamically modelled in terms of TEOS-10 equations. LCL height may serve as a remotely measured, sensitive estimate for the sea surface's relative fugacity, or conventional relative humidity. [ABSTRACT FROM AUTHOR]

The necessity of understanding and simulating hydrological phenomena as well as their interactions and the effect of anthropogenic and climate conditions on the ecosystem have encouraged researchers for years to investigate the moisture transfer in soil. Considering the moisture transfer as an isothermal phenomenon might cause a wrong estimation due to the non-isothermal nature of the moisture movement in porous media. Hygrothermal (coupled heat and moisture transfer) models are quite diverse and are the engine of the various hygrothermal software tools used to analyze the heat and moisture in building envelopes, drying technologies, and many other applications. This paper is a literature survey conducted to provide an overview on the classical hygrothermal models to address the historical perspectives on these models. First, it investigated, from a historical point of view, the challenges behind the development of hygrothermal models as unsaturated flow theories, beginning with Buckingham theory. The non-isothermal nature of moisture was the starting point for researchers to deal with new challenges during mathematical modeling and experimental analysis. In general, the theory of coupled heat and moisture transfer first developed by J.R. Philip and De Vries and the authors in the mid-1950s inspired the novel hygrothermal models, including Sophocleous and Milly's model, Rode's model, Künzel's model, and Grunewal's model. In a parallel of hygrothermal model developments, the models of Whitaker and Luikov can also be classified as hygrothermal models; they were mostly applied in modeling the phenomenon of drying. The study highlights the application of hygrothermal models in building physics and gathered a summary of international efforts such as Annex 24, Annex 41, and the HAMSTAD project and advancements performed from the classical dew point or steady-state Glaser method. Moreover, this study emphasizes the advantages of the standard of EN 15026 and limitations of the Glaser method. To sum up, hygrothermal models are still under development based on various assumptions of moisture driving potentials and transfer coefficients. [ABSTRACT FROM AUTHOR]

In this research, modeling and estimation of dew point temperature values ​​in eight meteorological stations located in the eastern regions of Iran were done. These stations, including Bam, Birjand, Iranshahr, Kerman, Mashhad, Tabas, Zabol and Zahan, are all characterized by a dry climate. First, the correlation of different weather parameters with dew point temperature was investigated and then the parameters of mean temperature, maximum temperature and minimum temperature were selected as the parameters with the highest correlation to dew point temperature. These selected parameters then incorporated into a VAR (Vector Autoregression) model as inputs for estimating dew point temperature values. This modeling approach allows us to capture the interdependencies between these variables and enhance our accuracy in predicting dew point temperature. Then the stability of the residual series of the VAR model was investigated and the residual series of this model was developed using the generalized ARCH model. The result of the development of the VAR model was the investigation of the dew point temperature in eight meteorological stations with the VAR-GARCH model. The results indicated that this combined model outperformed VAR model in both the train and test phases. Specifically, the VAR-GARCH model demonstrated higher accuracy and improved results compared to solely using a VAR model. The incorporation of GARCH allowed better modeling of the residual series, leading to an overall increase in accuracy ranging from 5% to 30% during the test phase. These findings suggest that considering both autoregressive dynamics and conditional heteroskedasticity is crucial for accurately predicting dew point temperatures. By incorporating GARCH into our modeling approach, we were able to capture additional information about volatility and further enhance our predictions.

[Display omitted] Atmospheric water harvesting (AWH) is a promising solution to the water shortage problem. Current sorption-based AWH (SAWH) systems seldom obtain both wide climatic adaptability and high energy efficiency due to the lack of thermodynamic optimization. To achieve the ideal harvesting circulation in SAWH systems, the "optimal harvesting window" (OHW) design based on thermodynamic analysis was first proposed and validated by our prototype. The "OHW" theory indicates the water production rate and energy efficiency could be improved by properly reducing the adsorption temperature. As the humidity increases, the optimal adsorption temperature should be closer to the dew point of the environment. Experimental results revealed that, loaded with 3 kg widely adopted silica gel, the daily water production could reach 5.76–17.64 L/d with ultrahigh energy efficiency of 0.46–1.5 L/kWh. This prototype could also achieve optimal performance in wide climatic conditions in terms of 13–35 °C and 18%–72% RH. Lastly, the performance of photovoltaic (PV)-driven SAWH was evaluated. Results showed that a 1 m2 PV panel could generate 0.66–2 L water per day in Shanghai throughout the year, the highest in opening literature. Notably, this work introduces a promising concept that can help achieve large-scale, ultra-fast, energy-efficient AWH worldwide. [ABSTRACT FROM AUTHOR]

A multi-input–multi-output artificial neuron network (MIMO-ANN) model has been developed for process monitoring and improvement on a natural gas glycol dehydration process. The MIMO-ANN model was based on a steady-state process simulation model constructed in commercial software Aspen HYSYS. A set of training data was generated with the converged simulation model for the training of the MIMO-ANN model in Python. The process input of the model includes lean glycol recirculation rate and purity along with wet gas inlet pressure. On the other hand, the process output considered includes dehydrated gas water and aromatics content, dehydrated gas hydrate formation temperature and water dew point, stripping gas flow rate as well as reboiler duty. The overall mean squared error (MSE) of the MIMO-ANN model was calculated as 1.79. The best-fit line that highly overlaps with a 45° diagonal line is constructed with a correlation coefficient (R2) score of more than 0.999 for all studied process output testing datasets. The mean absolute percentage error (MAPE) of the predicted outputs is generally less than 1%, except for dehydrated gas water dew point (16.63%) and stripping gas flow rate (11.55%), due to error predictions attempted on pseudo-zero values. This successfully displays an exceptional predictive performance of the MIMO-ANN model developed in this work which can be further deployed as an online dashboard for real-time monitoring tool. [ABSTRACT FROM AUTHOR]

A natural gas (NG) dehydration unit based on glycol absorption is considered one of the most important gas processing units, aiming to decrease water content and consequently adjust its dew point. However, during this process, not only water is absorbed by the glycol solvent, but also some aromatic compounds, including benzene, toluene, ethylbenzene, and xylene (BTEX), in addition to volatile organic compounds (VOC), are absorbed. These compounds are released during glycol regeneration into the atmosphere, resulting in environmental pollution and consequent catastrophic mental and physical health problems. This study aims to minimize BTEX emissions while ensuring efficient dew point control. Various strategies have been adopted to control BTEX emissions, but the present work focuses on optimizing operating conditions and investigating the influence of operational variables on BTEX emissions, as well as NG water content. LINGO optimization software and HYSYS (version 11) are used to find the plant's optimum conditions for minimizing BTEX emissions and satisfying efficient dew point control. Simulation results show that stripping gas, triethylene glycol (TEG) circulation rate, and inlet feed gas temperature significantly affect BTEX emissions. The proposed optimum operating conditions in this work resulted in a reduction in BTEX emissions by about 81% while satisfying the required NG dew point. Furthermore, two quadratic equations are developed based on regression analysis for efficient calculation of the BTEX emissions and water dew point at any operational variables. [ABSTRACT FROM AUTHOR]