Humidity Vapor Research Articles

Bioinspired on-off switchable multi-level responsiveness for ultralong fire-warning, super-sensitive solvent/humidity and light-driven behaviors

The prospects of endowing the omnipresent hazardous substances with sensitive, safe, and stable life-like behaviors poses significant for the development of on–off switchable smart materials. Herewith, based on material-structural synergistic design, a multi-level responsiveness smart structures (VBGO) inspired by phospholipid biomolecules is self-assembled through asymmetric swelling and smart supramolecular nano-structures. Due to the outstanding sensitive of fire-warning nano-hybrid of functionalized cyclodextrin-graphene and highly stable substrate of vermiculite, the designed VBGO exhibits the high-sensitively fire alarm time (only 0.17 s) and super-along sustained fire alarm time (up to 249 s). Moreover, the VBGO displays significant increment in thermal stability and film-forming properties. Besides, given the asymmetrical and self-assembled smart structures, the VBGO exhibits the unique fast responses in their surrounding environments like fire, heat, light, humidity, and solvent vapor. Additionally, the on–off switchable mechanisms of fire-warning responsiveness, solvent-/humidity-/light-driven, shape memory and environmental awareness are presented systematically. This work introduces a sensitive, safe, and stable approach to designing multi-level responsive smart materials by modifying fire-warning bioinspired structures.

The Variation in Atmospheric Turbidity over a Tropical Site in Nigeria and Its Relation to Climate Drivers

Atmospheric turbidity exhibits substantial spatial–temporal variability due to factors such as aerosol emissions, seasonal changes, meteorology, and air mass transport. Investigating atmospheric turbidity is crucial for climatology, meteorology, and atmospheric pollution. This study investigates the variation in atmospheric turbidity over a tropical location in Nigeria, utilizing the Ångström exponent (α), the turbidity coefficient (β), the Linke turbidity factor (TL), the Ångström turbidity coefficient (βEST), the Unsworth–Monteith turbidity coefficient (KAUM), and the Schüepp turbidity coefficient (SCH). These parameters were estimated from a six-month uninterrupted aerosol optical depth dataset (January–June 2016) and a one-year dataset (January–December 2016) of solar radiation and meteorological data. An inverse correlation (R = −0.77) was obtained between α and β, which indicates different turbidity regimes based on particle size. TL and βEST exhibit pronounced seasonality, with higher turbidity during the dry season (TL = 9.62 and βEST = 0.60) compared to the rainy season (TL = 0.48 and βEST = 0.20) from May to October. Backward trajectories and wind patterns reveal that high-turbidity months align with north-easterly air flows from the Sahara Desert, transporting dust aerosols, while low-turbidity months coincide with humid maritime air masses originating from the Gulf of Guinea. Meteorological drivers like relative humidity and water vapor pressure are linked to turbidity levels, with an inverse exponential relationship observed between normalized turbidity coefficients and normalized water vapor pressure. This analysis provides insights into how air mass origin, wind patterns, and local climate factors impact atmospheric haze, particle characteristics, and solar attenuation variability in a tropical location across seasons. The findings can contribute to environmental studies and assist in modelling interactions between climate, weather, and atmospheric optical properties in the region.

Wind Profile Retrieval Based on LSTM Algorithm and Mobile Observation of Brightness Temperature over the Tibetan Plateau

Stationary or mobile microwave radiometers (MRs) can measure atmospheric temperature, relative humidity, and water vapor density profiles with high spatio-temporal resolution, but cannot obtain the vertical variations of wind field. Based on a dataset of brightness temperatures (TBs) measured with a mobile MR over the Three-River-Source Region of the Tibetan Plateau from 18 to 30 July 2021, we develop a direct retrieval method for the wind profile (WP) based on the Long Short-Term Memory (LSTM) network technique, and obtain the reliable dynamic variation characteristics of the WP in the region. Furthermore, the ground-based radiative transfer model for TOVS (RTTOV-gb) was employed to validate the reliability of the TB observation, and we analyzed the impact of weather conditions, altitude, observational mode, and TB diurnal variation on the accuracy of the TB measurement and the retrieval of the WP. Results show that the TB from the mobile observation (MOTB) on clear and cloudy days are close to those of the simulated TB with the RTTOV-gb model, while TB measurements on rainy days are far larger than the modeled TBs. When compared with radiosonde observations, the WPs retrieved with the LSTM algorithm are better than the ERA5 reanalysis data, especially below 350 hPa, where the root mean square errors for both wind speed and wind direction are smaller than those of ERA5. The major factors influencing WP retrieval include the weather conditions, altitude, observational mode, and TB diurnal variation. Under clear-sky and cloudy conditions, the LSTM retrieval method can reproduce the spatio-temporal evolution of wind field and vertical wind shear characteristics. The findings of this study help to improve our understanding of meso-scale atmospheric dynamic structures, characteristics of vertical wind shear, atmospheric boundary layer turbulence, and enhance the assessment and forecasting accuracy of wind energy resources.

Identification of Convective Boundary Layer Depth over the Great Lakes Region Using Aircraft Observations: A Comparison of Various Methods

Abstract This study evaluates the methods of identifying the height zi of the top of the convective boundary layer (CBL) during winter (December and January) over the Great Lakes and nearby land areas using observations taken by the University of Wyoming King Air research aircraft during the Lake-Induced Convection Experiment (1997/98) and Ontario Winter Lake-effect Systems (2013/14) field campaigns. Since CBLs facilitate vertical mixing near the surface, the most direct measurement of zi is that above which the vertical velocity turbulent fluctuations are weak or absent. Thus, we use zi from the turbulence method as the “reference value” to which zi from other methods, based on bulk Richardson number (Rib), liquid water content, and vertical gradients of potential temperature, relative humidity, and water vapor mixing ratio, are compared. The potential temperature gradient method using a threshold value of 0.015 K m−1 for soundings over land and 0.011 K m−1 for soundings over lake provided the estimates of zi that are most consistent with the turbulence method. The Rib threshold-based method, commonly used in numerical simulation studies, underestimated zi. Analyzing the methods’ performance on the averaging window zavg we recommend using zavg = 20 or 50 m for zi estimations for lake-effect boundary layers. The present dataset consists of both cloudy and cloud-free boundary layers, some having decoupled boundary layers above the inversion top. Because cases of decoupled boundary layers appear to be formed by nearby synoptic storms, we recommend use of the more general term, elevated mixed layers. Significance Statement The depth zi of the convective atmospheric boundary layer (CBL) strongly influences precipitation rates during lake-effect snowstorms (LES). However, various zi approximation methods produce significantly different results. This study utilizes extensive concurrently collected observations by project aircraft during two LES field studies [Lake-Induced Convection Experiment (Lake-ICE) and OWLeS] to assess how zi from common estimation methods compare with “reference” zi derived from turbulent fluctuations, a direct measure of CBL mixing. For soundings taken both over land and lake; with cloudy or cloud-free conditions, potential temperature gradient (PTG) methods provided the best agreement with the reference zi. A method commonly employed in numerical simulations performed relatively poorly. Interestingly, the PTG method worked equally well for “coupled” and elevated decoupled CBLs, commonly associated with nearby cyclones.

Experimental investigation on the self-ignition behavior of dangerous dust accumulations

A process known as spontaneous combustion is brought on by the gradual oxidation of flammable organic particles and takes place when air passes over a mass of dust. Combustible powders react with air oxygen in a process known as oxidation, which produces carbon dioxide, carbon oxide, water, and other gases whose contents depend on the temperature at which the oxidation occurs. Combustible dusts can self-ignite depending on their chemical makeup, the characteristics of their constituent components, the particle size and mass geometry, and last but not least, the ambient temperature. Self-ignition is a complicated process that occurs in three subsequent or concurrent stages of development, namely self-heating, humidity evaporation, and self-ignition. Self-ignition is a complicated process that occurs in three separate or concurrent stages of development, namely self-heating, humidity evaporation and self-ignition, all of which interact with one another. Even at normal temperatures, the molecules on the surface of combustible dust particles are prone to exothermic interactions with oxygen in the air conveyed in the free volume between particles, which is the cause of self-heating (or possibly self-ignition). The temperature of the reactive-air dust system will then rise as a result of any heat emitted, hastening the reactivity of other dust molecules with oxygen. By using drying tests at constant temperatures, this work aims to demonstrate the self-ignition behavior of flammable dusts by volume.

Sap flow of two typical woody halophyte species responding to the meteorological and irrigation water conditions in Taklimakan Desert

Understanding plant water consumption is crucial for artificial afforestation under drought environments and water stress in desert regions. However, the water consumption characteristics of desert species responding to the irrigation regimes are often neglected. By conducting a field test in the Taklimakan Desert Highway shelterbelt, this study examines the sap flow traits of two typical woody halophyte species (Calligonum mongolicum and Haloxylon ammodendron) and how they react to weather conditions and watering practices. Under the same irrigation treatment, the stem flux of C. mongolicum on sunny days was 1.5–5.3 times that on dusty days, while the stem flux of H. ammodendron on sunny days was 3.5–5.5 times that on dusty days. Both species demonstrated some sap flow during the night, representing 14.3%–24.9% and 7.3%–10.4% of the total sap flow for C. mongolicum and H. ammodendron, respectively. H. ammodendron maintained a higher stem flow during daytime and was more drought resistant than C. mongolicum. The daily sap flow patterns of these two species varied, showing both ‘single’ and ‘double peak’ curves depending on the watering conditions. A delay was also observed between the sap flow of these two species and the environmental factors. The factors influencing plant sap flow were found to be in the order of solar radiation, temperature, relative humidity, and saturated water vapor pressure difference. A BP-neural network proved highly effective for accurately simulating the sap flow of these two species. This research provides insights into how two common desert tree species adapt their water use in response to drought conditions, which is vital for artificial forest creation in desert areas.

Climate Impact on Irrigation Water Use in Jiangsu Province, China: An Analysis Using Empirical Mode Decomposition (EMD)

In this paper, the quantitative effects of climatic factor changes on irrigation water use were analyzed in Jiangsu Province from 2004 to 2020 using the Empirical Mode Decomposition (EMD) time-series analysis method. In general, the irrigation water use, precipitation (P), air temperature (T), wind speed (Ws), relative humidity (Rh) and water vapor pressure (Vp) annual means ± standard deviation were 25.44 ± 1.28 billion m3, 1034.4 ± 156.6 mm, 16.1 ± 0.4 °C, 2.7 ± 0.2 m·s−1, 74 ± 2%, and 15.5 ± 0.6 hPa, respectively. The analysis results of the irrigation water use sequence using EMD indicate three main change frequencies for irrigation water use. The first major change frequency (MCF1) was a 2-to-3-year period varied over a ±1.00 billion m3 range and showed a strong correlation with precipitation (the Pearson correlation was 0.68, p < 0.05). The second major change frequency (MCF2) was varied over a ±2.00 billion m3 range throughout 10 years. The third major change frequency (MCF3) was a strong correlation with air temperature, wind speed, relative humidity, and water vapor pressure (the Pearson correlations were 0.56, 0.75, 0.71, and 0.69, respectively, p < 0.05). In other words, MCF1 and MCF3 represent the irrigation water use changes influenced by climate factors. Furthermore, we developed the Climate–Irrigation–Water Model based on farmland irrigation theory to accurately assess the direct effects of climate factor changes on irrigation water use. The model effectively simulated irrigation water use changes with a root mean square error (RMSE) of 0.06 billion m3, representing 2.24% of the total. The findings from the model indicate that climate factors have an average impact of 6.40 billion m3 on irrigation water use, accounting for 25.14% of the total. Specifically, precipitation accounted for 3.04 billion m3 of the impact, while the combined impact of other climatic factors was 3.36 billion m3.

Fundamentals of Monitoring Condensation and Frost/Ice Formation in Cold Environments Using Thin-Film Surface-Acoustic-Wave Technology.

Moisture condensation, fogging, and frost or ice formation on structural surfaces cause severe hazards in many industrial components such as aircraft wings, electric power lines, and wind-turbine blades. Surface-acoustic-wave (SAW) technology, which is based on generating and monitoring acoustic waves propagating along structural surfaces, is one of the most promising techniques for monitoring, predicting, and also eliminating these hazards occurring on these surfaces in a cold environment. Monitoring condensation and frost/ice formation using SAW devices is challenging in practical scenarios including sleet, snow, cold rain, strong wind, and low pressure, and such a detection in various ambient conditions can be complex and requires consideration of various key influencing factors. Herein, the influences of various individual factors such as temperature, humidity, and water vapor pressure, as well as combined or multienvironmental dynamic factors, are investigated, all of which lead to either adsorption of water molecules, condensation, and/or frost/ice in a cold environment on the SAW devices. The influences of these parameters on the frequency shifts of the resonant SAW devices are systematically analyzed. Complemented with experimental studies and data from the literature, relationships among the frequency shifts and changes of temperature and other key factors influencing the dynamic phase transitions of water vapor on SAW devices are investigated to provide important guidance for icing detection and monitoring.

Multi-level anti-counterfeiting and X-ray imaging based on luminescence of Cs–Cu–I perovskite

Cesium copper iodine perovskite is widely studied for applications in X-ray imaging and anti-counterfeiting fields based on its excellent photovoltaic properties. Uniquely, Cs3Cu2I5 undergoes a reversible phase transition to CsCu2I3 when induced by humidity, a phenomenon that is utilized in fluorescent anti-counterfeiting application. However, there is no relevant proof for the phase transition of CsCu2I3 upon humidity, which leads to an incomplete explanation of the water-induced phase transition of Cs3Cu2I5. Here, we illustrate the water-induced phase transition events of Cs3Cu2I5 and CsCu2I3 crystals that were made utilizing a straightforward anti-solvent approach. Interestingly, Cs3Cu2I5 can undergo a reversible phase transition based on humidity exposure and removal, whereas CsCu2I3 undergoes immediate phase decomposition and fluorescence burst upon humidity exposure, and recrystallization to low-formation-energy Cs3Cu2I5 is accompanied by fluorescence recurrence after humidity evaporation. Furthermore, Cs3Cu2I5 and CsCu2I3 crystals exhibit a fascinating X-ray light yield and a high spatial resolution of 16.6 and 12.5 lp mm−1, respectively. As a result, this research adds to our understanding of the phase transition between Cs3Cu2I5 and CsCu2I3 and also provides new candidates for advanced fluorescence anti-counterfeiting techniques and X-ray imaging scintillators.

An Effective Resistive-Type Alcohol Vapor Sensor Using One-Step Facile Nanoporous Anodic Alumina.

With the increases in work environment regulations restricting alcohol to 1000 ppm, and in drink-driving laws, testing for alcohol with a simple method is a crucial issue. Conventional alcohol sensors based on sulfide, metal oxide, boron nitride or graphene oxide have a detection limit in the range of 50-1000 ppm but have disadvantages of complicated manufacture and longer processing times. A recent portable alcohol meter based on semiconductor material using conductivity or chemistry measurements still has the problem of a complex and lengthy manufacturing process. In this paper, a simple and effective resistive-type alcohol vapor sensor using one-step anodic aluminum oxide (AAO) is proposed. The nanoporous AAO was produced in one-step by anodizing low-purity AA1050 at room temperature of 25 °C, which overcame the traditional high-cost and lengthy process at low temperature of anodization and etching from high-purity aluminum. The highly specific surface area of AAO has benefits for good sensing performance, especially as a humidity or alcohol vapor sensor. With the resistance measurement method, alcohol vapor concentration of 0, 100, 300, 500, 700 and 1000 ppm correspond to mean resistances of 8524 Ω, 8672 Ω, 9121 Ω, 9568 Ω, 10,243 Ω, and 11,045 Ω, respectively, in a linear relationship. Compared with other materials for detecting alcohol vapor, the AAO resistive sensor has advantages of fast and simple manufacturing with good detection limits for practical applications. The resistive-type alcohol vapor-sensing mechanism is described with respect to the resistivity of the test substance and the pore morphology of AAO. In a human breath test, the AAO sensor can quickly distinguish whether the subject is drinking, with normal breath response of -30% to -40% and -20% to -30% response after drinking 50 mL of wine of 25% alcohol.

Cu-loaded MOF-303 for iodine adsorption: The roles of Cu species and pyrazole ligands

The capture of toxic radioiodine is an increasingly important priority for the safe development of nuclear energy. Copper is a promising alternative for expensive silver to capture iodine. To develop novel copper-based adsorbents and determine the effect of copper species on iodine adsorption, the metal–organic framework with dual-pyrazole ligands (MOF-303) is employed as the scaffold to bind Cu2+ species. Cu0 nanoparticles were formed after the reduction by NaBH4. The obtained Cu2+-MOF-303 and Cu0-MOF-303 show high iodine uptake capacities at 353 K, 747 mg·g−1 and 837 mg·g−1, respectively. They also show high iodine uptake capacities of more than 300 mg·g−1 at a high temperature (423 K), which are better than other Cu-based adsorbents. Besides, the loading of Cu can enhance the iodine selectivity under humid vapor, and iodine adsorption rate in iodine-cyclohexane solutions. The Cu0 on Cu0-MOF-303 can react with iodine directly via the redox mechanism. For Cu2+-MOF-303, the adjacent pyrazole ligands can chelate with Cu2+ ions strongly and transfer charges to trapped iodine to form polyiodide anions, and thus stable CuI species could also be generated. The strategy of anchoring Cu species using MOF-303 provides large channels for iodine diffusion, and highly-dispersed Cu and N sites for iodine capture.

Solvent-induced fabrication of Cu/MnOx nanosheets with abundant oxygen vacancies for efficient and long-lasting photothermal catalytic degradation of humid toluene vapor

Construction of highly-active photothermal catalysts featuring merits of high quantum efficiency and superior heat resistance is a great challenge during volatile organic compounds (VOCs) degradation under high humidity. Herein, a facile solvent-induced dimensionality reduction strategy was proposed to engineer a nanosheeted and polycrystalline Cu/Mn-based catalyst (M-Cu/MnOx) having interfacial oxygen vacancies for enhanced photo-thermal catalytic degradation of toluene under highly humid conditions. Unique Cu-mediated δ-MnO2/Mn3O4 nanosheets with high surface area exhibited excellent light absorptivity and photogenerated carrier separation efficiency, as well as superior light-driven thermogenesis. It realized ultra-high (92.8%) toluene conversion and deep mineralization (84.4%) under RH = 80% and continuous catalytic reaction (200 h). Its toluene degradation rate exhibited 3.5–71.9 times higher than reported state-of-the-art photothermal catalysts. The newly designed M-Cu/MnOx catalyst provides a promising, low-cost and alternative for the efficient degradation of toluene and other similar VOCs under humid conditions on large-scale operations.

The Potential Benefits of Handling Mixture Statistics via a Bi-Gaussian EnKF: Tests With All-Sky Satellite Infrared Radiances.

The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., some members are clear while others are cloudy), that column's ensemble statistics will contain a mixture of clear and cloudy statistics. Such mixtures are inconsistent with the ensemble data assimilation algorithms currently used in numerical weather prediction. Hence, ensemble data assimilation algorithms that can handle such mixtures can potentially outperform currently used algorithms. In this study, we demonstrate the potential benefits of addressing such mixtures through a bi-Gaussian extension of the ensemble Kalman filter (BGEnKF). The BGEnKF is compared against the commonly used ensemble Kalman filter (EnKF) using perfect model observing system simulated experiments (OSSEs) with a realistic weather model (the Weather Research and Forecast model). Synthetic all-sky infrared radiance observations are assimilated in this study. In these OSSEs, the BGEnKF outperforms the EnKF in terms of the horizontal wind components, temperature, specific humidity, and simulated upper tropospheric water vapor channel infrared brightness temperatures. This study is one of the first to demonstrate the potential of a Gaussian mixture model EnKF with a realistic weather model. Our results thus motivate future research toward improving numerical Earth system predictions though explicitly handling mixture statistics.

Net Primary Productivity Estimation Using a Modified MOD17A3 Model in the Three-River Headwaters Region

Remote sensing (RS) models can easily estimate the net primary productivity (NPP) on a large scale. The majority of RS models try to couple the effects of temperature, water, stand age, and CO2 concentration to attenuate the maximum light use efficiency (LUE) in the NPP models. The water effect is considered the most unpredictable, significant, and challenging. Because the stomata of alpine plants are less sensitive to limiting water vapor loss, the typically employed atmospheric moisture deficit or canopy water content may be less sensitive in signaling water stress on plant photosynthesis. This study introduces a soil moisture (SM) content index and an alpine vegetation photosynthesis model (AVPM) to quantify the RS NPP for the alpine ecosystem over the Three-River Headwaters (TRH) region. The SM content index was based on the minimum relative humidity and maximum vapor pressure deficit during the noon, and the AVPM model was based on the framework of a moderate resolution imaging spectroradiometer NPP (MOD17) model. A case study was conducted in the TRH region, covering an area of approximately 36.3 × 104 km2. The results demonstrated that the AVPM NPP greatly outperformed the MOD17 and had superior accuracy. Compared with the MOD17, the average bias of the AVPM was −9.8 gCm−2yr−1, which was reduced by 91.8%. The average mean absolute percent error was 57.0%, which was reduced by 68.2%. The average Pearson’s correlation coefficient was 0.4809, which was improved by 30.0%. The improvements in the NPP estimation were mainly attributed to the decreasing estimation of the water stress coefficient on the NPP, which was considered the higher constraint of water impact on plant photosynthesis. Therefore, the AVPM model is more accurate in estimating the NPP for the alpine ecosystem. This is of great significance for accurately assessing the vegetation growth of alpine ecosystems across the entire Qinghai–Tibet Plateau in the context of grassland degradation and black soil beach management.

A conditional copula model to identify the response of runoff probability to climatic factors

Understanding the response of runoff to climate drivers is important to ensure rational water allocation and address the risk of drought. Many models that assess the effect of climate factors on the response of runoff volume have been developed and widely used. However, models that assess the response of the probability of runoff occurrence (runoff probability) are lacking. In this study, we developed a model by integrating a conditional probability distribution (CPD) and a copula function model to assess the effect of climate conditions on variation of the probability of runoff occurrence. The developed model was applied to the basin of Poyang Lake, the largest freshwater lake in China. The study showed that Frank copula was the copula that had the best-fitted effect to identify the impact of climate factors (except for precipitation and air temperature [AT] in low flow period [LFP]) on the probability of runoff occurrence. The copulas with the best-fitted effect of precipitation and AT is the Gumbel copula and Clayton copula during LFP, respectively. Precipitation, relative humidity (RH), and water vapor pressure (WP) were positive with streamflow variation, while wind speed (WS), potential evapotranspiration (ET0), and sunshine duration (SD) were negative with runoff, but AT had an inverse relation with the streamflow during high flow period (HFP) and LFP. Sensitivity analysis indicated that precipitation has a weaker effect on the likelihood of extreme hydrological events than many other climate factors (such as RH and SD). Moreover, the sensitivity of runoff probability to climatic factors tended to be relatively stable during HFP, which was in contrast to that during LFP. This research highlights the significance of considering change conditions when evaluating runoff response to climate drivers, which is consistent with the objective of achieving more accurate runoff predictions to combat climate change and extreme weather conditions.

Swelling induced debonding of thin hydrogel films grafted on silicon substrates.

We report on the delamination of thin (≈μm) hydrogel films grafted to silicon substrates under the action of swelling stresses. Poly(dimetylacrylamide) (PDMA) films are synthesized by simultaneously cross-linking and grafting preformed polymer chains onto the silicon substrate using a thiol-ene reaction. The grafting density at the film/substrate interface is tuned by varying the surface density of reactive thiol-silane groups on the silicon substrate. Delamination of the films from well controlled line defects with low adhesion is monitored under a humid water vapor flow ensuring full saturation of the polymer network. A propagating delamination of the film is observed under the action of differential swelling stresses at the debonding front. A threshold thickness for the onset of this delamination is evidenced which is increasing with grafting density while the debonding velocity is also observed to decrease with an increase in grafting density. These observations are discussed within the framework of a nonlinear fracture mechanics model which assumes that the driving force for crack propagation is the difference between the swelling state of the bonded and delaminated parts of the film. Using this model, the threshold energy for crack initiation was determined from the measured threshold thickness and discussed in relation to the surface density of reactive thiol groups on the substrate.

Localized urban canopy model and improved anthropogenic heat parameters in the weather research and forecasting model: Simulation of a warm-sector heavy rainfall event over the pearl river delta urban agglomeration

Warm-sector heavy rainfall in South China is a frequent type of precipitation in summer in the Pearl River Delta region. The complexity of the mechanisms involved in the triggering of convection, especially the effects of urbanization, has greatly increased the uncertainty of numerical simulations of warm-sector heavy rainfall. In this study, five new surface parameters with five new anthropogenic heat (AH) parameters were constructed and coupled with the urban canopy model (UCM) of the Weather Research and Forecasting model, version 4.1, based on the local climate zone system over the Pearl River Delta Urban Agglomeration (PRDUA). Taking a typical warm-sector heavy rainfall process that occurred in the PRDUA on 20 April 2019 as an example, five groups of experiments involving different schemes were compared and analyzed, revealing that the precipitation simulated using the localized UCM with the new AH parameters was the best (closest to observations). The localized UCM successfully simulated the increase in 2 m temperature and sensible heat flux and the resultant thermal forcing in urban areas, which promoted the convergence of low-level southerly winds with water vapor and the lifting of the lower-layer warm and humid water vapor to the upper layers in the urban center, leading to a significant increase of precipitation. The improved AH parameters enhanced the anthropogenic heat and its vertical conduction in urban areas, but contributed only marginally to the convergence of 10 m winds. Compared with observations from wind profile radar, it was found that the localized UCM enhanced the accuracy of the simulated horizontal wind field convergence at upper and lower levels, while the improved AH parameters enhanced the accuracy of the simulated low-level jet intensity and vertical movement, which are important drivers for the spatial variation in warm-sector heavy rainfall over the PRDUA. The current findings will be helpful for improving the model skill in simulating warm-sector heavy rainfall over high-density urban areas, as well as enhancing understanding of the impact mechanism of urbanization on the occurrence and development of warm-sector heavy rainfall.

Negative corona discharge and flow characteristics of a two-stage needle-to-ring configuration ionic wind pump for temperature and relative humidity

Ionic wind pumps have the advantages of a compact structure, no moving parts, and low power consumption. The effects of temperature and humidity on the current–voltage and flow characteristics of ionic wind pumps are still unclear. This study experimentally investigates the effects of temperature and humidity on the breakdown voltage, discharge current, and velocity of a two-stage needle-to-ring type ionic wind pump with a negative corona discharge. It is found that the coupling effects of temperature, humidity, and water vapor condensation determine the current–voltage and flow characteristics of ionic wind pumps. The temperature and vapor condensation effects can enhance the discharge current and outlet velocity and weaken the breakdown voltage. However, the humidity effect can weaken the discharge current and outlet velocity, and improve the breakdown voltage. Moreover, there exists a competition between humidity and vapor condensation effects on breakdown voltage, current, and velocity. The increase in temperature intensifies the humidity effect and weakens the condensation effect; thus, the temperature changes the contribution of humidity and condensation effects in the competition. A working spectrum of ionic wind is provided in the temperature and humidity coupling environment, including a vapor condensation-controlled zone, a sensitive humidity zone for breakdown voltage and velocity, and an insensitive humidity zone for breakdown voltage and velocity. The spectrum can provide theoretical guidance for designing ionic wind pumps at different temperatures and humidity.

Numerical Modeling of the Radio Wave Over-the-Horizon Propagation in the Troposphere

Using atmospheric data, which include pressure, temperature, relative humidity and water vapor pressure, the actual refractive index of a specific segment of the atmosphere has been modeled. Based on the refractive index, a numerical method is presented to quickly estimate the propagation path of the radio wave in the troposphere. Utilizing the terrain and the surface medium model of the propagation area and the parabolic equation (PE) method, an image of the electric field distribution of radio waves in the troposphere is obtained. A comparison of propagation paths between the numerical method and the PE model is presented. Additionally, the effects of the antenna’s elevation angle have been studied. Physical measurements provide a reference for the accuracy of the simulation results obtained using the method presented in this work.

Microclimatic Evaluation of Five Types of Colombian Greenhouses Using Geostatistical Techniques.

In Colombia, the second-largest exporter of cut flowers worldwide and one of the South American countries with the largest area of crops under cover, passive or naturally ventilated greenhouses predominate. Locally, there are several types of greenhouses that differ in architecture, size, height, shape of roof and ventilation surfaces, of which many characteristics of the microclimate generated in their interior environment are unknown. This generates productive limitations that in some way may be limiting the yield, quality and health of the final products harvested; in addition, Colombian producers do not have the ability to monitor the microclimate of their farms, much less to correlate microclimate data with data on crop production and yield. Therefore, there is a need for the Colombian grower to know the most relevant microclimate characteristics generated in the main greenhouses used locally. The objective of this work was to carry out a microclimatic characterization of the five most used types of greenhouses in Colombia. The main results allowed determining that in these structures, there are conditions of high humidity and low vapor pressure for several hours of the day, which affects the physiological processes of growth and development of the plants. It was also identified that for each type of greenhouse, depending on the level of radiation, there is a significant microclimatic heterogeneity that may be the cause of the heterogeneity in plant growth, which is a common characteristic observed by the technical cultivation personnel. Therefore, it can be concluded that it is urgent to propose microclimatic optimization strategies to help ensure the sustainability of the most important production systems in the country.