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The paper discusses changes in the low-flow regime of rivers in Poland, resulting from climate change that occurred between 1987 and 1989. The low-flow variability of rivers was measured with the use of the number of days with low flows (NDLF) below a threshold value, which was adopted as the 0.1 (10%) percentile (Q10) from the set of daily flows recorded in the multi-annual period 1951–2020 at 140 water gauges on 83 rivers. The analysis of the course of climate change over Poland showed that it was caused by macro-circulation conditions, controlled by changes in the intensity of thermohaline circulation in the North Atlantic (NA THC). Climate change consisted of a sharp increase in sunshine duration and air temperature, and a decrease in relative humidity after 1988. Along with the lack of changes in precipitation totals, characterized by a strong yearly variability, and an increase in field evaporation, it led to noticeable changes in the water balance. As a result, in 1989–2020, there was a significant increase in NDFL detected in about 2/3 of the area of Poland. With the change in the NA THC phase and the macro-circulation conditions, there was also a change in the spatial distribution of areas drained by rivers with increased NDFL. In 1951–1988, these included the eastern parts of Poland, while after the climate change (1989–2020), its western and south-western parts. [ABSTRACT FROM AUTHOR]

Surface air temperature is a critical element in the surface–atmosphere interaction, energy exchange, and water cycle. Multi-source fusion reanalysis products (hereafter referred to as reanalysis) have spatiotemporal continuity and broad applicability that can provide key data support for various studies such as glacier melting, soil freeze-thaw and desertification, ecosystem, and climate change in the alpine region of the Qinghai–Tibet Plateau (QTP). Surface air temperature observations collected at 17 weather stations in the High-cold region Observation and Research Network for Land Surface Process and Environment of China (HORN) over the period of 2017–2018 are implemented to evaluate the advanced and widely used surface air temperature reanalysis datasets, which include the European Centre for Medium-Range Weather Forecasts (ECMWF) Fifth Generation Land Surface Reanalysis (ERA5L), the U.S. Global Land Data Assimilation System (GLDAS), and China Meteorological Administration Land Data Assimilation System (CLDAS). Results are as follows: (1) Evaluation results of temporal changes and spatial distribution characteristics indicate that the three reanalysis datasets are consistent with in-situ observations in the alpine region of the QTP. CLDAS is more consistent with observations and can better describe details of temperature distribution and variation than ERA5L and GLDAS. (2) For the evaluation period, CLDAS is 0.53 °C higher than the in-situ observation, while ERA5L and GLDAS are lower than the in-situ observation by −3.45 °C and −1.40 °C, respectively. (3) The accuracy of CLDAS is better than ERA5L and GLDAS under different elevations and land covers. We resampled three reanalysis datasets with a spatial resolution of 0.25° and used the two most common interpolation methods to analyze the impact of spatial resolution and different interpolation methods on the evaluation results. We found that the impact is small. In summary, the three reanalysis datasets all have certain applicability in the alpine region of the QTP, and the accuracy of CLDAS is significantly higher than ERA5L and GLDAS. The results of the present paper have important implications for the selection of reanalysis data in the studies of climate, ecosystem, and sustainable development in the QTP. [ABSTRACT FROM AUTHOR]

Olive oil is considered to be a food of utmost importance, especially in the Mediterranean countries. The quality of olive oil must remain stable regarding authenticity and storage. This review paper emphasizes the detection of olive oil oxidation status or rancidity, the analytical techniques that are usually used, as well as the application and significance of chemometrics in the research of olive oil. The first part presents the effect of the oxidation of olive oil during storage. Then, lipid stability measurements are described in parallel with instrumentation and different analytical techniques that are used for this particular purpose. The next part presents some research publications that combine chemometrics and the study of lipid changes due to storage published in 2005–2021. Parameters such as exposure to light, air and various temperatures as well as different packaging materials were investigated to test olive oil stability during storage. The benefits of each chemometric method are provided as well as the overall significance of combining analytical techniques and chemometrics. Furthermore, the last part reflects on fraud in olive oil, and the most popular analytical techniques in the authenticity field are stated to highlight the importance of the authenticity of olive oil. [ABSTRACT FROM AUTHOR]

Due to global warming and urbanization, high-temperature events—which frequently occur in cities—are presenting an increasing threat to the daily lives of human beings. In coastal cities, sea breezes can cool the near surface and improve the urban environment to some extent. Understanding the cooling characteristics of sea breeze on the urban environment is informative for improving and mitigating the urban heat island (UHI) effect. In this paper, we analyze the basic characteristics of the timing of the cooling effect of sea breeze in urban summer based on the long-term multi-point measurements of air temperatures. Additionally, the Weather Research and Forecasting (WRF) model is used to show the influence of sea breeze on cities in terms of the cooling action time. The whole process is reproduced based on a time distribution map created using the results of the WRF simulation. The measured temperature and WRF simulation results are also evaluated with observations. The results show little difference between the two. The analysis of the distribution map shows that the sea breeze gradually penetrates inland from coastal areas. It can therefore be concluded that the sea breeze blows at different speeds in different areas. Our results show that the sea breeze is weak in places near the coast, while it is significantly stronger around inland rivers. Moreover, in urban areas that are far from inland rivers, the speed of the sea breeze is evenly distributed in space. The spatial pattern of sea breeze retreat time and arrival time is reversed: retreats happen earlier in inland areas. The duration of the sea breeze shows a significantly decreasing trend from the coast to inland, with the longest duration at the southern end of the urban area near the coast. [ABSTRACT FROM AUTHOR]

This paper aims to better understand why there was a global warming pause in 2000–2015 and why the global mean surface temperature (GMST) has risen again in recent years. We present and statistically analyze substantial time-series observed datasets of global lower-stratospheric temperature (GLST), troposphere–stratosphere temperature climatology, global land surface air temperature, GMST, sea ice extent (SIE) and snow cover extent (SCE), combined with modeled calculations of GLSTs and GMSTs. The observed and analyzed results show that GLST/SCE has stabilized since the mid-1990s with no significant change over the past two and a half decades. Upper-stratospheric warming at high latitudes has been observed and GMST or global land surface air temperature has reached a plateau since the mid-2000s with the removal of natural effects. In marked contrast, continued drastic warmings at the coasts of polar regions (particularly Russia and Alaska) are observed and well explained by the sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free quantum-physics warming model of halogenated greenhouse gases (GHGs) show excellent agreement with the observed GMSTs after the natural El Niño southern oscillation and volcanic effects are removed. These results have provided strong evidence for the dominant warming mechanism of anthropogenic halogenated GHGs. The results also call for closer scrutiny of the assumptions made in current climate models. [ABSTRACT FROM AUTHOR]

In this paper, for the first time, simultaneous atmospheric temperature perturbation profiles obtained from the TIMED/SABER satellite and equatorial ion density and vertical plasma drift velocity observations with and without ESF activity obtained from the C/NOFS satellite are used to investigate the effect of gravity waves (GW) on ESF. The horizontal and vertical wavelengths of ionospheric oscillations and GWs are estimated by applying wavelet analysis techniques. In addition, vertically propagating GWs that dissipate energy in the ionosphere-thermosphere system are investigated using the spectral analysis technique. We find that the vertical wavelength of GW, corresponding to dominant wavelet power, ranges from 12 to 31 km regardless of the conditions of the ionosphere; however, GWs with vertical wavelengths between about 1 to 13 km are found every day, saturated between 90 and 110 km at different longitudinal sectors. Filtering out vertical wavelengths above 13 km from temperature perturbations, ranges of zonal wavelengths of GW (i.e., from about 290 to 950 km) are found corresponding to irregular and non-irregular ionosphere. Similarly, corresponding to dominant oscillations, the zonal wavelength of ion density perturbations is found within 16 to 1520 km. Moreover, we find an excellent agreement among the median zonal wavelengths of GW for the cases of irregular and non-irregular ionosphere and ion density perturbations that are 518, 495, and 491 km, respectively. The results imply that seed perturbations due to GW with a vertical wavelength from about 1 to 13 km evolve to ion density irregularity and may be amplified due to post-sunset vertical upward drift velocity. [ABSTRACT FROM AUTHOR]

In this work, the design of a microfluidic paper-based analytical device (μPAD) for the quantification of nitrate in urine samples was described. Nitrate monitoring is highly relevant due to its association to some diseases and health conditions. The nitrate determination was achieved by combining the selectivity of the nitrate reductase enzymatic reaction with the colorimetric detection of nitrite by the well-known Griess reagent. For the optimization of the nitrate determination μPAD, several variables associated with the design and construction of the device were studied. Furthermore, the interference of the urine matrix was evaluated, and stability studies were performed, under different conditions. The developed μPAD enabled us to obtain a limit of detection of 0.04 mM, a limit of quantification of 0.14 mM and a dynamic concentration range of 0.14–1.0 mM. The designed μPAD proved to be stable for 24 h when stored at room temperature in air or vacuum atmosphere, and 60 days when stored in vacuum at −20 °C. The accuracy of the nitrate μPAD measurements was confirmed by analyzing four certified samples (prepared in synthetic urine) and performing recovery studies using urine samples. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

A key element for reducing energy consumption and improving thermal comfort on high-speed rail is controlling air-conditioning temperature. Accurate prediction of air supply temperature is aimed at improving control effects. Existing studies of supply air temperature prediction models are interdisciplinary, involving heat transfer science and computer science, where the problem is defined as time-series prediction. However, the model is widely accepted as a complex model that is nonlinear and dynamic. That makes it difficult for existing statistical and deep learning methods, e.g., autoregressive integrated moving average model (ARIMA), convolutional neural network (CNN), and long short-term memory network (LSTM), to fully capture the interaction between these variables and provide accurate prediction results. Recent studies have shown the potential of the Transformer to increase the prediction capacity. This paper offers an improved temporal fusion transformers (TFT) prediction model for supply air temperature in high-speed train carriages to tackle these challenges, with two improvements: (i) Double-convolutional residual encoder structure based on dilated causal convolution; (ii) Spatio-temporal double-gated structure based on Gated Linear Units. Moreover, this study designs a loss function suitable for general long sequence time-series forecast tasks for temperature forecasting. Empirical simulations using a high-speed rail air-conditioning operation dataset at a specific location in China show that the temperature prediction of the two units using the improved TFT model improves the MAPE by 21.70% and 11.73%, respectively the original model. Furthermore, experiments demonstrate that the model effectively outperforms seven popular methods on time series computing tasks, and the attention of the prediction problem in the time dimension is analyzed. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify the trends of changes in atmospheric precipitation percolation under the changing climate conditions of Lithuania (the East Baltic region) based on long-term lysimeter studies. Data from 1987–2022 research (n = 1296) was used to determine trends in precipitation infiltration changes. Two 10-year periods, 1989–1998 and 2011–2020, were selected from the whole observation period (1987–2022) to assess changes in precipitation infiltration due to climate change. The air temperature has increased significantly in November (+3.4 °C) and December (+3.3 °C), with a +2.2 °C increase in the standard climate normal. The distribution of yearly precipitation has changed, with the annual amount decreasing from 686 to 652 mm. Precipitation increased the most in July and August (10.9 and 22.9 mm). In autumn, the amount of precipitation decreased by 7.9–31.1 mm. The number of rainy days did not change during the year, but the frequency of heavy precipitation increased significantly in August. The annual percolation increased by 14.2% over 2011–2020 compared to 1989–1998. Percolation increased by 19.0, 22.3, and 20.1% during the spring, autumn, and winter, respectively, and decreased by 35.0% in summer. The increase in annual percolation is mostly related to the increase in temperature during the cold season: November and December. During these months, the likelihood of early freeze formation, which interrupts gravitational water percolation in soil, is significantly reduced. In the spring, the increase in average air temperatures in March leads to faster melting of the winter snow in a shorter period, which significantly increases percolation processes. In Lithuania, higher percolation in autumn and winter, when part of the agricultural land is not covered by vegetation, may lead to higher leaching of chemical elements. [ABSTRACT FROM AUTHOR]

The boreal hemisphere has been experiencing increasing extreme hot and dry conditions over the past few decades, consistent with anthropogenic climate change. The continental extension of this phenomenon calls for tools and techniques capable of monitoring the global to regional scales. In this context, satellite data can satisfy the need for global coverage. The main objective we have addressed in the present paper is the capability of infrared satellite observations to monitor the vegetation stress due to increasing drought and heatwaves in summer. We have designed and implemented a new water deficit index (wdi) that exploits satellite observations in the infrared to retrieve humidity, air temperature, and surface temperature simultaneously. These three parameters are combined to provide the water deficit index. The index has been developed based on the Infrared Atmospheric Sounder Interferometer or IASI, which covers the infrared spectral range 645 to 2760 cm−1 with a sampling of 0.25 cm−1. The index has been used to study the 2017 heatwave, which hit continental Europe from May to October. In particular, we have examined southern Italy, where Mediterranean forests suffer from climate change. We have computed the index's time series and show that it can be used to indicate the atmospheric background conditions associated with meteorological drought. We have also found a good agreement with soil moisture, which suggests that the persistence of an anomalously high water deficit index was an essential driver of the rapid development and evolution of the exceptionally severe 2017 droughts. [ABSTRACT FROM AUTHOR]

This paper presents work on investigating the effect of the initial size of water mist droplets on the evaporation and removal of heat from the fire-induced hot gas layer while travelling through the air in a compartment. The histories of the temperature, diameter and position of droplets with different initial diameters (varied from 100 µm to 1000 µm) are determined considering surrounding air temperatures of 75 °C and 150 °C and a room height of 3.0 m. A water droplet evaporation model (WDEM) developed in a previous study (Fire and Materials 2016; 40:190–205) is employed to navigate this work. The study reveals that tiny droplets (for example, 100 µm) have disappeared within a very short time due to evaporation and travelled a very small distance from the spray nozzle because of their tiny size. In contrast, droplets with a larger diameter (for example, 1000 µm) reached the floor with much less evaporation. In the case of this study, the relative tiny droplets (≤200 µm) have absorbed the highest amount of energy from their surroundings due to their complete evaporation, whereas the larger droplets have extracted less energy due to their smaller area/volume ratios, and their traverse times are shorter. One of the key findings of this study is that the smaller droplets of spray effectively cool the environment due to their rapid evaporation and extraction of heat from the surroundings, and the larger droplets are effective in traversing the hot air or smoke layer and reaching the floor of the compartment in a fire environment. The findings of this study might help in understanding the behaviour of water-mist droplets with different initial diameters in designing a water-mist nozzle. [ABSTRACT FROM AUTHOR]

Refrigerant maldistribution severely deteriorates the heat transfer performance of a microchannel evaporator. Compared with the refrigerant distribution among flat tubes along the header, refrigerant distribution among microchannels in the flat tube in the airflow direction has barely been paid attention. In this paper, a heat transfer mathematical model of a microchannel evaporator's flat tube composed of vertically placed parallel microchannels in the airflow direction was developed. The Refrigerant distribution among the microchannels was evaluated and its influence on heat transfer between air and refrigerant was analyzed. The results showed that the refrigerant distribution and heat transfer performance between air and refrigerant were interrelated and interacted with each other. The temperature of the air leaving the microchannel evaporator changed along the microchannel because of uneven refrigerant distribution among the microchannels, and the air temperature difference between air leaving out of the bottom and the top of the evaporator was approximately 2.13 °C. Ignoring the heat transfer from adjacent microchannels will lead to a small heat transfer deviation for the flat tube; thus, heat transfer among microchannels can be neglected. [ABSTRACT FROM AUTHOR]

Atmospheric weighted mean temperature (Tm) is a key parameter used by the Global Navigation Satellite System (GNSS) for calculating precipitable water vapor (PWV). Some empirical Tm models using meteorological or non-meteorological parameters have been proposed to calculate PWV, but their accuracy and reliability cannot be guaranteed in some regions. To validate and determine the optimal Tm model for PWV retrieval in China, this paper analyzes and evaluates some typical Tm models, namely, the Linear, Global Pressure and Temperature 3 (GPT3), the Tm model for China (CTm), the Global Weighted Mean Temperature-H (GTm-H) and the Global Tropospheric (GTrop) models. The Tm values of these models are first obtained at corresponding radiosonde (RS) stations in China over the period of 2011 to 2020. The corresponding Tm values of 87 RS stations in China are also calculated using the layered meteorological data and regarded as the reference. Comparison results show that the accuracy of these five Tm models in China has an obvious geographical distribution and decreases along with increasing altitude and latitude, respectively. The average root mean square (RMS) and Bias for the Linear, GPT3, CTm, GTm-H and GTrop models are 4.2/3.7/3.4/3.6/3.3 K and 0.7/−1.0/0.7/−0.1/0.3 K, respectively. Among these models, Linear and GPT3 models have lower accuracy in high-altitude regions, whereas CTm, GTm-H and GTrop models show better accuracy and stability throughout the whole China. These models generally have higher accuracy in regions with low latitude and lower accuracy in regions with middle and high latitudes. In addition, Linear and GPT3 models have poor accuracy in general, whereas GTm-H and CTm models are obviously less accurate and stable than GTrop model in regions with high latitude. These models show different accuracies across the four geographical regions of China, with GTrop model demonstrating the relatively better accuracy and stability. Therefore, the GTrop model is recommended to obtain Tm for calculating PWV in China. [ABSTRACT FROM AUTHOR]

Remotely sensed land surface temperature (LST) is often used as a proxy for air temperature in urban heat island studies, particularly to illustrate relative temperature differences between locations. Two sensors are used predominantly in the literature, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS). However, each has shortcomings that currently limit its utility for many urban applications. Landsat has high spatial resolution but low temporal resolution, and may miss hot days, while MODIS has high temporal resolution but low spatial resolution, which is inadequate to represent the fine grain heterogeneity in cities. In this paper, we overcome this inadequacy by combining high spatial frequency Environmental Services (ES), Landsat-driven Normalized Difference Vegetation Index (NDVI), and MODIS low spatial frequency background LST at different spatial frequency bands (spatial spectral composition). The method is able to provide fine scale LST four times daily on any day of the year. Using data from Paris in 2019 we show that (1) daytime cooling by vegetation reaches a maximum of 30 °C, above which there is no further increase in cooling. In addition, (2) the cooling is relatively local and does not extend further than 200 m beyond the boundary of the NBS. This model can be used to quantify the benefits of NBS in providing cooling in cities. [ABSTRACT FROM AUTHOR]

A sea ice model is an important component of an Earth system model, which is an essential tool for the study of sea ice, including its internal processes, interactions with other components, and projected future changes. This paper evaluates a simulation of sea ice by the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM 2.0), focusing on a historical simulation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the observations, CAS-ESM 2.0 reproduces reasonable seasonal cycle features and the climatological spatial distribution of Arctic and Antarctic sea ice, including sea ice extent (SIE), sea ice concentration, and sea ice thickness and motion. However, the SIE in CAS-ESM 2.0 is too large in winter and too low in summer in both hemispheres, indicating higher seasonal variations of the model relative to observations. Further sea ice mass budget diagnostics show that basal growth contributes most to ice increase in both hemispheres, basal melt and top melt make a comparable contribution to Arctic ice decrease, and basal melt plays a dominant role in Antarctic ice loss. This, combined with surface air temperature (SAT) and sea surface temperature (SST) biases, suggests that the excess of sea ice simulated in wintertime in both hemispheres and the lower SIE simulated in the Antarctic summer are mainly attributable to the bias in SST, whereas the lower SIE simulated in the Arctic summer is probably due to the combined effects of both the SST and SAT biases. [ABSTRACT FROM AUTHOR]

Recently, the requirements regarding the environment of nursing homes are high, because the elderly are a vulnerable group with limited adaptive capacity to respond to transient environmental change. This paper presents a field investigation on the influence of transient thermal comfort changes between the indoor and outdoor spaces (i.e., air temperature (Ta), solar radiation (SR), relative humidity (RH), wind speed (WS), and the thermal comfort indices of Universal Thermal Index (UTCI)) on the willingness of the elderly to use outdoor spaces of the Wanxia nursing home of Chengdu City. Results indicated that, in summer, the mean UTCI values of indoor and corridor spaces corresponded to the level of moderate heat stress, while those of road and garden corresponded to the strong heat stress level. Road and garden spaces even showed moderate heat stress in spring. Approximately 28.93% (139) of the elderly living here used outdoor spaces every day. The morning period (from 9:00 a.m. to 10:00 a.m.) was the elderly's favorited period for using outdoor spaces in seasons. The microclimatic transient differences between indoor and outdoor spaces ranged from 0.47 °C to 2.93 °C (|ΔTa|), from 86.09 W/m2 to 206.76 W/m2 (|ΔSR|), from 5.29% to 14.76% (ΔRH), from 0.01 m/s to 0.07 m/s (|ΔWS|), and from 0.25 °C to 2.25 °C (ΔUTCI). These big microclimate differences could cause enormous health risks for the elderly in the process of indoor and outdoor space conversion. The minimal transient change occurred between corridors and indoors. Pearson correlation analysis indicated ΔTa and ΔRH between indoor and outdoor spaces were the primary meteorological factors that influenced the elderly's willing to use outdoor spaces. The elderly preferred to live in a constant Ta and RH environment. Only when the ΔTa and ΔRH are small enough to resemble a steady-state (ΔUTCI ≤ 0.5 °C), ΔWS and ΔSI could affect the elderly's choice of using outdoor space. Optimal design strategies were put forward for reducing the transient differences between indoor and outdoor microclimates to inspire the elderly to use outdoor spaces safely, including improving outdoor canopy coverage and indoor mechanical ventilation. [ABSTRACT FROM AUTHOR]

Heat island effects raise the ambient air temperature in metropolitan areas by 4–5 degrees Celsius and can reach 10 degrees Celsius at their maximum. This phenomenon magnifies cities' energy difficulties while reducing comfort. Mitigation strategies have been developed and recommended to deal with the issue. Methods to increase albedo and the utilisation of vegetation appear to be the most promising, with a reasonably high heat island reduction capacity. This paper examines the heat mitigation techniques and their effectiveness under Sydney's climate conditions and compares strategies. We implement two perspectives, namely urban greening (green roofs, green pavements) and albedo (street, roof), and characterise urban surface structures, and Envi-met software is employed for our simulation method. Mitigation strategies show a cooling potential of 4.1 °C in temperature along this precinct during the heatwave period. Scenarios that increase high-albedo material on the road, pavements and rooftops and full mitigation show the maximum cooling potential. The mitigation strategies have higher predicted cooling potential on the peak ambient temperature, up to 1.18 °C, while having no or little impact on minimum ambient temperature. The outdoor thermal comfort based on PMV indices varies between a minimum of −0.33 in scenario seven in large layout areas to 3. However, the mitigation scenario presents more acceptable outdoor thermal comfort, but large layouts are predicted to have a hot condition. [ABSTRACT FROM AUTHOR]

Energy harvesting is an effective technique for prolonging the lifetime of Internet of Things devices and Wireless Sensor Networks. In applications such as environmental sensing, which demands a deploy-and-forget architecture, energy harvesting is an unavoidable technology. Thermal energy is one of the most widely used sources for energy harvesting. A thermal energy harvester can convert a thermal gradient into electrical energy. Thus, the temperature difference between the soil and air could act as a vital source of energy for an environmental sensing device. In this paper, we present a proof-of-concept design of an environmental sensing node that harvests energy from soil temperature and uses the DASH7 communication protocol for connectivity. We evaluate the soil temperature and air temperature based on the data collected from two locations: one in Belgium and the other in Iceland. Using these datasets, we calculate the amount of energy that is producible from both of these sites. We further design power management and monitoring circuit and use a supercapacitor as the energy storage element, hence making it battery-less. Finally, we deploy the proof-of-concept prototype in the field and evaluate its performance. We demonstrate that the system can harvest, on average, 178.74 mJ and is enough to perform at least 5 DASH7 transmissions and 100 sensing tasks per day. [ABSTRACT FROM AUTHOR]

Knowledge of the flowering dates of black locust trees (Robinia pseudoacacia L.) is crucial information of both economic significance and scientific interest. Black locust is in fact an excellent melliferous plant and can provide information on climate change impacts due to its large distribution throughout the world as planted and naturalized trees. This paper presents the calibration and validation of a phenological model targeted at the simulation of the whole process of black locust flowering (from BBCH 51—inflorescence of flower buds visible—to BBCH 69—end of flowering). The work relies on the phenological observations gathered in the context of IPHEN, the Italian PHEnological Network, with a broad latitudinal distribution of the observational sites (from 37.53° to 46.28° N) and a long time span, from 2010 to 2021. Phenology modeling is based on the Normal Heat Hours approach, which translates air temperature into thermal units based on a plant specific response curve. As meteorological input data, a high resolution (0.045°) gridded dataset was obtained by spatial interpolation of GSOD (NOAA) weather stations. [ABSTRACT FROM AUTHOR]

Putting glass doors on the display cases of refrigerators is one of the most efficient ways to reduce the energy consumption of supermarkets. However, the glass fogs up when opening the door because of the difference in air temperature inside and outside of the refrigerator, thereby obscuring the view. To defog the glass, anti-sweat heaters (ASHs) are used. In this paper, the power usage of ASHs according to changes in the dew point (DP) inside a supermarket were evaluated for two types of ASH, i.e., the door-frame ASH and the glass ASH. The evaluation was based on measurements of the condensation on the glass doors of vertical display cases, used for the preservation of frozen foodstuffs. A mathematical model of the correlation between the ASH's power usage and the DP was developed and used for predicting the long-term energy savings. The savings were calculated based on the measured DPs inside the supermarket, which were extrapolated over a longer time period based on their correlation with the outside DPs. Regulating the door-frame ASH according to the DP resulted in an 84.6% reduction in energy consumption and a 90.1% reduction in the case of the glass ASH, compared to the current state. The correlation between the DPs inside and outside the supermarket served as a basis for the proposed implementation of the power usage regulation of the ASH according to the DP. [ABSTRACT FROM AUTHOR]

The territory of Albania presents wide outcrops of soluble rocks, with typical karst landforms and the presence of remarkable carbonate aquifers. Many karst areas are located near the coasts, which results in a variety of environmental problems, mostly related to marine intrusion. This paper focuses on the brackish springs of Albania, which exhibit temperatures approximately equal to the yearly air temperature at their location. Total dissolved solids of the springs are higher than 1000 mg/L, their waters are not drinkable, and they are rarely used for other purposes. The groundwater of the alluvial aquifers of Albania, particularly those of Pre-Adriatic Lowland, are often brackish too, but these will not be addressed here. Brackish springs of Albania are mainly of karst origin and can be classified into two groups: springs in evaporitic rock, mainly gypsum, and springs in carbonate rock. The hydro-chemical facies of the first group are usually Ca-SO4, locally with increased concentrations of Na-Cl, whereas springs belonging to the second group usually exhibit Na-Cl facies. The largest brackish springs of Albania are described in detail, including their hydro-chemical correlations. [ABSTRACT FROM AUTHOR]

Due to the coupling impacts of solar radiation, wind, air temperature and other environmental parameters, the temperature field of steel structures is significantly non-uniform during their construction and service stages. Corrugated web steel beams have gained popularity in structural engineering during the last few decades, while their thermal actions are barely investigated. In this paper, both experimental and numerical investigations were conducted to reveal the non-uniform features and time variation of the corrugated web steel beams under various environmental conditions. The heat-transfer simulation model was established and verified using the experimental temperature data. Both the experiment and simulation results demonstrate that the steel beam has a complicated and non-uniform temperature field. Moreover, 2-year continuous numerical simulations of steel beams' thermal actions regarding eight different cities were carried out to investigate the long-term temperature variations. Finally, based on the long-term simulation results and extreme value analysis (EVA), the representative values of steel beams' daily temperature difference with a 50-year return period were determined. The extreme temperature difference of the steel beam in Harbin reached up to 46.9 °C, while the extreme temperature difference in Haikou was 28.8 °C. The extreme temperature difference is highly associated with the steel beam's location and surrounding climate. Ideally, the outcomes will provide some contributions for the structural design regarding the corrugated web steel beam. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays an important role in regulating terrestrial–atmospheric water circulation and energy balance. Most of the existing studies have explored the dynamic patterns of SM based on experimental methods. However, the analysis of large-scale regions and long-term SM sequences was limited. Alternatively, satellite remote sensing data is a potential source for SM analysis for large-scale basins. Therefore, the SM data from the European Space Agency (ESA) Climate Change Initiative (CCI) from 2000 to 2015 is used in this paper to analyze the SM spatial-temporal changes in the Yellow River Basin (YRB). Further, the Normalized Difference Vegetation Index (NDVI) and meteorological data are used to explore the relationships between SM and NDVI, precipitation, air temperature, and wind speed, respectively. The results showed that the overall trend of SM in the YRB was decreasing from southeast to northwest during the past 16 years. The upper reaches of the YRB had shown a humid trend, with a value of 0.00047 m3·m−3·year−1, mainly due to the increase in precipitation; there was an obvious drought trend in the middle reaches of the YRB, especially in Shanxi Province and Henan Province, with a value of −0.00030 m3·m−3·year−1, which may be owed to vegetation greening increasing the soil evaporation. Overall, it is determined that the main factors influencing SM changes were NDVI and precipitation, followed by air temperature and wind speed. This study can provide a scientific basis for the spatial-temporal distribution characteristics and attributions of SM in the YRB over a long time series. [ABSTRACT FROM AUTHOR]

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin's development. [ABSTRACT FROM AUTHOR]

The paper presented the results of surface water temperature measurements from 17 lakes located in northern Poland and Belarus over the period of 50 years (1971–2020). Using the Excel computer program, Corel Quattro Pro 8, and graphic Draw 9, annual and monthly averages, extreme values, and annual and monthly trends were calculated and presented. These were supplemented by the monthly average air temperatures for 13 weather stations. The research showed that the temperature in all lakes was characterized by a positive trend at the level of 0.044 °C year−1. The largest lake was characteristic for the Chervonoe Lake—0.066 °C year−1—and the smallest 0.029 °C year−1 for the deep Lake Hańcza. In the course of the average monthly surface water temperatures, a positive trend was also observed, ranging from 0.015 °C year−1 in January to 0.069 °C year−1 in May. These values correlated with the average air temperatures in the winter months (December–March) and with the winter NAO index (DJFM). [ABSTRACT FROM AUTHOR]

The temperature rises hydrogen tanks during the fast-filling process could threaten the safety of the hydrogen fuel cell vehicle. In this paper, a 2D axisymmetric model of a type III hydrogen for the bus was built to investigate the temperature evolution during the fast-filling process. A test rig was carried out to validate the numerical model with air. It was found significant temperature rise occurred during the filling process, despite the temperature of the filling air being cooled down due to the throttling effect. After verification, the 2D model of the hydrogen tank was employed to study the temperature distribution and evolution of hydrogen during the fast-filling process. Thermal stratification was observed along the axial direction of the tank. Then, the effects of filling parameters were examined, and a formula was fitted to predict the final temperature based on the simulated results. At last, an effort was paid on trying the improve the temperature distribution by increasing the injector length of the hydrogen tank. The results showed the maximal temperature and mass averaged temperature decreased by 2 K and 3.4 K with the length of the injector increased from 50 mm to 250 mm. [ABSTRACT FROM AUTHOR]

This paper investigates the annual and seasonal variations in the minimum and maximum air temperature (Tmin and Tmax) and precipitation over Kashmir valley, Northwestern Himalayas from 1980–2019 by using the innovative trend analysis (ITA), Mann-Kendall (MK), and Sen's slope estimator methods. The results indicated that the annual and seasonal Tmin and Tmax are increasing for all the six climatic stations, whereas four of them exhibit significant increasing trends at (α = 0.05). Moreover, this increase in Tmin and Tmax was found more pronounced at higher altitude stations, i.e., Pahalgam (2650 m asl) and Gulmarg (2740 m asl). The annual and seasonal precipitation patterns for all climatic stations showed downward trends. For instance, Gulmarg station exhibited a significant downward trend for the annual, spring, and winter seasons (α = 0.05). Whereas, Qazigund showed a significant downward trend for the annual and spring seasons (α = 0.05). The overall analysis revealed that the increased Tmin and Tmax trends during the winter season are one of the reasons behind the early onset of melting of snow and the corresponding spring season. Furthermore, the observed decreased precipitation trends could result in making the region vulnerable towards drier climatic extremes. Such changes in the region's hydro-meteorological processes shall have severe implications on the delicate ecological balance of the fragile environment of the Kashmir valley. [ABSTRACT FROM AUTHOR]

In recent years, the phenomenon of urban warming has become increasingly serious, and with the number of urban residents increasing, the risk of heatstroke in extreme weather has become higher than ever. In order to mitigate urban warming and adapt to it, many researchers have been paying increasing attention to outdoor thermal comfort. The mean radiant temperature (MRT) is one of the most important variables affecting human thermal comfort in outdoor urban spaces. The purpose of this paper is to predict the distribution of MRT around buildings based on a commonly used multilayer neural network (MLNN) that is optimized by genetic algorithms (GA) and backpropagation (BP) algorithms. Weather data from 2014 to 2018 together with the related indexes of the grid were selected as the input parameters for neural network training, and the distribution of the MRT around buildings in 2019 was predicted. This study obtained very high prediction accuracy, which can be combined with sensitivity analysis methods to analyze the important input parameters affecting the MRT on hot summer days (the days with the highest air temperature over 30 °C). This has significant implications for the optimization strategies for future building and urban designers to improve the thermal conditions around buildings. [ABSTRACT FROM AUTHOR]

Due to their simple design and reliable operation, earth-to-air heat exchangers (EAHE) are used in modern buildings to reduce ventilation heat losses. EAHE operation in atmospheric conditions results in variation in ambient air temperature and pressure affecting air density. The paper presents the study on the impact of ambient air density variation on the calculated hourly air temperature at the EAHE outlet and the resulting energy use for space heating and cooling of an exemplary residential building. The ground temperature was computed from the model given in EN 16798-5-1. Then, air density was obtained using five various methods. Energy use for space heating and cooling of the building was computed using the 5R1C thermal network model of EN ISO 13790. Depending on the chosen method and concerning the base case without EAHE, a reduction in annual heating and cooling needs was obtained from 7.5% to 8.8% in heating and from 15.3% to 19% in cooling. Annual heating and cooling gain from EAHE were 600.9 kWh and 628.3 kWh for heating and 616.9 kWh and 603.5 kWh for cooling for the Typical Meteorological Years (TMY) and International Weather for Energy Calculation (IWEC) files, respectively. Unit heating and cooling gains per heat exchanger area were from 34.9 kWh/m2 to 36.8 kWh/m2 and from −35.1 kWh/m2 to −36.3 kWh/m2. Density variation with temperature from the relevant typical Polish meteorological year at constant pressure, in comparison to the method of EN 16798-5-1, resulted in an hourly difference of that unit gain up to 4.3 W/m2 and 2.0 W/m2 for heating and cooling, respectively. The same was true inthe case of IWEC files that resulted in differences of 5.5 W/m2 and 1.1 W/m2. [ABSTRACT FROM AUTHOR]

Bump foil journal bearings (BFJBs) are widely used in the superchargers of aviation piston engines (APEs). This paper proposes a method to evaluate the operating state of superchargers by monitoring the bearing temperature. A numerical model with a repeating symmetrical structure in the axial direction is established based on a certain type of supercharger, which solves the temperature field of BFJBs with the non-isothermal Reynolds equation and energy equation. It can be used to analyze the effect of thermal expansion on lift-off speed and stop-contact speed. A new test rig and six various BFJBs were designed to check the temperature characteristics of the BFJBs with variable load and speed. By comparing the numerical results with the experimental results, it was shown that the air film temperature increased almost linearly with the increase in bearing load and speed. However, the temperature increase caused by the rotation speed was significantly greater than the load. The structural parameters of the BFJB affected the bearing support stiffness, which had a nonlinear effect on the lift-off speed and air film temperature. Therefore, the proposed method to evaluate the state of superchargers with BFJBs was effective. These thermal characteristics can be used to guide BFJB design and predict the life cycle of BFJBs. [ABSTRACT FROM AUTHOR]

Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed "wave-type ", "invested U-type", "U-type" and "wave-type", respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang. [ABSTRACT FROM AUTHOR]

Featured Application: The study presents a methodology to assess the risk of degradation for artifacts in a museum using indoor meteorological observations. Preservation of the cultural heritage of museums includes measures to prevent degrading effects induced by air temperature and humidity factors which are difficult to control. The present paper includes a synopsis of values of air temperature and relative humidity characterizing the indoor climate of the "Poni-Cernătescu" Museum of Iași, Romania for a period of one year. The objective of this research was to describe the museum microclimate and to identify and analyze the degradation risk of museum artifacts in order to study the impact of hygrothermal indoor and outdoor loads on indoor microclimate parameters. To achieve the objective, the following activities were carried out: acquisition of data on the relative humidity and the temperature of indoor and outdoor air; analysis of data with climate analysis tools and statistical methods; and transformation of data into quantitative and qualitative numerical measures of collection decay risks. The collected data enabled us to accurately describe the indoor climate conditions of the analyzed building. The main conclusions of the assessment were that the May–July period represented the interval with the highest degradation risk for all types of cultural assets (wood, leather, photos and paintings); this occurred because of the combination of a high amount of water vapor and high air temperature conditions. Based on charts and tabular data, this study presents the evolution of two parameters of internal microclimate, air temperature and relative humidity, and their correlation with external climate factors. The structural and functional parameters of the museum, the working levels of heating and air conditioning systems, the arrangement, the load, and the typological complexity of the artifacts displayed, were also considered in the analysis. The results obtained enabled us to develop useful recommendations to stabilize climate conditions inside the museum. Specific measures to mitigate the detrimental impact of the analyzed environmental factors are proposed. The results obtained show that in the basement, favorable conditions for mycelium growth occurred. In the summer months, across the entire museum space, the preservation indices were the lowest, from 20 to 25, so suitable conditions for storing the artifacts were not met. [ABSTRACT FROM AUTHOR]

Evaporation calculations are important for the proper management of hydrological resources, such as reservoirs, lakes, and rivers. Data-driven approaches, such as adaptive neuro fuzzy inference, are getting popular in many hydrological fields. This paper investigates the effective implementation of artificial intelligence on the prediction of evaporation for agricultural area. In particular, it presents the adaptive neuro fuzzy inference system (ANFIS) and hybridization of ANFIS with three optimizers, which include the genetic algorithm (GA), firefly algorithm (FFA), and particle swarm optimizer (PSO). Six different measured weather variables are taken for the proposed modelling approach, including the maximum, minimum, and average air temperature, sunshine hours, wind speed, and relative humidity of a given location. Models are separately calibrated with a total of 86 data points over an eight-year period, from 2010 to 2017, at the specified station, located in Arizona, United States of America. Farming lands and humid climates are the reason for choosing this location. Ten statistical indices are calculated to find the best fit model. Comparisons shows that ANFIS and ANFIS–PSO are slightly better than ANFIS–FFA and ANFIS–GA. Though the hybrid ANFIS–PSO ( R 2 = 0.99, VAF = 98.85, RMSE = 9.73, SI = 0.05) is very close to the ANFIS ( R 2 = 0.99, VAF = 99.04, RMSE = 8.92, SI = 0.05) model, preference can be given to ANFIS, due to its simplicity and easy operation. [ABSTRACT FROM AUTHOR]

In the context of aircraft aerodynamics, the compressibility of air flowing around the aircraft must always be considered. This fact brings with it one inconvenience: to evaluate the velocity of the flowing air (airspeed), it is necessary to know its temperature as well. Unfortunately, direct measurement of the temperature of air flowing at high speed (usually at Ma > 0.3) is practically impossible without knowledge of its velocity. Thus, there are two unknown quantities in the problem that depend on each other. The solution is achieved by a method that uses temperature probes composed of multiple sensors with different properties (different recovery factors). The comparison of rendered temperatures subsequently allows the elimination of the necessary knowledge of static temperature and the evaluation of velocity. In this paper, one of such probes is described together with its thermodynamic properties and possible applications. [ABSTRACT FROM AUTHOR]

In this paper, a plate counter-flow dew-point evaporative cooling system was designed with a nanoporous membrane covered on the surface of the wet channel for enhancement of heat and mass transfer. First, the operating principle of this device and theoretical analysis of nanoporous membrane evaporation were discussed in detail. Then, the impacts of several operating parameters on cooling performance, mainly including inlet air temperature, humidity, velocity, and the effect of utilizing the membrane, were investigated in trials. It was found that the cooling performance can be improved by using membrane significantly. In the dry channel, the maximum temperature decrease can reach 12.5 °C. At a high inlet air temperature, the product air can be dropped to a lower temperature, contributing to a more significant heat transfer process. Lower humidity, on the other hand, resulted in a reduced product air temperature and a lower cooling efficiency. Under the condition of 50% humidity, the wet-bulb efficiency and dew-point efficiency were 1.09 and 0.79, respectively. With the inlet air velocity increasing from 1.5 m/s to 2 m/s, the outlet air temperature would rise, and the wet-bulb efficiency and dew-point efficiency would decrease. To achieve better cooling performance, inlet air velocity ought to be limited to a low speed. [ABSTRACT FROM AUTHOR]

This paper investigates the response and characteristics of the narrowband power line communication (NB-PLC) technique for the effective control of electric appliances such as smart air conditioners (SACs) for demand side management (DSM) services. The expression for temperature sensitivity by examining the influence of atmospheric temperature variations on power consumption profile of all possible types of loads, i.e., residential, commercial, and industrial loads is derived and analyzed. Comprehensive field measurements on these power consumers are carried out in Lahore, Pakistan. The responses of low voltage channels, medium voltage channels, and transformer bridge for a 3–500 kHz NB-PLC frequency range are presented for DSM services. The master control room transmits control commands for the thermostat settings of SACs over power lines, crossing the transformer bridge to reach the SACs of power consumers by using communication protocol smart energy profile 1.0. The comparison of hourly and daily power consumption profiles under evaluation loads, by analyzing typical and variable frequency air conditioners on setting thermostat temperature at 25 °C and 27 °C conventionally and then by using DSM control technique, is analyzed. A prominent reduction in power consumption is found with the implementation of the DSM control technique. [ABSTRACT FROM AUTHOR]

This paper shows more evidence for the existing spatial–temporal synchronization of the air surface temperature and pressure within the lower stratospheric ozone, which is unevenly distributed over the globe. The focus of this study is put on the region of formation and manifestation of El Niño Southern Oscillation (ENSO). Statistical analysis of data (covering the period 1900–2019) displays a well pronounced covariance of ozone at 70 hPa with (i) Nino3.4 index, (ii) air surface temperature, and (iii) sea level pressure, in each grid-point with spatial resolution of 5° in latitude and longitude. The ozone impact could be found at different time scales—from interannual (altering the ENSO phase transition) to interdecadal. Moreover, the centers of action of ozone on the sea level temperature and pressure are positioned at different places, depending on the temporal scale of variability—from the tropical Central Pacific—at interannual and interdecadal, to extratropics—at subdecadal time scales. We show also that positive ozone anomalies at 70 hPa trigger a cooling of the sea surface, with a delay of 9 record's time intervals. The ozone depletion, on the other side, is followed by a sea level warming with a delay of 1–2 record's time intervals. [ABSTRACT FROM AUTHOR]

Precipitation is one of the many important natural factors impacting agriculture and natural resource management. Although statistics have been applied to investigate the non-stationary trend and the unpredictable variances of precipitation under climate change, existing methods usually lack a sound physical basis that can be generally applied in any location and at any time for future extrapolation, especially in tropical areas. Physically, the formation of precipitation is a result of ascending air which reduces air pressure and condenses moisture into drops, either by irregular terrain or atmospheric phenomena (e.g., via frontal lifting). Thus, in this paper, pressure change events (PCEs) will be used as a physical indicator of the stability of atmospheric systems to reveal the impact of temperature on precipitation in the tropical areas of Florida. By using data from both national and regional weather observation networks, this study segments the continuous observation series into PCE sequences for further analysis divided by dry and wet seasons. The results reveal that the frequency and intensity of PCE are highly associated with the occurrences of weather events. Decreasing pressure favors precipitation, and may turn extreme when the temperature and air moisture are sufficient to fuel the process. With similar intensity, decreasing pressure change events (DePCEs) generally bear a higher probability of precipitation (POP) and precipitation depth (PD) than increasing pressure change events (InPCEs). The frequency of alternating between InPCEs and DePCEs is subject to the temperature of the season and climate. Due to the seasonal fluctuations of weather characteristics, such as temperature and relative humidity, the dependence of extreme precipitation on these characteristics can be interpreted via PCE. A 7% increase rate of precipitation vs. temperature rise, determined by the Clausius—Clapeyron (C—C) relationship, can be observed from extreme precipitation with variances in the season and PCE types. Although indicated by other research, active vertical movement of air caused by a phase change in water at the frozen point is not pronounced in Florida. The response patterns of humidity to precipitation also vary by season and PCE types in extreme conditions. In summary, PCEs demonstrate reliable physical evidence of precipitation formation and can better associate the occurrence and intensity of extreme weather with other characteristics. In turn, such associations embody the underlying physical concepts present at any location in the world. [ABSTRACT FROM AUTHOR]

The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively. [ABSTRACT FROM AUTHOR]

Unexpected observations of strong radiowave scatter at a ~85–90 km altitude with very high frequency radars were explained in the early 1990s, when it was demonstrated that these were due to special turbulent and small-scale scatterers with high Schmidt number. Studies of these phenomena have primarily been concentrated in polar regions, and the events seem most prominent in regions of very cold air (below 140 K). Such radar echoes are referred to as polar mesosphere summer echoes (PMSE), and are rare at lower latitudes. In this paper we report observations of similar scatterers at sites below 50° latitude. The nature of these scatterers is discussed and results are compared to observations at the polar site of Eureka, Canada. Mid-latitude observations at frequencies of 48.92 and 45.47 MHz were made, respectively, at Abitibi Canyon (49.9° N latitude) and Markstay (46.5° N latitude) in Ontario, Canada. In particular, we look at the relationship of these scatterers to geophysical parameters, especially the Ap index. Our results suggest that mesospheric air with temperatures less than 140 K now exists below 50° latitude. This may be an indication of an equator-ward creep of global mesospheric cooling (which is associated with the well-known tropospheric global warming), but the scatterers at lower latitudes also demonstrate correlation with the Ap index. On the other hand, the polar scatterers at Eureka demonstrated no correlation of any significance with Ap. The importance of these results in regard to the global distribution of mesospheric temperatures is discussed, and comparisons to other measurements are made. [ABSTRACT FROM AUTHOR]

To maintain proper indoor air quality and increase energy efficiency, a demand-control ventilation (DCV) system has become a popular solution. This paper reports the findings of a field study conducted on the performance of the DCV systems in eight public buildings in southern Finland. We conducted the measurements in two stages. In the first stage, we made a site visit and measured the airflow rates in the design operation conditions of the chosen space. For the second stage, we left temperature/humidity data loggers to monitor the thermal conditions during the normal operation mode of the space. The results indicate that, out of the eight studied spaces, only one DCV system was performing according to design specifications. While the systems were operating in a suboptimal way, the flaws in functionality were mostly minor, and none of the sites had perceived indoor-air-quality- and/or thermal-condition-related problems during the time of measurement. Nonetheless, this result shows that the potential benefits of DCV were partially lost due to malfunctioning systems. Additionally, by only monitoring room air temperature (or IAQ) without airflow rate measurements in different operation modes, it is not possible to conclude whether the DCV system works properly or not. [ABSTRACT FROM AUTHOR]

This paper aims to provide data support for rural sustainable development through analyzing the spatio-temporal characteristics of the interactions of the outdoor thermal environment. The ordinary and representative rural settlements in the Guanzhong area were selected to analyze the dynamic process of the rural thermal environment through field measurements and numerical simulations. RMSE (root mean square error) and MAPE (mean absolute percentage) were used to verify the numerical simulation model, and physiological equivalent temperature (PET) was used to evaluate the outdoor thermal environment. Results show that the ENVI-met model reliably predicts the thermal environment of a rural settlement, as the air temperature and relative humidity values range of the RMSE and MAPE were 0.85–1.79 and 2.04–5.11%, respectively. Moreover, the air temperature rose by 3.08% and relative humidity dropped by 4.42% from 2003 to 2018 as the amount of artificial surfaces increased by 35.4% and the PET index gradually increased by 27.43% at daytime and 34.03% at nighttime. Furthermore, trees could improve the outdoor thermal environment significantly, mainly because the average air temperature decreased by 3.6% and relative humidity increased by 8%, and the PET index decreased by 12.4% and 13.1%, respectively, for daytime and nighttime. This case study is representative of rural settlements in the Guanzhong plain, and thus is an appeal to rural planners to pay attention to the thermal environment issues caused by increased artificial underlay surfaces and to focus on trees in rural areas. [ABSTRACT FROM AUTHOR]

Buildings account for a large portion of the total energy use in the US; therefore, improving the operation of typical variable-air-volume (VAV) systems in buildings can provide a tremendous economic opportunity. ASHRAE Guideline 36 recommends a resetting strategy for supply air temperature (SAT) for VAV systems based on outside air temperature. However, this strategy may not produce optimal performance, particularly when simultaneous cooling and heating occurs in zones. In addition, there is no strategy recommended in the Guideline to reset the zone minimum airflow set point in a single-duct VAV terminal unit with reheat, although this setpoint has a great impact on zone reheat requirements and ventilation efficiency. Thus, this paper introduces new strategies to reset both the SAT and zone minimum airflow rate set points to improve the efficiency of typical VAV systems. The strategies were tested under various conditions through experiments performed in fully instrumented VAV systems located in the HVAC lab at the University of Cincinnati. The experiments were conducted on a chilled-water VAV system that serves three controlled zones with hot-water reheat VAV boxes controlled by a typical commercial BACnet web-based building automation system BAS. The simulation studies were performed using the building energy simulation software EnergyPlus to evaluate the strategies at a larger scale in various locations. The simulation results show that the proposed resetting strategies can provide fan energy savings between 1.6% and 5.7% and heating load savings between 7.7% to 33.7%, depending on the location. The laboratory testing shows that the proposed strategies can provide stable control performance in actual systems as well as achieving the anticipated reheat and fan energy savings. The result offers significant improvements that can be implemented in the Guideline for single-duct VAV system operation and control. [ABSTRACT FROM AUTHOR]

In the present research, an overview of the wind climate on the northwestern coast of the Black Sea basin is assessed, using a total of 6 years of data (2015–2020) provided by the National Institute of Marine Geology and Geoecology (GeoEcoMar). It is well known that the enclosed/semi-enclosed basins are complex environments and to accurately represent the features of wind and wave are necessary high resolution spatial fields. For the Black Sea, which is an enclosed basin with complicated regional geography, the main weather parameters reported (wind direction, wind speed, air temperature, air pressure) give a more comprehensive picture of how energetic the area of interest is, and represent the features of the Black Sea's diversified marine environment. Finally, the results obtained in this paper cover a broad range of applications in marine studies, being useful for future research in the area of wind climate in the Black Sea. [ABSTRACT FROM AUTHOR]

This paper presents the results of long-term temperature monitoring at the Yakutsk and Zeleny Lug stations, which are experimental sites, for the thermal state of valley permafrost landscapes under the conditions of modern climate warming. An analysis of the long-term data from meteorological stations in the region clearly showed one of the highest trends of increase in the mean annual air temperature in the north of Russia. Here, we established quantitative regularities in the long-term variability of the ground temperature at the bottom of the active layer and at zero amplitude. The dynamics of the ground temperature of the layer of zero amplitude during climate warming indicate the thermal stability of permafrost. The main regulating factor of the thermal state of grounds in permafrost landscapes is short-term fluctuations in the regime of snow accumulation. Active layer thickness is characterized by low interannual variability, weak climate warming responses, and insignificant trends. The results of studies of the thermal regime of soils can be extended to the same types of valley landscapes in the Lena River, and are a reliable basis for predicting heat transfer in natural and disturbed landscapes. [ABSTRACT FROM AUTHOR]

Braking time in a moving train at standard speeds has become a critical variable that increasingly concerns the industry. The present paper discusses the possible option of temperature variation to cut down the response time of the whole pneumatic braking system in a train installation. A pneumatic system, considered equivalent to the system existing in a real train, was experimentally analyzed to account for the time and characteristics of a sonic pressure wave moving in the pipes. The available system behavior was compared for two different air temperatures. The obtained results point to a relevant temperature effect on the pressure wave transmission, which may promote time or distance shortening in a standard braking process. Although in the experimental campaign only two initial temperatures could be set, the study shows a possible research path for future improvements. A parallel theoretical calculation corrected by the effect of the relevant elements in the pipes was performed to allow a comparison with the experiments. [ABSTRACT FROM AUTHOR]

The sensitivity of seafloor temperature  T B  to the warming of surface air temperature  T a  is examined for 1850–2300, based on simulations with five models from the Coupled Models Intercomparison Project phase 6 ensemble and driven by a scenario with high anthropogenic emissions of greenhouse gases. In this historical period (until 2015), sensitivity coefficients  α = Δ T B / Δ T a  (Δ  indicates changes relative to the pre-industrial period) were typically ≤0.12 for annual means and up to 0.43 in summer. However, during the same period in the Barents Sea sector, the sensitivity coefficients were as large as 0.6 in summer. For summer, the obtained results are consistent with the limited measurements available for the Siberian shelf. In future, sensitivity coefficients will increase markedly, and  α ≥ 0.7  will become common for the part of the Arctic shelf that becomes ice-free in summer. Our results have implications for estimating the future thermal state of subsea sediments, as well as for oceanic biota. [ABSTRACT FROM AUTHOR]

Air pollution causes millions of mortalities and morbidities in large cities. Different mitigation strategies are being investigated to alleviate the negative impacts of different pollutants on people. Designing proper urban forms is one of the least studied strategies. In this paper, we modelled air pollution (NO2 concentration) within four hypothetical neighbourhoods with different urban forms: single, courtyard, linear east-west, and linear north-south scenarios. We used weather and air pollution data of Manchester as one of the cities with high NO2 levels in the UK. Results show that the pollution level is highly dependent on the air temperature and wind speed. Annually, air pollution is higher in cold months (45% more) compared to summer. Likewise, the results show that during a winter day, the concentration of air pollution reduces during the warm hours. Within the four modelled scenarios, the air pollution level in the centre of the linear north-south model is the lowest. The linear building blocks in this scenario reduce the concentration of the polluted air and keep a large area within the domain cleaner than the other scenarios. Understanding the location of air pollution (sources) and the direction of prevailing wind is key to design/plan for a neighbourhood with cleaner air for pedestrians. [ABSTRACT FROM AUTHOR]

Since the summer of 2022, the whole world has suffered the abnormal weather phenomena of high ambient temperature. Equipment for refrigeration, particularly portable refrigeration equipment, is crucial for personal protection in high–temperature environments, but cooling performance and miniaturization have been challenging issues. A portable air conditioner based on a semiconductor refrigeration device for human body cooling was developed. The total weight of the device is 450 g. The overall power consumption of the device is 82 W and the energy consumption ratio of semiconductor cooling plate is 0.85. The semiconductor refrigeration technology is based on the Peltier effect, supplemented by a DC fan to send the cooling air out to a specified position or zone. The structural parts are manufactured by 3D printing technology to make the overall size of the device more compact. The air volume and cooling performance of the device were analyzed by computational fluid dynamics simulation and the temperature distribution was measured by an infrared thermal imager and other instruments, and the measured results agreed with the CFD simulation results. The test ambient temperature was 20 °C. The measurement results showed that the wind speed of the hot air outlet was 6.92 m/s and that of the cold air outlet was 8.24 m/s. The cold air surface temperature reached a stable state of 13.9 °C in about 4 min, while the hot air surface temperature reached a stable state of 47.2 °C. [ABSTRACT FROM AUTHOR]