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This paper presents an off-design analysis of a gas turbine Organic Rankine Cycle (ORC) combined cycle. Combustion turbine performances are significantly affected by fluctuations in ambient conditions, leading to relevant variations in the exhaust gases' mass flow rate and temperature. The effects of the variation of ambient air temperature have been considered in the simulation of the topper cycle and of the condenser in the bottomer one. Analyses have been performed for different working fluids (toluene, benzene and cyclopentane) and control systems have been introduced on critical parameters, such as oil temperature and air mass flow rate at the condenser fan. Results have highlighted similar power outputs for cycles based on benzene and toluene, while differences as high as 34% have been found for cyclopentane. The power output trend with ambient temperature has been found to be influenced by slope discontinuities in gas turbine exhaust mass flow rate and temperature and by the upper limit imposed on the air mass flow rate at the condenser as well, suggesting the importance of a correct sizing of the component in the design phase. Overall, benzene-based cycle power output has been found to vary between 4518 kW and 3346 kW in the ambient air temperature range considered. [ABSTRACT FROM AUTHOR]

The condensate on the surface of the minichannel heat exchanger generated during air cooling substantially reduces the heat transfer performance as it works as an evaporator in the air-conditioning system. This has received much attention in scientific communities. In this paper, the effect of operating parameters on the heat transfer performance of a minichannel heat exchanger (MHE) is investigated under an evaporator working condition. An experimental MHE test system is developed for this purpose, and extensive experimental studies are conducted under a wide range of working conditions using the water-cooling method. The inlet air temperature shows a large effect on the overall heat transfer coefficient, while the inlet air relative humidity shows a large effect on the condensate aggregation rate. The airside heat transfer coefficient increases from 66 to 81 W/(m2·K) when the inlet air temperature increases from 30 to 35 °C. While the condensate aggregation rate on the MHE surface increases by up to 1.8 times when the relative humidity increases from 50% to 70%. The optimal air velocity, 2.5 m/s, is identified in terms of the heat transfer rate and airside heat transfer coefficient of the MHE. It is also found that the heat transfer rate and overall heat transfer coefficient increase as the air velocity increases from 1.5 to 2.5 m/s and decreases above 2.5 m/s. Furthermore, a large amount of condensate accumulates on the MHE surface lowering the MHE heat transfer. The inclined installation angle of the MHE in the wind tunnel effectively enhances heat transfer performance on the MHE surface. The experimental results provide useful information for reducing condensate accumulation and enhancing microchannel heat transfer. [ABSTRACT FROM AUTHOR]

The latest reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF), ERA5, can provide atmospheric data for calculating Zenith Tropospheric Delay (ZTD) with hourly temporal resolution, which is a key factor in Global Navigation Satellite System (GNSS) high-precision application. This paper is aimed at evaluating the performance of ZTD derived from ERA5 reanalysis data over China using 219 GNSS stations of the Crustal Movement Observation Network of China (CMONOC) covering the period from 2015 to 2016. The site-specific hourly ZTD at these stations is obtained by integration method and Saastamoinen model method on ERA5 pressure-level and surface-level reanalysis data with the temporal resolution of 1 h and the spatial resolution of 0.25° × 0.25°. Firstly, the atmospheric temperature and pressure that derived from ERA5 are compared with temperature and pressure obtained from meteorological sensors available at 193 GNSS stations. The biases are 2.31 °C and 1.26 mbar implying the accuracy and feasibility of ERA5 pressure and temperature for calculating ZTD over China. Secondly, the performance of ERA5 ZTD is systematically evaluated using ZTD from 219 GNSS sites. The average bias and Root Mean Square (RMS) of ERA5 pressure-level ZTD at all test stations in integration method are approximately 2.97 mm and 11.49 mm respectively, and those of ERA5 surface-level ZTD in model method are 7.97 mm, 39.25 mm, which indicates that ERA5 pressure-level ZTD has a higher accuracy over China. Further analysis indicates that the accuracies of ZTD derived from ERA5 pressure-level and surface-level data are approximately 13.8% and 10.9% higher than those from of ERA-Interim pressure-level and surface-level data. Moreover, ERA5 is able to accurately capture the short-term (hourly) variation of ZTD, which further indicates the better performance of ERA5. Thirdly, the temporal and spatial variation characteristics of ERA5 ZTD accuracy are further analyzed over China. The results show that the ZTD in the southern region has the lower accuracy compared with that in the northern region over China due to the influence of latitude and altitude. Furthermore, it is found that the ERA5 ZTD over China has obvious seasonality, with higher accuracy in winter and lower accuracy in summer. [ABSTRACT FROM AUTHOR]

Atmospheric ozone (O3) in the surface level plays a central role in determining air quality and atmospheric oxidizing capacity. In this paper, we review our comprehensive results of simultaneous measurements of surface ozone (O3) and its precursor gas (NOx) and weather parameters that were carried out continuously for a span of six years (January 2013–December 2018) at a typical rural coastal site, Kannur (11.9° N, 75.4° E) in South India. Surface O3 concentration reached its maximum during daytime hours and minimum during the night time. The influence of solar radiation and water content on variations of O3 are discussed. A Multi-Layer Perceptron (MLP) artificial neural network technique has been used to understand the effect of atmospheric temperature on the increase in O3 over the past six years. This has been found that temperature has been a major contributor to the increase in O3 levels over the years. The National Centre for Atmospheric Research- Master Mechanism (NCAR-MM) Photochemical box model study was conducted to validate the variations of O3 in different seasons and years, and the results were shown to be in good agreement with observed trends. [ABSTRACT FROM AUTHOR]

Works of art are sensitive to environmental factors—mainly temperature and relative humidity—which, when stable, are generally recommended as ideal protection conditions, but in historical museum buildings, the required conditions are difficult to maintain, due to a lack of adequate heating, ventilation and air-conditioning systems. The paper presents the analysis of one-year measurements of temperature and relative humidity in three different museums in Poland. The aim of the research was to identify the risk to museum collections, due to unbalanced moisture loads and unstable indoor air temperatures, as well as to identify possible causes of fluctuations in these parameters. This article focuses on assessing the impact of variable external and internal loads on the hygrothermal parameters of indoor air. The profile of internal hygrothermal loads in exhibition halls varied over time, which resulted in a temporary variation of the indoor environmental parameters. The lack of appropriate systems, shaping the microclimate in the analyzed museums, and the lack of automatic control in existing devices did not allow to maintain the temperature and relative humidity within appropriate limits. In the museums, the maximum indoor temperature values were higher than those recommended in the requirements. Relative humidity values in all museums exceeded the recommended range both above and below. [ABSTRACT FROM AUTHOR]

Foam materials are widely used in heat exchange because of their high porosity and large specific surface area. Correctly characterizing heat transfer characteristics is the key to ensuring efficient heat transfer. In this paper, single-blow transient test technology is used to experimentally measure the temperature. Silicon carbide ceramics with various thicknesses ranging from 30 to 105 mm and different pore structures were used in the experiments. The test was carried out at the velocity ranging from 0.5 to 1.8 m/s. The air temperature distributions of the inlet and outlet were obtained by processing the experimental data, and the regularity of the average volumetric heat transfer coefficient was obtained and analyzed. Subsequently, the simplified tetrakaidecahedron models with a porosity of 0.85 and 0.75 were used to analyze the heat transfer characteristics. The local thermal equilibrium and local thermal non-equilibrium at the pore scale were analyzed. By comparing the simulation with the experiment, it shows that the larger thickness affects local thermal equilibrium and leads to a decrease in the volumetric heat transfer coefficient. The conclusion can be used to guide the optimization of the design of foam material-mediated heat exchange equipment. [ABSTRACT FROM AUTHOR]

The quick U-building (QUB) method is used to measure the overall heat loss coefficient of buildings during one to two nights by applying heating power and by measuring the indoor and the outdoor temperatures. In this paper, the numerical model of a real house, previously validated on experimental data, is used to conduct several numerical QUB experiments. The results show that, to some extent, the accuracy of QUB method depends on the boundary conditions (solar radiation), initial conditions (initial power and temperature distribution in the walls) and on the design of QUB experiment (heating power and duration). QUB method shows robustness to variation in the value of the overall heat loss coefficient for which the experiment was designed and in the variation of optimum power for the QUB experiments. The variations in the QUB method results are smaller on cloudy than on sunny days, the error being reduced from about 10% to about 7%. A correction is proposed for the solar radiation absorbed by the wall that contributes to the evolution of air temperature during the heating phase. [ABSTRACT FROM AUTHOR]

Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of residential buildings in order to derive potential design strategies. Different climate file inputs of Madrid have been used to quantify comparatively the thermal needs of two reference residential buildings located in this city. One of them represents buildings older than 40 years built according to the applicable Spanish regulations prior to 1979. The other refers to buildings erected in the last decade under more energy-restrictive constructive regulations. Three different climate databases of Madrid have been used to assess the impact of the evolution of the climate in recent years on the thermal demands of these two reference buildings. Two of them are typical meteorological years (TMY) derived from weather data measured before 2000. On the contrary, the third one is an experimental file representing the average values of the meteorological variables registered in Madrid during the last decade. Annual and monthly comparisons are done between the three climate databases assessing the climate changes. Compared to the TMYs databases, the experimental one records an average air temperature of 1.8 °C higher and an average value of relative humidity that is 9% lower. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of buildings is among the most urgent social development tasks due to the scale of energy consumption in this industry. At the same time, it is essential to meet high requirements for indoor environmental quality and thermal comfort. The issue of overheating is most often analysed in summer but it also occurs in transition seasons, when the cooling systems do not operate. The paper attempts to evaluate the effectiveness of external mobile shading elements on the microclimate of rooms with large glazed areas in the transition season. Passive solutions, such as shading elements, which limit the increase of indoor temperature, do not always allow the acquisition and maintenance of comfortable solutions for the duration of the season, as demonstrated by the authors. Temporary cooling of the rooms may be necessary to maintain comfortable conditions for the users, or other solutions should be devised to improve comfort (e.g., reduction of clothing insulation characteristics). The novelty of the study consists in the analysis of comfort in a "nearly zero energy consumption" building (NZEB) during a period not analyzed by other scientists. This is a transition period during which heating/cooling systems do not operate. The research task set by the authors involved the assessment of the possibility to reduce office space overheating in the transition season (spring) by using external shading equipment in rooms with large glazed areas. An additional research task aimed at checking the extent to which user behaviour, such as reduction in clothing insulation characteristics, can improve comfort in overheated rooms. The results of the tests reveal that the difference in the ambient air temperature between a room with external venetian blinds and an identical room with no venetian blinds in the transition season, i.e., from 27 March to 6 April 2017, ranged from 12.3 to 2.1 °C. The use of a shading system (external venetian blinds positioned at an angle of 45°) reduced the number of discomfort hours by 92% (during working hours) compared to the room without external venetian blinds. A reduction in the thermal insulation of the clothes worn by people working in the room with no venetian blinds helped to reduce the number of discomfort hours by 31%. [ABSTRACT FROM AUTHOR]

Environmental conditions (temperature, moisture and the intensity of the sun) influence variation in asphalt pavement strength during the year. Lithuania is situated in a zone by average warm summers and average cold winters, and the most important climatic factor is the variation of the air temperature. This study presents the influence of temperature (of asphalt concrete (AC) and subgrade layers) and moisture content (of subgrade layers) to the pavement bearing capacity. The experimental research was obtained in five pavement sections of the experimental road. This experimental road was constructed in 2007 in Lithuania and is operated for more than 12 years. This paper presents a statistical analysis between the bearing capacity and the thickness of the asphalt concrete layers, the temperature and moisture content of different pavement layers, among sections, loaded and unloaded lanes (right and left wheel paths and tracks). The bearing capacity was evaluated by a falling weight deflectometer (FWD), temperature and moisture content by electronic sensors and thickness of AC layers by Georadar. Analysis of overall E0 and E0,h9 (bearing capacity at a depth of 9 cm from asphalt surface) data declares that seasonal impact on pavement structural strength due to a change of subgrade bearing capacity remains after correction of asphalt stiffness dependent on the temperature in the layer. However, it was detected that neither E0 nor E0,h9 are related to moisture content at a depths of 100 cm, 130 cm and 150 cm. [ABSTRACT FROM AUTHOR]

The successful launch of the Landsat 8 satellite provides important data for the monitoring of urban heat island effects. Since the Landsat 8 TIRS data has two thermal infrared bands, it is suitable for many algorithms to retrieve the land surface temperature (LST). However, the selection of algorithms for retrieving the LST, the acquisition of algorithm input parameters, and the verification of the results are problems without obvious solutions. Taking Changchun City as an example, this paper used the mono-window algorithm (MWA), the split window algorithm (SWA), and the single-channel (SC) method to extract the LST from the Landsat 8 image and compared the three algorithms in terms of input parameters, accuracy, and sensitivity. The results show that all three algorithms can achieve good results in retrieving the LST. The SWA is the least sensitive to the error of the input parameters. The MWA and the SC method are sensitive to the error of the input parameters, and compared with the error of the LSE, these two algorithms are more sensitive to the error of atmospheric water vapor content. In addition, the MWA is also very sensitive to the error of the effective mean atmospheric temperature. [ABSTRACT FROM AUTHOR]

This paper aims to analyse and conclude about the behaviour of the most commonly used human thermal comfort indices under a variety of atmospheric conditions in order to provide further information about their appropriateness. Utilising Generalized Additive Models (GAMs), this article examines the indices' sensitivity when exposed to diverse classified atmospheric conditions. Concentrated upon analysing commonly used human thermal indices, two Statistical/Algebraic indices (Thermohygrometric Index (THI) and HUMIDEX (HUM)), and four Energy Balance Model indices (Physiologically Equivalent Temperature (PET), modified PET (mPET), Universal Thermal Climate Index (UTCI), and Perceived Temperature (PT)) were selected. The results of the study are twofold, the identification of (1) index sensitivity to parameters' variation, and change rates, resultant of different atmospheric conditions; and, (2) the overall pertinence of each of the indices for local thermal comfort evaluation. The results indicate that the thermohygrometric indices cannot follow and present the thermal conditions' variations. On the other hand, UTCI is very sensitive under low radiation condition, and PET/mPET present higher sensitivity when the weather is dominated by high radiation and air temperature. PT index provides the lower sensitive among the human energy balance indices, but this is adequately sensitive to describe the thermal comfort environment. [ABSTRACT FROM AUTHOR]

An increasing number of individuals and institutions own or operate meteorological stations, but the resulting data are not yet commonly used in the Czech Republic. One of the main difficulties is the heterogeneity of measuring systems that puts in question the quality of outcoming data. Only after a thorough quality control of recorded data is it possible to proceed with for example a specific survey of variability of a chosen meteorological parameter in an urban or suburban region. The most commonly researched element in the given environment is air temperature. In the first phase, this paper focuses on the quality of data provided by amateur and institutional stations. The following analyses consequently work with already amended time series. Due to the nature of analyzed data and their potential use in the future it is opportune to assess the appropriateness of chronological and possibly spatial interpolation of missing values. The evaluation of seasonal variability of air temperature in the scale of Brno city and surrounding area in 2015–2017 demonstrates, that the enrichment of network of standard (professional) stations with new stations may significantly refine or even revise the current state of knowledge, for example in the case of urban heat island phenomena. A cluster analysis was applied in order to assess the impact of localization circumstances (station environment, exposition, etc.) as well as typological classification of the set of meteorological stations. [ABSTRACT FROM AUTHOR]

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machines and Random Forest, are compared with Multiple Linear Regression and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using two different approaches, a leave-one-out cross validation in the spatial domain and a spatio-temporal k-block cross-validation, and four different statistics on a daily basis, allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest produces the best results (R2 = 0.888 ± 0.026, Root mean square error = 3.01 ± 0.325 using k-block cross-validation). Regression methods (Support Vector Machine, Random Forest and Multiple Linear Regression) are calibrated with MODIS data and several predictors easily calculated from a Digital Elevation Model. The most important variables in the Random Forest model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day. [ABSTRACT FROM AUTHOR]

Nature has been adversely affected by increasing industrialization, especially during the latter part of the last century, as a result of accelerating technological development, unplanned urbanization, incorrect agricultural policies and deforestation, which have contributed to the elevated concentration of the greenhouse gases (GHGs) in the environment. GHG accumulation has an adverse impact on meteorological and hydro-meteorological parameters, particularly temperature. Temperature plays a prominent and well-known role in evaporation, transpiration and changes in water demand, and thus significantly affects both water availability and food security. Therefore, a systematic understanding of temperature is important for fighting food insecurity and household poverty. Variations in temperature are often assessed and characterized through trend analysis. Hence, the objective of this paper is to determine long-term trends in mean monthly maximum and minimum air temperatures for the Maloti-Drakensberg region. The Mann–Kendall test, a non-parametric test, was applied on mean air temperature for the 1960–2016 period. A significant rising trend (p < 0.001) was detected with a yearly change in the long term annual mean maximum and mean minimum temperature by 0.03 °C/annum and 0.01 °C/annum, respectively. This knowledge has important implications for both the state of the environment and livelihoods in the region, since its use can be useful in planning and policymaking in water resource management, biodiversity conservation, agriculture, tourism and other sectors of the economy within the region. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate the suitability of an analog model output statistics (MOS) downscaling technique for urban-scale meteorology research and compares this MOS-Analog technique with the sliding window technique. We downscaled air temperatures forecasted for the Seoul metropolitan area from 1.5 km resolution (using data from the Unified Model-Local Data Assimilation and Prediction System, UM-LDAPS) to 25 m resolution using the analog MOS technique described in the paper. The support vector machine (SVM) technique was employed for empirical computational modeling, using urban surface parameters calculated using the Climate Analysis Seoul (CAS) workbench and automated weather station (AWS) observational data as training data. The comparison of the downscaled prediction results with the AWS observations for the periods of July/August 2016 and 2017 resulted in a lower root mean square error (RMSE) and higher correlation coefficients (CC) than those obtained for the LDAPS prediction results. The prediction performance was also stable for September, during which precipitation episodes and seasonal fluctuations occurred. The results of this study demonstrate that the proposed technique, which overcomes the limitations of the sliding window technique, is applicable to urban-scale meteorology research and potentially applicable other areas. [ABSTRACT FROM AUTHOR]

In the context of urbanization, research on urban microclimate and thermal comfort has become one of the themes of eco-city design. Sky view factor (SVF), one of the parameters of urban spatial form, combines multiple morphological information, such as plane opening, aspect ratio, and building density and has an important impact on the urban microclimate. However, there is still no clear research conclusion on the correlation between SVF and microclimate. In this paper, nine Local Climate Zone (LCZ) models are used and typical summer meteorological conditions of Nanjing are applied as an attempt to partially fill this gap. The calculated microclimate and thermal comfort indices include air temperature (AT), surface temperature (ST), relative humidity (RH), wind speed (WS), mean radiant temperature (MRT), and predicted mean vote (PMV). Results show that the local effect of urban morphology on thermal comfort can be retrieved from the use of comprehensive parameters such as SVF (which takes into account the building height, layout, and density) whose distribution in the investigated models showed to be correlated with MRT, so did PMV under low wind speed conditions. [ABSTRACT FROM AUTHOR]

Weigh-in-motion systems are installed in pavements or on bridges to identify and reduce the number of overloaded vehicles and minimise their adverse effect on road infrastructure. Moreover, the collected traffic data are used to obtain axle load characteristics, which are very useful in road infrastructure design. Practical application of data from weigh-in-motion has become more common recently, which calls for adequate attention to data quality. This issue is addressed in the presented paper. The aim of the article is to investigate the accuracy of 77 operative weigh-in-motion stations by analysing steering axle load spectra. The proposed methodology and analysis enabled the identification of scale and source of errors that occur in measurements delivered from weigh-in-motion systems. For this purpose, selected factors were investigated, including the type of axle load sensor, air temperature and vehicle speed. The results of the analysis indicated the obvious effect of the axle load sensor type on the measurement results. It was noted that systematic error increases during winter, causing underestimation of axle loads by 5% to 10% for quartz piezoelectric and bending beam load sensors, respectively. A deterioration of system accuracy is also visible when vehicle speed decreases to 30 km/h. For 25% to 35% of cases, depending on the type of sensor, random error increases for lower speeds, while it remains at a constant level at higher speeds. The analysis also delivered a standard steering axle load distribution, which can have practical meaning in the improvement of weigh-in-motion accuracy and traffic data quality. [ABSTRACT FROM AUTHOR]

Numerous reviews on hydrogen storage have previously been published. However, most of these reviews deal either exclusively with storage materials or the global hydrogen economy. This paper presents a review of hydrogen storage systems that are relevant for mobility applications. The ideal storage medium should allow high volumetric and gravimetric energy densities, quick uptake and release of fuel, operation at room temperatures and atmospheric pressure, safe use, and balanced cost-effectiveness. All current hydrogen storage technologies have significant drawbacks, including complex thermal management systems, boil-off, poor efficiency, expensive catalysts, stability issues, slow response rates, high operating pressures, low energy densities, and risks of violent and uncontrolled spontaneous reactions. While not perfect, the current leading industry standard of compressed hydrogen offers a functional solution and demonstrates a storage option for mobility compared to other technologies. [ABSTRACT FROM AUTHOR]

Highlights from the article: This special issue collects original and review articles on large-scale atmospheric circulation variability and its climate impacts. Anomalous atmospheric circulations influence temperature and precipitation fields, the two most important climate elements. Papers 7-12 explore sea surface temperature (SST) forcings, particularly those associated with the tropical El Niño-Southern Oscillation (ENSO), on atmospheric circulation and climate anomalies over various regions across the globe.

Condenser evaporative pre-coolers provide a low cost retrofit option for existing packaged rooftop air conditioning application units. This paper aimed to provide a comprehensive study to assess energy savings and peak power reductions of condenser evaporative cooling. Condenser evaporative cooling leads to a lower temperature of the air entering the condenser of a rooftop unit, which results in smaller compressor power consumption. Using EnergyPlus building energy simulations, we mapped the impacts on energy savings and energy reductions at peak ambient temperatures in three building types and 16 locations with levels of pad effectiveness and demonstrated the effects on air conditioner using either R22 or R410A as refrigerants. Economics and control strategy to maximize the cost saving were also investigated. The results demonstrate that energy savings are much greater for HVAC systems with the refrigerant R410A than they are with R22, and evaporative pre-cooling provides the opportunity for annual energy savings and peak demand reductions, with significant potential in hot, dry climates. Additionally, we validated an improved mathematical model for estimating the condenser pre-cooling wet bulb efficiency which shows clear advantage over the current EnergyPlus model. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to evaluate whether meteorological variables influence rates of pneumothorax and chest tube placement after percutaneous transthoracic needle biopsy (PTNB) of pulmonary nodules. A retrospective review of 338 consecutive PTNBs of pulmonary nodules at a single institution was performed. All procedures implemented a coaxial approach, using a 19-gauge outer guide needle for access and a 20-gauge core biopsy gun with or without a small-gauge aspiration needle for tissue sampling. Correlation between age, sex, smoking history, lesion size, meteorological variables, and frequency of complications were evaluated. Fisher exact, trend and t tests were used to evaluate the relationship between each factor and rates of pneumothorax and chest tube placement. A p value of less than 0.05 was considered to indicate a statistically significant difference. Pneumothorax occurred in 115 of 338 patients (34%). Chest tube placement was required in 30 patients (8.9%). No significant relationship was found between pneumothorax rate and age (p = 0.172), sex (p = 0.909), smoking history (p = 0.819), or lesion location (p = 0.765). The presence or absence of special weather conditions did not correlate with the rate of pneumothorax (p = 0.241) or chest tube placement (p = 0.213). The mean atmospheric temperature (p = 0.619) and degree of humidity (p = 0.858) also did not correlate with differences in the rate of pneumothorax. Finally, mean atmospheric pressure on the day of the procedure demonstrated no correlation with the rate of pneumothorax (p = 0.277) or chest tube placement (p = 0.767). In conclusion, no correlation is demonstrated between the occurrence of pneumothorax after PTNB of pulmonary nodules and the studied meteorological variables. [ABSTRACT FROM AUTHOR]

The continuous energy transformation processes in heating, ventilation, and air conditioning systems of buildings are responsible for 36% of global final energy consumption. Tighter thermal insulation requirements for buildings have significantly reduced heat transfer losses. Unfortunately, this has little effect on energy demand for ventilation. On the basis of the First and the Second Law of Thermodynamics, the concepts of entropy and exergy are applied to the analysis of ventilation air handling unit (AHU) with a heat pump, in this paper. This study aims to develop a consistent approach for this purpose, taking into account the variations of reference temperature and temperatures of working fluids. An analytical investigation on entropy generation and exergy analysis are used, when exergy is determined by calculating coenthalpies and evaluating exergy flows and their directions. The results show that each component of the AHU has its individual character of generated entropy, destroyed exergy, and exergy efficiency variation. However, the evaporator of the heat pump and fans have unabated quantities of exergy destruction. The exergy efficiency of AHU decreases from 45–55% to 12–15% when outdoor air temperature is within the range of −30 to +10 °C, respectively. This helps to determine the conditions and components of improving the exergy efficiency of the AHU at variable real-world local climate conditions. The presented methodological approach could be used in the dynamic modelling software and contribute to a wider application of the Second Law of Thermodynamics in practice. [ABSTRACT FROM AUTHOR]

Surface air temperature (Ta) is an important physical quantity, usually measured at ground weather station networks. Measured Ta data is inadequate to characterize the complex spatial patterns of Ta field due to low density and unevenness of the networks. Remote sensing can provide satellite imagery with large scale spatial coverage and fine resolution. Estimating spatially continuous Ta by integrating ground measurements and satellite data is an active research area. A variety of methods have been proposed and applied in this area. However, the existing studies primarily focused on daily Ta and failed to quantify uncertainties in model parameter and estimated results. In this paper, a Bayesian Kriging regression (BKR) method is proposed to model and estimate monthly Ta using satellite-derived land surface temperature (LST) as the only input. The BKR is a spatial statistical model with the capacity to quantify uncertainties via Bayesian inference. The BKR method was applied to estimate monthly maximum air temperature (Tmax) and minimum air temperature (Tmin) over the conterminous United States in 2015. An exploratory analysis shows a strong relationship between LST and Ta at the monthly scale, indicating LST has the great potential to estimate monthly Ta. 10-fold cross-validation approach was adopted to compare the predictive performance of the BKR method with the linear regression method over the whole region and the urban areas of the contiguous United States. For the whole region, the results show that the BKR method achieves a competitively better performance with averaged RMSE values 1.23 K for Tmax and 1.20 K for Tmin, which are also lower than previous studies on estimation of monthly Ta. In the urban areas, the cross-validation demonstrates similar results with averaged RMSE values 1.21 K for Tmax and 1.27 K for Tmin. Posterior samples for model parameters and estimated Ta were obtained and used to analyze uncertainties in the model parameters and estimated Ta. The BKR method provides a promising way to estimate Ta with competitively predictive performance and to quantify model uncertainties at the same time. [ABSTRACT FROM AUTHOR]

In the context of global warming, the air temperature of the Heihe basin in Northeast China has increased significantly, resulting in the degradation of the island permafrost. In this paper, we used an elaborated time-series Interferometric Synthetic Aperture Radar (InSAR) strategy to monitor the ground deformation in the Heihe area (Heilongjiang Province, China) and then analyzed the permafrost deformation characteristics from June 2007 to December 2010. The results showed that the region presented island permafrost surface deformation, and the deformation rate along the line of sight mainly varied from –70 to 70 mm/a. Based on the analysis of remote sensing and topological measurements, we found that the deformation area generally occurred at lower altitudes and on shady slopes, which is consistent with the distribution characteristics of permafrost islands. Additionally, the deformation of permafrost is highly correlated with the increase of annual minimum temperature, with an average correlation value of –0.80. The accelerated degradation of permafrost in the study area led to the settlement, threatening the infrastructure safety. Our results reveal accelerated degradation characteristics for the island permafrost under the background of rising air temperature, and provide a reference for future relevant research. [ABSTRACT FROM AUTHOR]

Highlights from the article: Moreover, a number of studies in recent years have drawn attention to the increasing intensity of heavy rainfall events, heat waves, and severe droughts in monsoon regions. It is imperative that scientists who study monsoon circulations improve the prediction of their start date or onset, the monsoon intensity, and how these variables respond to climate change. The 16 papers in this volume cover several regional monsoons including East Asia, South Asia and the South China Sea, Australian monsoon, and African Monsoon.

Based on the centennial-scale observations and re-analyses, this paper employs the ensemble empirical mode decomposition to separate the internal multidecadal variability (IMV) from the externally-forced variability of sea surface temperature (SST), and then defines new indices that represent the IMV of SST in the North Pacific (NPIMV) and South Pacific (SPIMV), respectively. The spatial structure of NPIMV/SPIMV shows remarkably positive SST anomaly only in the index-defined region; meanwhile, the temporal evolutions of NPIMV and SPIMV are uncorrelated, indicating their independence of each other. Both NPIMV and SPIMV play a critical role in the near-surface air temperature and rainfall over land in the Northern hemisphere, especially in the season when their intensity is the strongest. It is through teleconnection wave trains that NPIMV and SPIMV exert influences on remote regions. Results from another two rainfall datasets are found to be consistent in the majority of the Northern hemisphere in response to NPIMV/SPIMV, yet disagreement exists in certain regions due to large uncertainties of rainfall datasets. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of data centers' cost efficiency considering the potential of reusing the generated heat in district heating networks. We started by analyzing the requirements and heat reuse potential of a high performance computing data center and then we had defined a heat reuse model which simulates the thermodynamic processes from the server room. This allows estimating by means of Computational Fluid Dynamics simulations the temperature of the hot air recovered by the heat pumps from the server room allowing them to operate more efficiently. To address the time and space complexity at run-time we have defined a Multi-Layer Perceptron neural network infrastructure to predict the hot air temperature distribution in the server room from the training data generated by means of simulations. For testing purposes, we have modeled a virtual server room having a volume of 48 m3 and two typical 42U racks. The results show that using our model the heat distribution in the server room can be predicted with an error less than 1 °C allowing data centers to accurately estimate in advance the amount of waste heat to be reused and the efficiency of heat pump operation. [ABSTRACT FROM AUTHOR]

It is difficult to recover the residual heat from flue gas when supercritical carbon dioxide (S-CO2) cycle is used for a coal fired power plant, due to the higher CO2 temperature in tail flue and the limited air temperature in air preheater. The combined cycle is helpful for residual heat recovery. Thus, it is important to build an efficient bottom cycle. In this paper, we proposed a novel exergy destruction control strategy during residual heat recovery to equal and minimize the exergy destruction for different bottom cycles. Five bottom cycles are analyzed to identify their differences in thermal efficiencies (ηth,b), and the CO2 temperature entering the bottom cycle heater (T4b) etc. We show that the exergy destruction can be minimized by a suitable pinch temperature between flue gas and CO2 in the heater via adjusting T4b. Among the five bottom cycles, either the recompression cycle (RC) or the partial cooling cycle (PACC) exhibits good performance. The power generation efficiency is 47.04% when the vapor parameters of CO2 are 620/30 MPa, with the double-reheating-recompression cycle as the top cycle, and RC as the bottom cycle. Such efficiency is higher than that of the supercritical water cycle power plant. [ABSTRACT FROM AUTHOR]

In this paper, the solid desiccant adsorption packed bed with a three-stage internal cooling (ICSPB) has been proposed to improve the dehumidification efficiency and make a comparison with that of non-internal cooling. To investigate the performance of the ICSPB, the dehumidification capacity, dehumidification efficiency, water content of solid desiccant, moisture ratio of solid desiccant, temperature of solid desiccant and inlet and outlet air temperature difference were discussed in different conditions of inlet air and supplying water temperature. It was found that the dehumidification performance of the bed with internal cooling could be improved greatly in the low temperature and low humidity conditions, while in the high temperature and humid, the improvement was not obvious. With internal cooling, the dehumidification efficiency and the water content of the solid desiccant could be improved 59.69% and 110.7%, respectively, and the temperature of solid desiccant could be reduced 2.2 °C when the ICSPB operated at the inlet air temperature of 20 °C, inlet humidity of 55%, and water temperature of 14 °C. Moreover, the dehumidification performance at each stage of ICSPB was studied. It was found that, the first stage played the most important role in the dehumidification process. In addition, the calculation models that can be used to predict the moisture ratio and the temperature of solid desiccant were established on the test results. [ABSTRACT FROM AUTHOR]

Observational data collected during experiments, such as the planned Fire and Smoke Model Evaluation Experiment (FASMEE), are critical for evaluating and transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM into operational use. Historical meteorological data, representing typical weather conditions for the anticipated burn locations and times, have been processed to initialize and run a set of simulations representing the planned experimental burns. Based on an analysis of these numerical simulations, this paper provides recommendations on the experimental setup such as size and duration of the burns, and optimal sensor placement. New techniques are developed to initialize coupled fire-atmosphere simulations with weather conditions typical of the planned burn locations and times. The variation and sensitivity analysis of the simulation design to model parameters performed by repeated Latin Hypercube Sampling is used to assess the locations of the sensors. The simulations provide the locations for the measurements that maximize the expected variation of the sensor outputs with varying the model parameters. [ABSTRACT FROM AUTHOR]

The relevance and role of aesthetic, thermal and physical facets to climatic tourism potential over Algeria at 12.00 UTC (13.00 local time) are analyzed. This role is revealed using the Climate-Tourism-Information-Scheme (CTIS) elaborated for six Algerian cities having indisputable tourism potentiality and representing different regions and climate regimes: Coastline, Highland and Sahara zone. In this paper, the relevance of the use of the 10-day time-scale resolution of the physiologically equivalent temperature (PET) derived from the body-atmosphere energy balance as well as the importance of the CTIS at this time-scale resolution is illustrated. The CTIS diagrams produced concern the period 1986–2015 and comprise detailed information on the frequencies of the occurrence of different climatological and human biometeorological parameters throughout the year, which could help tourists to plan ahead their vacations. A significant upward trend in discomfort conditions, as well as a substantial decline in human thermal comfort acceptability, are observed during the period of the study. The obtained results could help enormously in the promotion of tourism and leisure services in the country as a highly promising economic sector in the future and those who are involved, such as tour operators, by diversifying their products through the provision of alternative types of tourism offerings in line with the climate conditions. [ABSTRACT FROM AUTHOR]

Accurate modeling for nonlinear and nonstationary rainfall-runoff processes is essential for performing hydrologic practices effectively. This paper proposes two hybrid machine learning models (MLMs) coupled with variational mode decomposition (VMD) to enhance the accuracy for daily rainfall-runoff modeling. These hybrid MLMs consist of VMD-based extreme learning machine (VMD-ELM) and VMD-based least squares support vector regression (VMD-LSSVR). The VMD is employed to decompose original input and target time series into sub-time series called intrinsic mode functions (IMFs). The ELM and LSSVR models are selected for developing daily rainfall-runoff models utilizing the IMFs as inputs. The performances of VMD-ELM and VMD-LSSVR models are evaluated utilizing efficiency and effectiveness indices. Their performances are also compared with those of VMD-based artificial neural network (VMD-ANN), discrete wavelet transform (DWT)-based MLMs (DWT-ELM, DWT-LSSVR, and DWT-ANN) and single MLMs (ELM, LSSVR, and ANN). As a result, the VMD-based MLMs provide better accuracy compared with the single MLMs and yield slightly better performance than the DWT-based MLMs. Among all models, the VMD-ELM and VMD-LSSVR models achieve the best performance in daily rainfall-runoff modeling with respect to efficiency and effectiveness. Therefore, the VMD-ELM and VMD-LSSVR models can be an alternative tool for reliable and accurate daily rainfall-runoff modeling. [ABSTRACT FROM AUTHOR]

The objective of the paper was to characterize the occurrence of cold days and cold waves in Poznań in the years 1966/67–2015/16, as well as to characterize thermal conditions in the city during selected cold waves in the years 2008/09–2015/16. The study was based on daily data on maximum and minimum air temperature for station Poznań-Ławica from the years 1966/67–2015/16 and daily air temperature values from eight measurement points located in the territory of the city in different types of land use from the years 2008/08–2015/16. In addition, to characterize thermal conditions during selected days forming cold waves, satellite images were used, on the basis of which the land surface temperature (LST) was calculated. A cold day was defined as a day with daily maximum temperature (Tmax) below the value of 5th annual percentile of Tmax, and a cold wave was defined as at least five consecutive cold days. The study showed an increase in Tmax in winter, which translated to a decrease in the number of cold days over the last 50 years, although the changes were not statistically significant. Thermal conditions in the city showed high variability in the winter season and during the analyzed cold waves. [ABSTRACT FROM AUTHOR]