Performance evaluation of solar-powered atmospheric water harvesting using different glazing materials in the tropical built environment: an experimental study

Water scarcity is a global issue, and its severity is expected to worsen in the near future, prompting further efforts to find new sources of freshwater. Solar-Powered Atmospheric Water Harvesting (SPAWH) is a promising passive approach for atmospheric water generation. This study aims to examine the thermal performance of different glazing materials and water production in SPAWH. The research consists of two phases: a laboratory test of various glazing materials and an experimental study to assess system efficiency in producing water in the tropics. The preliminary results indicated that glass demonstrated better thermal performance than acrylic in the lab, with higher thermal conductivity and less heat loss. The experimental findings showed that the maximum water produced by the proposed SPAWH (60 cm length, 60 cm width and 30 cm height) placed on a 30° tilt angle using glass (3 mm) and acrylic (3 mm) was 0.61 L/m2/day and 0.44 L/m2/day, respectively. The cost analysis revealed that produced water costs $0.18/kg for glass and$0.40/kg for acrylic, respectively. Atmospheric water could be harvested using SPAWH in the tropics, which would help to provide new opportunities for sustainable water supplies and development in these regions

Exploring the environmental performance of liquid glass coating using Sol-Gel technology and responsive Venetian blinds in the tropics

The dynamic nature of tropical skies presents challenges for the built environment due to the momentous fluctuations and instability in solar irradiance and illuminance levels that cause limitations in responding to the needs of the indoor environment. The study aims to investigate the performance of daylighting strategies using liquid glass coating and responsive Venetian blinds in an office building in the tropics. The objective of this study is to systematically examine the impacts of proposed strategies on indoor environmental conditions. The study was experimentally investigated by utilising field measurements in full-scale cellular offices in a real environment and simulation using Radiance. The results indicated that responsive Venetian blinds provided steady daylight levels between 375 lx and 588 lx in the centre of the room, while a further integration with liquid glass coating provided a glare control with a maximum of 33.71% (Imperceptible) using Daylight Glare Probability. The indoor air temperature was reduced by 3.42 °C with liquid glass coating and 2.85 °C with responsive Venetian blinds. The outputs of assessing the performance of static and responsive strategies demonstrated new findings that are significant to developing these strategies in the tropics

Freshwater microalgae-based wastewater treatment under abiotic stress

Wastewater treatment by microalgae is an eco-friendly and sustainable method for pollutant removal and biomass generation. Microalgae production under abiotic stress (such as salinity/salt stress) has an impact on nutrient removal and fatty acid accumulation. In this study, a freshwater microalgal strain (Desmodesmus communis GEEL-12) was cultured in municipal wastewater with various NaCl concentrations (ranging from 25–150 mM). The growth kinetics and morphological changes of the microalgae were observed. The nutrient removal, salinity change, fatty acid composition, and biodiesel quality under various groups were also investigated. The maximum growth of D. communis GEEL-12 was observed in the control group at 0.48 OD680nm. The growth inhibition was observed under high salt conditions (150 mM), which showed poor tolerance with 0.15 OD680nm. The nitrogen (N) and phosphorus (P) removal significantly decreased from 99–81% and 5.0–5.9% upon the addition of 100–150 mM salt, respectively. Palmitic acid (C16:0) and stearic acid (C18:0) were the most common fatty acid profiles. The abundance of C18:0 enhanced from 49.37%–56.87% in D. communis GEEL-12 upon high NaCl concentrations (100–150 mM). The biodiesel quality index of D. communis GEEL-12 under 50–75 mM salt concentrations reached the levels advised by international standards

Dynamic training rate for backpropagation learning algorithm

In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. The stop training or limited error was determined by1.0 e-

A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective

Applications of the Internet of Things (IoT) are rapidly utilized in smart buildings and smart cities to reduce energy consumption. This advancement has caused a knowledge gap in applying IoT effectively by experts in the built environment to achieve energy efficiency. The study aims to provide an extensive review of IoT applications for energy savings in buildings and cities. This study contributes to the field of IoT by guiding and supporting built environment experts to utilize IoT technologies. This paper performed a thorough study using a systematic review that covered an overview of IoT concepts, models, applications, trends and challenges that can be encountered in the built environment. The findings indicated limitations in developing IoT strategies in buildings and cities by professionals in this field due to insufficient comprehension of technologies and their applied methods. Additionally, the study found an indefinite implementation and constraints on using IoT when integrated into the built environment. Finally, the study provides critical arguments and the next steps to effectively utilize IoT in terms of energy efficiency

Modeling of Chloride Binding Capacity in Cementitious Matrices Including Supplementary Cementitious Materials

The improvement in the chloride binding capacity of concrete has been shown to increase corrosion resistance. The addition of supplementary cementitious materials (SCMs) to Portland cement has been proven to increase the binding capacity, except for silica fume, whereas the impact of chemical additives is not extensively addressed in the literature. This work studies the influence of SCMs and chemical additives, i.e., calcium nitrite inhibitor (CNI), migrating corrosion inhibitor (MCI), and Caltite as a hydrophobic material, on binding capacity. The addition of both corrosion inhibitors (MCI and CNI) has minimal effect on the binding capacity, while the addition of Caltite reduces the binding capacity by limiting the contact of the samples with the salt in water due to its hydrophobic nature. In addition, the study compares the performance of the available fitting–binding models against the available experimental work in the literature, and shows that the Freundlich isotherm is the best fitting model for describing the relationship between the binding capacity and the free chloride. The study further relates the binding capacity to different compositions in cement and SCMs, and shows, by conducting quantitative analysis, that the Al2O3 content is the dominant factor affecting the binding capacity. Finally, this work proposes a new model, which uses Al2O3 content and free salt concentration to predict the bound chloride. The model shows adequate correlations to the experimental work and, further, can be used in service-life modeling of concrete

Modeling of Chloride Binding Capacity in Cementitious Matrices Including Supplementary Cementitious Materials

The improvement in the chloride binding capacity of concrete has been shown to increase corrosion resistance. The addition of supplementary cementitious materials (SCMs) to Portland cement has been proven to increase the binding capacity, except for silica fume, whereas the impact of chemical additives is not extensively addressed in the literature. This work studies the influence of SCMs and chemical additives, i.e., calcium nitrite inhibitor (CNI), migrating corrosion inhibitor (MCI), and Caltite as a hydrophobic material, on binding capacity. The addition of both corrosion inhibitors (MCI and CNI) has minimal effect on the binding capacity, while the addition of Caltite reduces the binding capacity by limiting the contact of the samples with the salt in water due to its hydrophobic nature. In addition, the study compares the performance of the available fitting–binding models against the available experimental work in the literature, and shows that the Freundlich isotherm is the best fitting model for describing the relationship between the binding capacity and the free chloride. The study further relates the binding capacity to different compositions in cement and SCMs, and shows, by conducting quantitative analysis, that the Al2O3 content is the dominant factor affecting the binding capacity. Finally, this work proposes a new model, which uses Al2O3 content and free salt concentration to predict the bound chloride. The model shows adequate correlations to the experimental work and, further, can be used in service-life modeling of concrete

Analysis of patients with end-stage renal disease on dialysis in Tabuk City, Saudi Arabia: A single-center, three-year retrospective study

This study was performed to analyze various demographic data such as age, gender, nationality, status of the patients, and the causes of end-stage renal disease (ESRD) of 349 patients who were undergoing hemodialysis (HD) during the period from January 2013 to December 2015 at the Dialysis Center of King Khalid Hospital in Tabuk City. One hundred and fifty-two patients (43.6%) were on HD in 2015. Age of the patients ranged from 9 to 93 years and the mean age was 51.3 ± 17.6 years. Majority of the patients, i.e., 140 (40.1%) were in the age group of 40–59 years, followed by the age group of 60–79 years by 27.8% (97 patients). Saudis constituted 84.2% (294) and non-Saudis accounted 15.8% (55) of the patients over the years studied. There were 198 males (56.7%) and 151 females (43.3%). The death rate in 2014 was 6.2%, whereas it increased in 2015 to 10.5%. The high escape rate (10.3%) of patients was in 2014. Diabetic nephropathy was the most common cause of ESRD, accounting for 30.4% of all cases, followed by unknown etiologies accounting for 25.2%. Nearly 22.6% of all ESRD cases had hypertension. Primary glomerular disease was seen in 8.9% and obstructive uropathy in 3.7%. Other causes constituted 7.4% of the cases. The data of ERSD patients in Tabuk City are comparable with that of other regions of the Kingdom of Saudi Arabia. We conclude that analysis studies of HD centers help to understand the problems and the needs of the patients, find the solutions, and create a connection between the consumers and health-care providers

A generalized framework for quantifying and monitoring the severity of meteorological drought

The current study proposes a new framework for quantifying and monitoring the severity of meteorological drought. The proposed framework consists of three phases. The first phase of the framework uses K-component Gaussian Mixture Distribution (GMD) in the computation. The second phase is mainly based on the dissimilarity matrix-based clustering using C-index and Monte Carlo Feature-based Selection (MCFS) method. The third phase uses the Markov chain, transition probabilities and a non-homogeneous Poisson process under the Bayesian estimation. The Relative Importance (RI) values are used to choose appropriate stations. The Deviance Information Criteria (DIC) is used to check model suitability, and Root Mean Square Error (RMSE) is utilized for determining model performance. The proposed framework is validated to the 52 meteorological stations in Pakistan for 49 years from 1968 to 2016. Moreover, the outcomes of the current analysis provide insight to quantify and monitor meteorological drought comprehensively and accurately