Heavy Metal Pollution in Arid Urban Environments: Anthropogenic and Geogenic Insights from Road Dust in the United Arab Emirates.

Dust is a significant environmental concern due to its pervasive nature and potential health risks, particularly from heavy metals. This is exacerbated in urban areas, where dust can act as a reservoir for pollutants, posing risks to human health through various exposure pathways. This study aims to explore and compare the distribution of heavy metals in road dust from two distinct cities in the UAE: Dubai, a commercial hub, and Khor Fakkan, a coastal town with industrial activities.

Combined Particle Swarm Optimization and Reinforcement Learning for Water Level Control in a Reservoir.

This article focuses on the research and advancement of an optimal system for the automatic regulation of the water level in a reservoir to eliminate flooding in the area where it is located. For example, in this article, the regulation of the level in the Mariselu Reservoir from the dam in Bistrita-Nasaud County, Romania, was considered as a practical application. Industrial PID controller tuning provides robust and stable solutions; however, the controller parameters may require frequent tuning owing to uncertainties and changes in operating conditions.

Assessing Pollution with Heavy Metals and Its Impact on Population Health.

Pollution is one of the most important issues currently affecting the global population and environment. Therefore, determining the zones where stringent measures should be taken is necessary. In this study, Principal Component Analysis (PCA), Factor Analysis (FA), and t-distributed Stochastic Neighbor Embedding (t-SNE) were utilized for dimensionality reduction and clustering of data series containing the concentration of 10 heavy metals collected at 14 locations.

Outdoor Pollution Comparison Between Bucharest and Its Outskirts Using Mobile Laboratory.

This study presents a modern mobile laboratory to monitor outdoor air quality in Bucharest, Romania, with a focus on pollutants associated with transportation. Particulate matter (PM., PM), carbon monoxide (CO), ozone (O), sulfur dioxide (SO), nitrogen oxides (NO, NO), and BTEX compounds (benzene, toluene, ethylbenzene, and xylenes) were among the significant pollutants that were examined in the lab.

An investigation of the physic-mechanical properties of the expanded perlite mortars with thermal-activated concrete waste and microencapsulated paraffin.

In the transition to zero waste and sustainable development, it becomes essential to use phase change materials and recycled cement in construction projects to improve energy efficiency and encourage sustainable building practices. The primary goal of this study is to determine how the properties of expanded perlite mortars are affected when Portland cement is partially replaced with recycled cement, produced by thermally treating concrete waste at 550 °C. Recycled cement substituted Portland cement in various percentages (10 %, 30 %, and 50 %).

Investigation of Physical-Mechanical Properties and Microstructure of Mortars with Perlite and Thermal-Treated Materials.

This study aimed to obtain and characterize a mortar with perlite aggregate and thermal-treated materials that could substitute for Portland cement. First, the thermally treated materials were obtained by calcinating old Portland cement (OC-tt) and concrete demolition waste (CC-tt) at 550 °C, for 3 h. Second, plastic mortars with a perlite: cement volume ratio of 3:1 were prepared and tested for water absorption, mechanical strength, and thermal conductivity.

Optimizing Occupant Comfort in a Room Using the Predictive Control Model as a Thermal Control Strategy.

Thermal comfort strategies represent a very important aspect when it comes to achieving thermal comfort conditions. At the same time, recently, there has been a growing interest in user-centered building control concepts. Thus, this work focuses on developing a thermal control strategy that combines the restrictions related to achieving thermal comfort, expressed in terms of environmental parameters and specific factors of personal perception, with the objective of reducing energy consumption.

Effects of Micro- and Nanosilica on the Mechanical and Microstructural Characteristics of Some Special Mortars Made with Recycled Concrete Aggregates.

In this paper, we study the influence of densified microsilica and colloidal nanosilica admixtures on the mechanical strength and the microstructural characteristics of special mortars used for immobilizing radioactive concrete waste. The experimental program focused on the replacement of cement with micro- and/or nanosilica, in different proportions, in the basic composition of a mortar made with recycled aggregates. The technical criteria imposed for such cementitious systems, used for the encapsulation of low-level radioactive waste, imply high fluidity, increased mechanical strength and lack of segregation and of bleeding.

Advances in Water, Air and Soil Pollution Monitoring, Modeling and Restoration.

Global pollution demands continuous attention and concerted efforts to reduce its effects [...

Optimizing Greenhouse Design with Miniature Models and IoT (Internet of Things) Technology-A Real-Time Monitoring Approach.

The market for smart greenhouses has been valued at USD 1.77 billion in 2022 and is expected to grow to 3.39 billion by 2030.

Assessing Benzene and TVOC Pollution and the Carcinogenic and Noncarcinogenic Risks to Workers in an Industrial Plant in Southeastern Romania.

The article aims to analyze the pollution with Volatile Organic Compounds (VOC) emitted from the biggest refinery in Romania, using the daily and monthly series registered for two years in two sites on the industrial platform, and the carcinogenic and noncarcinogenic risks for workers at the industrial plant. Since the values of the basic statistics (minimum, maximum, and average) and outliers indicate that most recorded values exceed the maximum admissible limits established by law, the Peaks Over Threshold (POT) method was utilized to model the maximum values of the series and determine the return levels for benzene and total VOC (TVOC). Given the high values obtained for relatively short return periods, indicating potential danger for the workers, we assessed the noncarcinogenic and carcinogenic risks to benzene and TVOC exposure by computing the hazard index (HI) and lifetime cancer risk (LCR).

Downscaling MERRA-2 Reanalysis PM Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging.

This study offers a detailed analysis of the fine particulate matter (PM) series in the Arabian Gulf zone, employing three interpolation models, Inverse Distance Weighting (IDW), Bicubic Spline Smoothing (BSS) and Spatio-Temporal Kriging (STK). Unique advancements include the use of complete temporal records in IDW, the management of edge effects in S with synthetic buffer points, and the application of STK to detrended data residuals. The results indicated that the BBS, particularly adept at handling boundary conditions, significantly outperformed the other methods.

Reaction to fire, thermal, and mechanical properties of materials based on recycled paper granules bound with starch and clay mortar.

The objective of this work is to produce an ecologically friendly material for use in Ivory Coast's construction sector in the future. These materials should have good thermal qualities and be flame resistant in addition to helping to achieve interior comfort. The fundamental components under consideration are freely accessible in Ivory Coast and include clay mortar as a fire retardant, potato starch as a binder, and recycled paper granules as a filler.

Laboratory Scaled-Down Cementitious Concrete Model Used for Estimating the Bearing Capacity of a Bridge Girder Based on the Similitude Theory.

Bridges are structures subjected to multiple types of loads and combinations during their service life. The uncertainties linked with the materials' behavior and manufacturing processes often necessitate the testing of produced elements on a real scale. This is particularly true for bridge concrete precast girders, which are frequently tested to predict the ultimate carrying load.

Assessment of Properties and Microstructure of Concrete with Cotton Textile Waste and Crushed Bricks.

Cotton textile waste (CW) and crushed bricks (CB) are wastes generated by the textile and construction industries that cause adverse effects on the environment. This paper explores the effect of adding 1, 2, 5, and 10 wt.% of CW and CB, instead of natural sand under 1 mm (50 to 100 vol.

Human Health Risk Assessment to the Consumption of Medicinal Plants with Melliferous Potential from the Romanian South-Eastern Region.

This study presents the impact on human health by consuming medicinal herbs with high melliferous potential (HMPs) from botanical areas with different pollution levels. First, the bioaccumulation of the plants' parts has been determined. The study assessed the potential health risks associated with the ingestion of various mineral species (macroelements-K, Ca, Mg, Na; microelements-Fe, Mn, Cu, Zn, and one trace element Cd) from three types of HMPs ( (), (), and ()).

Parametric Study of the Influence of Nonlinear Elastic Characteristics of Rail Pads on Wheel-Rail Vibrations.

The rail pad is the elastic element between the rail and the sleeper that has the role of absorbing the mechanical stresses from the rail and reducing the vibrations and shocks generated by wheel-rail interactions. In this paper, the problem of the influence of the variability of the nonlinear load-deformation characteristic of rail pads (resulting from the manufacturing process) on wheel-rail vibrations is investigated. The limit load-deformation characteristics of a manufactured rail pad and the medium load-deformation characteristic resulting as the arithmetic mean of the two are considered.

An improved balanced replicated sampling design for preliminary screening of the tailings ponds aiming at zero-waste valorization. A Romanian case study.

The scope of this study consists of setting up of an integrated cost-effective sampling & laboratory analyses procedure which delineates sampling, sub-sampling and analytical uncertainties in case of fine-grained extractive waste deposits. This procedure is designed to support the decision makers towards fine-grained waste deposits upcycling and land reclamation. This procedure consists of a balanced replicated sampling design (BRSD) coupled with a three split levels ANOVA data processing.

Numerical Investigation of Very Low Reynolds Cross Orifice Jet for Personalized Ventilation Applications in Aircraft Cabins.

This study focuses on the numerical analysis of a challenging issue involving the regulation of the human body's microenvironment through personalized ventilation. We intended to first concentrate on the main flow, namely, the personalized ventilation jet, before connecting the many interacting components that are impacting this microenvironment (human body plume, personalized ventilation jet, and the human body itself as a solid obstacle). Using the laminar model and the large eddy simulation (LES) model, the flow field of a cross-shaped jet with very low Reynolds numbers is examined numerically.

Indoor Particle's Pollution in Bucharest, Romania.

Air pollution risk factor on human health was surpassed only by high blood pressure, tobacco use and poor diet. Total number of deaths due to air pollution worldwide was estimated to 6.67 million people in 2019.

Tsallis Entropy for Loss Models and Survival Models Involving Truncated and Censored Random Variables.

The aim of this paper consists in developing an entropy-based approach to risk assessment for actuarial models involving truncated and censored random variables by using the Tsallis entropy measure. The effect of some partial insurance models, such as inflation, truncation and censoring from above and truncation and censoring from below upon the entropy of losses is investigated in this framework. Analytic expressions for the per-payment and per-loss entropies are obtained, and the relationship between these entropies are studied.

Artificial Intelligence Models for the Mass Loss of Copper-Based Alloys under Cavitation.

Cavitation is a physical process that produces different negative effects on the components working in conditions where it acts. One is the materials' mass loss by corrosion-erosion when it is introduced into fluids under cavitation. This research aims at modeling the mass variation of three samples (copper, brass, and bronze) in a cavitation field produced by ultrasound in water, using four artificial intelligence methods-SVR, GRNN, GEP, and RBF networks.

Survey and Measurements of Indoor Environmental Quality in Urban/Rural Schools Located in Romania.

Taken as a whole, the indoor environmental quality (IEQ) is a concept that deals not only with thermal conditions, but it also goes much further, because it includes indoor air quality (IAQ), illuminance or acoustic comfort. Among the different categories of buildings, schools are one of the most important in society especially because future generations are spending more than 6 h/day and ensuring them a healthy and comfortable environment must be top priority. The purposes of this research were to better understand school children's IEQ preferences and needs in classrooms and to compare these among rural versus urban respondents.

A spatiotemporal ensemble machine learning framework for generating land use/land cover time-series maps for Europe (2000-2019) based on LUCAS, CORINE and GLAD Landsat.

A spatiotemporal machine learning framework for automated prediction and analysis of long-term Land Use/Land Cover dynamics is presented. The framework includes: (1) harmonization and preprocessing of spatial and spatiotemporal input datasets (GLAD Landsat, NPP/VIIRS) including five million harmonized LUCAS and CORINE Land Cover-derived training samples, (2) model building based on spatial k-fold cross-validation and hyper-parameter optimization, (3) prediction of the most probable class, class probabilities and model variance of predicted probabilities per pixel, (4) LULC change analysis on time-series of produced maps. The spatiotemporal ensemble model consists of a random forest, gradient boosted tree classifier, and an artificial neural network, with a logistic regressor as meta-learner.