Outdoor Environments Research Articles

Support for regulating smoking in private and public places by adults who currently smoke and recently quit smoking in Spain.

While indoor smoking restrictions are common, outdoor restrictions are still rare. We explored opinions and support for regulating smoking in different indoor and outdoor environments among adults who smoke and those who recently quit smoking, in Spain. The 2021 ITC EUREST-PLUS Spain Survey is a cross-sectional study conducted among a nationally representative sample of 1006 adults aged ≥18 years who smoked cigarettes (n=867) or had recently quit smoking (n=139). Using Poisson regression with robust variance, we estimated adjusted prevalence and prevalence ratios of favorable opinions on regulating smoking in different indoor and outdoor environments and support for regulation in unregulated outdoor environments, by sociodemographic and smoking-related characteristics. There were highly favorable opinions for regulating smoking in places with minors (>95% in primary and secondary playgrounds, and cars with pre-school children and minors) and outdoor transportation (60-80%). There were less favorable opinions for regulating smoking in outdoor terraces of bars/pubs and restaurants (15-20%). Support for further total outdoor regulations on smoking was moderate for markets/shopping centers, public building entrances and swimming pools (40-60%), and low for restaurants/bars/pubs (29.2%). Having quit smoking, having no significant others who smoke and/or believing that cigarette smoke is harmful to others, were factors positively associated with favorable opinions and support for regulating smoking. The settings in Spain with the most favorable opinions for regulation among adults who smoke and have recently quit smoking are places with minors, private cars with others and outdoor areas of public transportation, while the settings with the least favorable opinions were outdoor terraces of bars, pubs, and restaurants. Support for further total outdoor smoking bans is generally moderate, but low for restaurants, bars, and pubs. Overall, these findings suggest the feasibility of extending smoke-free policies to other public and private settings to protect others from tobacco smoke exposure.

Atmospheric aldehydes in indoor and outdoor environments impacted by combustion emissions of diesel/biodiesel mixtures

The temporal evolution of air pollutants concentrations inside a semi-closed bus station has been investigated since 2002 until 2023 to understand the impact of direct combustion emissions from buses using diesel/biodiesel fuel blends (B3-B12). Carbonyl compounds concentrations were evaluated, which predominance of acetaldehyde and formaldehyde. It is known that acrolein emission increases with the addition of biodiesel to diesel. However, the determination of acrolein by the official method is compromised due to coelution with acetone on liquid chromatographic separation. In this work, with adaptation of the mobile phase, acrolein was separated adequately and could be determinate in samples obtained in the same bus station while the vehicles had been using B12 fuel blends. Concomitantly, samples were collected outside the station to compare indoor and outdoor air quality. Formaldehyde, acetaldehyde and acrolein were detected in both environments. Aldehydes concentration was higher indoor than outdoors. There are indications that acrolein levels may increase with higher proportions of biodiesel in diesel blends. This study valuable information for future studies on air quality and vehicular emissions.

A typical meteorological day database of solar terms for simplified simulation of outdoor thermal environment on a long-term

The simulation of the outdoor thermal environment long-term, represented by the annual conditions, can describe outdoor thermal environment characteristics more completely. To simplify the simulation, Typical Meteorological Year (TMY) or Principal Component Analysis (PCA) methods are often used to generate a Typical Meteorological Day (TMD) as input conditions for a simplified simulation of the outdoor thermal environment in the long term. However, the results of these typical days are accidental, the time interval between the typical days is heterogeneous, and these typical days cannot be linked together to represent a data sequence used to describe meteorological features in the long term. By combining knowledge of Solar Terms in the traditional Chinese calendar with the CSWD (the Chinese standard year) method, a meteorological element data sequence of a typical weather day (Solar Terms Typical Meteorological Day, STTMD) can be generated. There are 24 typical days obtained by the STTMD method. In the traditional Chinese calendar, they have a definite time order, and the time interval between the typical days is about 15 days. Connecting these typical days can form a hypothetical meteorological year, which is used to simplify the description of the annual meteorological characteristics with the maximum probability of occurrence. Based on meteorological observation data from 1981 to 2010, the STTMD data series of 61 stations in China were generated. These data were used to form a simple national climate division, and then the meteorological representation of different divisions was analyzed. Meteorological representativeness analysis for these subtions indicated the good accuracy of STTMD data. The method can simplify the numerical simulation process for those studied on long-term and can be extended to applications such as outdoor comfort evaluation and urban building energy consumption.

Capturing the social values of a mix-used university campus outdoor: An assessment of the Agricultural University of Tirana

Although mixed-use campuses are recognized by designers, little attention is paid to the social values that their outdoor environment generates for the wider community. Aiming to identify social values, the methodology used in this study includes a survey that is applied via an online questionnaire (N=156) to explore users’ perceptions about the values the campus produces to translate into indicators of wellbeing. This study’s aim is to identify indicators of wellbeing that can capture campus social value, referring to a continuously changing campus (Agricultural University of Tirana). The results indicate that the social and cultural benefits that come from a mixed-use campus are related to the adequacy of physical outdoor environments and social activities. However, compared to mixed-use spaces, outdoor spaces that preserve the functions of agricultural backgrounds (as originally designed) have higher social values. We suggest that both physical and non-physical determinants play a basic role in enhancing social interaction (this is a strong indicator), so they must be included in the policies and strategies of the higher education systems.

Role of Urban Trees in Enhancing the Thermal Comfort of Rapidly Urbanizing Cities: An Analysis of Tropical Asian Tree Species Based on Physiological Equivalent Temperature (PET)

AbstractBackgroundThermal comfort significantly influences well-being, productivity, and living conditions in outdoor environments, particularly in rapidly urbanizing, warm, humid tropical climates. This study assessed the influence of 5 five common urban tree species (Cassia fistula,Tectona grandis,Plumeria obtusa,Mangifera indica, andTerminalia catappa) on outdoor thermal comfort, using the physiological equivalent temperature (PET) index in Colombo, Sri Lanka, as a case study for a tropical humid city.MethodsField data collection encompassed measuring air and surface temperature, relative humidity, wind velocity, solar radiation, cloud cover, and sky view factor under tree canopies and adjacent exposed areas. The RayMan model was employed to estimate PET in both areas.ResultsOur findings indicated that PET was consistently higher in exposed areas compared to under the tree canopy, with an average difference of 5.61 °C. Among tree parameters, sky view factor (SVF) demonstrated the most significant correlation with thermal comfort, followed by crown diameter and tree height. Furthermore, notable variations in thermal comfort were observed among tree species, withTerminalia catappaoutperformingPlumeria obtusa, particularly on sunny days.ConclusionRegression analysis highlighted the importance of integrating trees with large crowns and low SVF to create thermally comfortable outdoor spaces. Consequently,Terminalia catappaemerged as the most suitable tree species for enhancing thermal comfort in Colombo’s outdoor urban areas out of the 5 selected species. These insights will aid in selecting appropriate tree species and parameters, fostering improved outdoor thermal comfort in tropical humid cities, and facilitating sustainable urban planning and design strategies.

Investigation of passenger thermal satisfaction across multi-space transitions in high-speed railway stations: A case study in cold regions of China

Passengers in high-speed railway stations experience multiple spatial transitions; however, existing research has typically examined thermal comfort in isolation, neglecting the entire sequence of thermal experiences. This study investigates passenger thermal comfort throughout the departure process, specifically analyzing two entry modes: Mode 1 (entry via the outdoor square) and Mode 2 (entry via the underground passage). Utilizing behavioral data from 17,354 passengers surveyed in a typical high-speed railway station, we replicated these conditions in climate chamber experiments. Participants were exposed to 30 combinations of outdoor environments and four indoor temperatures (24 °C, 26 °C, 28 °C, and 30 °C). Thirty subjects, dressed in 0.49 clo insulation garments, assessed thermal satisfaction (TSAT) in each space and overall thermal satisfaction (OTSAT) for the departure process through questionnaires. Results indicated that high outdoor temperatures led to lower satisfaction in Mode 1 compared to Mode 2. Strong correlations were observed between TSAT in the waiting room and check-in area with OTSAT, underscoring their significant impact on OTSAT. Optimal thermal sequences were identified as O-26-26-26-24 for Mode 1 and U-28-26-24-24 for Mode 2, achieving OTSAT values of 1.11 and 1.12, respectively. The study also proposed two effective thermal sequences: a downward trend and a fluctuation trend, highlighting the benefits of initial discomfort followed by improvement. The recency effect emphasized the importance of effective thermal management in the waiting room and check-in area to enhance OTSAT. These findings provide valuable insights for optimizing thermal environment control in high-speed railway stations, balancing passenger comfort with energy efficiency.

Rural heat island effect of centralized residences in China: Mitigation through localized measures

China has implemented a Centralized Rural Policy since 2004 to enhance energy efficiency. However, this has led to the potential creation of a Rural Heat Island (RHI) effect, which could diminish outdoor thermal comfort and increase building energy consumption during hot summers. While most studies on heat island effect focus on spatiotemporal variations and heat mitigation measures, there is limited research on rural areas, particularly the special layout of rural residences. Additionally, most studies only consider the outdoor environment, overlooking indoor thermal comfort and building energy consumption. Therefore, in order to investigate the RHI effect and assess the efficacy of localized heat mitigation measures, this study analyzed 22 types of courtyard layout patterns in a typical centralized village in northern China through detailed field measurements and performance simulations. The results show an obvious heat island effect in the rural centralized residences, where residential zones recorded average temperatures of 1.6 °C higher than those of rural boundaries. Courtyards featuring a south wing significantly alleviated outdoor thermal stress, reducing the discomfort time of extreme Physiological Equivalent Temperature (PET) by 1.5 h compared to those courtyards with a wall. Among the four localized heat mitigation measures examined, the featured black fabric shade performs best for its effectiveness in mitigating outdoor thermal stress, capable of reducing the courtyard's maximum Mean Radiant Temperature (Tmrt) by 21.5 °C and decreasing the duration of extreme PET by 2 h. Photovoltaic modules installed on the roof not only generate energy but also alleviate outdoor thermal stress, reducing the maximum Tmrt by 12.9 °C and lowering 23 % to 28 % daily energy demand, making them highly suitable for deployment in rural areas with high rates of energy poverty. The simulated results indicate that these localized heat mitigation measures mutually reinforce each other in reducing the RHI effect. The combination of four heat mitigation measures can reduce PET by up to 20 % and EUI by up to 44 % compared to the original courtyard. Incorporating these localized strategies into planning practice enables rural planners and policymakers to develop effective interventions against the RHI effect.

High-speed aerial grasping using a soft drone with onboard perception

Contrary to the stunning feats observed in birds of prey, aerial manipulation and grasping with flying robots still lack versatility and agility. Conventional approaches using rigid manipulators require precise positioning and are subject to large reaction forces at grasp, which limit performance at high speeds. The few reported examples of high-speed aerial grasping rely on motion capture systems, or fail to generalize across environments and grasp targets. We describe the first example of a soft aerial manipulator equipped with a fully onboard perception pipeline, capable of robustly localizing and grasping visually and morphologically varied objects. The proposed system features a novel passively closed tendon-actuated soft gripper that enables fast closure at grasp, while compensating for position errors, complying to the target-object morphology, and dampening reaction forces. The system includes an onboard perception pipeline that combines a neural-network-based semantic keypoint detector, a state-of-the-art robust 3D object pose estimator, and a fixed-lag smoother to estimate the pose of known objects. The resulting pose estimate is passed to a minimum-snap trajectory planner, tracked by an adaptive controller that fully compensates for the added mass of the grasped object. Finally, a finite-element-based controller determines optimal gripper configurations for grasping. Experiments on three different targets confirm that our approach enables dynamic, high-speed, and versatile grasping, all of which are necessary capabilities for tasks such as rapid package delivery or emergency relief. We demonstrate fully onboard vision-based grasps of a variety of objects, in both indoor and outdoor environments, and up to speeds of 2.0 m/s—the fastest vision-based grasp reported in the literature. Finally, we take a major step in expanding the utility of our platform beyond stationary targets, by demonstrating motion-capture-based grasps of targets moving up to 0.3 m/s, with relative speeds up to 1.5 m/s.

Optimization Study of Outdoor Activity Space Wind Environment in Residential Areas Based on Spatial Syntax and Computational Fluid Dynamics Simulation

In the context of increasing global energy shortages and climate change, the human living environment, as a crucial component of residents’ daily lives, has garnered growing attention from the academic community. Research on residential environments is vital for promoting the sustainable development of urban construction and constitutes an important aspect of sustainable development studies. This study focuses on the optimization strategy for the outdoor activity space wind environment in the Xihuayuan residential area in Lanzhou city, utilizing spatial syntax analysis and Computational Fluid Dynamics (CFD) simulation technology. Firstly, the outdoor activity space is analyzed for visibility and spatial accessibility using DepthmapX0.6 software. Then, the outdoor wind environment in the residential area is simulated using PHOENICS 2018 software, and the analysis is conducted on outdoor spaces with a poor wind environment in terms of high accessibility. The results indicate that residents’ outdoor comfort in these spaces is poor, highlighting the urgent need for improvement in the wind environment. This research attempts to optimize the wind environment in high-accessibility spaces within the residential area by improving building layout, orientation, and height. The simulation results after optimization demonstrate an increase in the overall average wind speed to 1.44 m/s, with the proportion of spaces with a good wind environment in high-accessibility areas during summer rising from 33.4% to 59.2%. The optimization strategy effectively improves the wind environment in high-accessibility areas of the residential area.

A novel pathloss prediction and optimization approach using deep learning in millimeter wave communication systems

Millimeter wave communication systems design requires accurate pathloss prediction as well as optimization. Traditional pathloss models gives less accuracy therefore pathloss models using deep learning is alternative solution for traditional method. These methods overcome the time consuming pathloss prediction parameter prediction based on large dataset which is available for different frequencies. In this proposed work, for prediction of pathloss, Convolutional Neural Network (CNN) and for optimization of pathloss Particle Swarm Optimization (PSO) is proposed. Towards implementation of the same, outdoor scenario with two roads and one cross section is used and dataset is generated using DeepMIMO generic dataset. The simulation result shows that using optimization technique reduces pathloss and CNN give accurate prediction of 95.7 %. Furthermore, root mean square error value of 6.6 dB has been achieve which is less in comparison to alternative approaches designed for outdoor environments. The forthcoming development of multifrequency path loss models has sparked significant interest due to their forecasting ability to support higher frequency bands and address blockage scenarios within future wireless networks.

An algorithm for large-span flexible bridge pose estimation and multi-keypoint vibration displacement measurement

Traditional visual vibration measurement methods face limitations in dynamic outdoor environments, making accurate multi-point vibration measurements challenging for the targeted objects. In this paper, a visual vibration measurement algorithm for large-span bridges is proposed by anthropomorphizing the bridge target and introducing key point detection at the same time. Firstly, the algorithm utilizes a convolutional neural network to extract multi-scale feature information from the image sequence of the bridge model. Secondly, to enhance target detection accuracy, a coordinate attention (CA) mechanism is incorporated, and the shape intersection over union (SIoU) loss function replaces the original loss function. Finally, the algorithm integrates the density-based spatial clustering of applications with noise (DBSCAN) and tracking algorithms to achieve precise localization of bridge targets. Vibration displacement data were extracted from a large-span suspension bridge structure in an outdoor environment and analyzed quantitatively and qualitatively. The vibration displacement curves obtained in this study show the highest level of agreement with the standard displacement signals, with a mean absolute percentage error of 0.5170% for the cable-stayed bridge model, 1.3822% for the Humen Bridge, and 3.2263% and 1.6982% for the Longjiang Bridge.

Photocatalytic activity of TiO2:TiN nanocomposite films prepared by DC reactive sputtering technique for air purification

This study concerns the production of advanced materials and a novel technique for enhancing photocatalytic efficiency, focusing specifically on the purification of air contaminated with methane gas. Titanium dioxide:Titanium nitride (TiO2/TiN) nanocomposite films were prepared by dc reactive magnetron sputtering of highly-pure titanium sheet in presence of oxygen and nitrogen as reactive gases with optimized mixing ratios to produce the composite structures. The structural, morphological, and optical characteristics of the prepared nanocomposites were determined and analyzed. The primary goal of this study was to enhance the photocatalytic activity of such nanocomposites against methane gas pollution. It is observed that increasing the nitrogen content in the TiO2:TiN nanocomposite structure led to notable improvements in photocatalytic efficiency. Specifically, when these nanocomposites were subjected to a UV light, they exhibited enhanced photocatalytic activity in the removal of methane gas from the surrounding air, which demonstrates a direct correlation with increased nitrogen (N) content in the composite structure. These nanocomposites are reasonably promising in removing harmful gases and pollutants present in indoor and outdoor environments. This exploration not only sheds light on the remarkable potential of TiO2:TiN nanocomposites for air purification but also highlights the importance of innovative techniques, such as dc reactive magnetron sputtering in the field of materials science and engineering as well as in environmental remediation.

A study of the impact of entrance space on indoor air quality in vernacular dwellings in desert areas during sandstorms

Alxa League, located in the western part of Inner Mongolia, China, frequently suffers from sandstorms. Such dusty conditions result in sharp increases in respirable particulate matter (PM10) concentration in outdoor and indoor environments, posing a significant health risk to local inhabitants. Vernacular dwellings in this area feature a specific floor plan that includes an entrance space to safeguard indoor air quality during sandstorms while being compatible with the local climate. This study utilises CONTAM, a multizone indoor air quality and ventilation analysis computer program, and field measurements to quantitatively evaluate the effectiveness of the entrance space in protecting indoor air quality against ambient PM10 pollution under both dusty and normal conditions. The simulation results reveal that the entrance space can effectively mitigate PM10 pollution in the middle room, lowering the average concentration from 47.0 μg/m3 to 37.5 μg/m3 during dust periods. However, PM10 pollution may increase in the entrance space, reaching an average concentration of up to 70.0 μg/m3. Experimental outcomes align with the simulated results. Given that construction activities exacerbate desertification and frequent sandstorms, the above findings help identify the optimal design strategies for energy-efficient green vernacular dwellings in the targeted desert area, promoting environmental harmony and addressing climate change challenges.

Machine Learning for Real-Time Building Outdoor Wind Environment Prediction Framework in Preliminary Design: Taking Xinjiekou Area of Nanjing, China as the Case

The incorporation of physical environmental performance as a primary consideration in building design can facilitate the harmonization of the built environment with the surrounding site and climate, enhance the building’s environmental adaptability and environmental friendliness, and contribute to the achievement of energy-saving and emission-reduction objectives through the integration of natural lighting and ventilation. General computational fluid dynamics (CFD) can help architects make accurate predictions and effectively control the building’s wind environment. However, CFD integration into the design workflow in the preliminary stages is frequently challenging due to program uncertainty, intricate parameter settings, and substantial computational expenses. This study offers a methodology and framework based on machine learning to overcome the complexity and computational cost barriers in simulating outdoor wind environments of buildings. In this framework, the machine learning model is trained using an automated CFD simulation system based on Butterfly and implemented within the Rhino and Grasshopper environment. This framework provides real-time simulation feedback within the design software and exhibits promising accuracy, with a Structural Similarity Index Measure (SSIM) ranging from 90–97% on a training dataset of 1200 unique urban geometries in Xinjiekou Area of Nanjing, China. Furthermore, we programmatically integrate various parts of the simulation and computation process to automate multiscenario CFD simulations and computations. This automation saves a significant amount of time in producing machine-learning training sets. Finally, we demonstrate the effectiveness and accuracy of the proposed working framework in the design process through a case study. Although our approach cannot replace CFD simulation computation in the later design stages, it can support architects in making design decisions in the preliminary stages with minimal effort and immediate performance feedback.

Refining Children's exposure assessment to NO2, SO2, and O3: Incorporating indoor-to-outdoor concentration ratios and individual daily routine

Exposure to air pollutants like sulfur dioxide (SO2), nitrogen oxides (NOx), and ozone (O3) is associated with adverse health effects, particularly with exacerbations of asthma symptoms and new asthma cases in both children and adults. While fixed-site monitoring (FSM) stations are commonly used in air pollutant exposure studies, they may not fully capture personal exposures due to limitations such as inadequate consideration of daily routines and indoor/outdoor concentration variations. In this study, to enhance the accuracy of personal exposure calculated by using FSM data, individual's daily activity routine, encompassing both indoor and outdoor environments, were incorporated by using indoor-to-outdoor concentration ratios. Three methodologies were compared to assess the accuracy of exposure calculations: (i) direct exposure determination employing passive samplers (PS), (ii) personal exposure calculated using FSM data alone, and (iii) personal exposure calculated using FSM data refined by integrating local average individual daily activity routines and indoor-to-outdoor ratios. The results demonstrate that the refined method (iii) yields substantial improvements in estimated exposure levels, reducing the average error from 1.4% to 0.4% for NO2, from 72.1% to 12.7% for SO2, and from 323.4% to 24.9% for O3.

An Effective LiDAR-Inertial SLAM-Based Map Construction Method for Outdoor Environments

An Effective LiDAR-Inertial SLAM-Based Map Construction Method for Outdoor Environments

EXPERIMENTAL INVESTIGATION OF NATURAL CIRCULATING SOLAR ENERGY SYSTEM INCLUDING A PARABOLIC TROUGH SOLAR COLLECTOR

Abstract The most common natural flow water heating systems are in one-ended inclined pipes today. In this study, it is aimed to investigate the natural circulation solar energy system experimentally with parabolic trough solar collector. For this purpose, a natural circulation solar energy system including a parabolic trough solar collector that follows the sun in one dimension on the N-S axis in the outdoor environment has been established. Experiments were conducted on different dates. The radiation values coming into the opening of the moving collector were calculated. With the SolTrace program, it has been found that 56 % of this radiation can reach the vacuum tube glass pipe in the focus of the collector. In addition, the Rayleigh number was calculated for each experiment for the section of the glass tube close to the tank inlet, and it was monitored whether there was natural circulation throughout the experiment. As a result, the average Rayleigh number in the experiments conducted on 13 February, 31 March, 24 April, 23 May, 9 June, and 6 July was 1.4E+06, 7.6E+05, 7.8E+04, 2.2E+04, 3.1E+05, respectively. and calculated as 2.8E+05. In the experiments on May 23 and April 24, when the cooling system was open, it was observed that the Rayleigh number constantly dropped below the critical value. In other experiments, the situation is the opposite, and the natural flow is continuous.

Assessing the effectiveness of bioclimatic strategies in improving thermal comfort and reducing energy consumption in a house located in a desert climate

This article examined the effectiveness of bioclimatic strategies to enhance thermal comfort and decrease energy consumption in a desert-climate residence. The study assessed the impact of thermal insulation, natural ventilation, and phase-change materials (PCMs) over a year, with each strategy evaluated both independently and in combination. Monthly energy bills were analyzed to determine the impact of these strategies. The results indicated substantial reductions in energy costs, with decreases of up to 50% during transitional seasons; however, the complete elimination of heating and cooling systems was not feasible due to significant thermal phase differences between indoor and outdoor environments. Further analysis of thermal discomfort hours revealed that increasing insulation thickness during specific seasons could mitigate peak heat intensity and delay its occurrence, thus extending periods of comfort and reducing discomfort hours. Despite these improvements, some periods of thermal distress persisted during the warmest months, underscoring the necessity for a balanced approach to climate adaptation strategies. Overall, the implementation of these strategies proved effective in improving comfort and reducing energy usage in desert-climate homes, although they do not fully negate the need for traditional heating and cooling systems.

Air pollution, traffic noise, mental health, and cognitive development: A multi-exposure longitudinal study of London adolescents in the SCAMP cohort

BackgroundThere is increasing evidence that air pollution and noise may have detrimental psychological impacts, but there are few studies evaluating adolescents, ground-level ozone exposure, multi-exposure models, or metrics beyond outdoor residential exposure. This study aimed to address these gaps. MethodsAnnual air pollution and traffic noise exposure at home and school were modelled for adolescents in the Greater London SCAMP cohort (N=7555). Indoor, outdoor and hybrid environments were modelled for air pollution. Cognitive and mental health measures were self-completed at two timepoints (baseline aged 11–12 and follow-up aged 13–15). Associations were modelled using multi-level multivariate linear or ordinal logistic regression. ResultsThis is the first study to investigate ground-level ozone exposure in relation to adolescent executive functioning, finding that a 1 interquartile range increase in outdoor ozone corresponded to −0.06 (p < 0.001) z-score between baseline and follow-up, 38 % less improvement than average (median development + 0.16). Exposure to nitrogen dioxide (NO2), 24-hour traffic noise, and particulate matter < 10 µg/m3 (PM10) were also significantly associated with slower executive functioning development when adjusting for ozone. In two-pollutant models, particulate matter and ozone were associated with increased externalising problems. Daytime and evening noise were associated with higher anxiety symptoms, and 24-hour noise with worse speech-in-noise perception (auditory processing). Adjusting for air pollutants, 24-hour noise was also associated with higher anxiety symptoms and slower fluid intelligence development. ConclusionsOzone’s potentially detrimental effects on adolescent cognition have been overlooked in the literature. Our findings also suggest harmful impacts of other air pollutants and noise on mental health. Further research should attempt to replicate these findings and use mechanistic enquiry to enhance causal inference. Policy makers should carefully consider how to manage the public health impacts of ozone, as efforts to reduce other air pollutants such as NO2 can increase ozone levels, as will the progression of climate change.

Synergies of sugar-derived epoxy-silica hybrids and amino-functionalized silica NPs for advanced stone conservation

Innovative approaches to stone conservation materials are essential for addressing the challenges of preserving cultural heritage while meeting environmental and sustainability standards. Based on this premise, this study delves into the synergy between sol-gel processes and nanotechnology to develop advanced epoxy-silica hybrid materials tailored for stone conservation. This investigation specifically targeted the use of amino-functionalized mesoporous silica nanoparticles (NH2-SiO2 NPs) as interactive carriers for natural phenolic biocidal compounds within advanced sugar-based hybrid, demonstrating significant potential in the field of stone conservation. The novel products exhibited improved multifunctional properties attributed to the surface-modified NPs, which facilitated their intimate incorporation into the hybrid network. This integration promoted the creation of homogeneous materials with adapted flexibility, particularly critical for thermal expansion effects, and ensuring mechanical integrity even in outdoor environments. Furthermore, the encapsulation of natural biocidal compounds such as carvacrol and curcumin addressed their intrinsic drawbacks of volatility and coloration effects, preserving their efficacy while minimizing also plasticizing adverse effect on base thermoset. Indeed, the inclusion of curcumin-loaded NH2-SiO2 as dual bactericidal system provided the most favorable compatibility in terms of thermo-mechanical behavior. This system exhibited thermal resistance up to 350 °C and featured inter-joined flexible crystalline domains, distinguished by glass-transition temperatures of 67 and 99 °C. Furthermore, it exhibited enhanced hydrophobic properties reaching contact angles of 105°, and showcased an optimal live/dead ratio response against bacteria. The laboratory scale testing demonstrated a balanced set of features with significant capabilities in both recovering and maintaining the integrity of the lithic substrate, against common degradation patterns induced by prolonged acid exposure.