A Study on Establishing Thermal Output Conditions of Radiant Ceiling Heating Panels for Improving Thermal Comfort of Perimeter Zone in Buildings

Amid concerns over airflow-induced transmission of the COVID-19 virus in buildings frequented by large numbers of people, such as offices, the necessity for radiant ceiling heating panels has increased. This is due to the concern that the airflows emitted from the convection heating systems installed near the ceiling or windows for winter heating may be a major cause of COVID-19 transmission. In this study, we aim to evaluate thermal comfort under various indoor and outdoor environmental conditions of a building and present the thermal output conditions of the radiant ceiling heating panel that can replace the convection heating system while ensuring comfort in the perimeter zone and handling the heating load. As a result, we were able to present, in a chart format, the thermal output conditions that can secure thermal comfort by analyzing the indoor airflow distribution depending on the surface temperature of the radiant ceiling heating panel, the interior surface temperature of the window, and the influence of internal heat generation. Moreover, through derived empirical formulas, we were able to determine the heating conditions of the panel that can secure the necessary heat dissipation while minimizing discomfort, such as downdrafts, even for indoor and outdoor conditions that were not evaluated in this study.

Validity and reliability of sustainable supply chain management frameworks in Indian smart manufacturing industries

PurposeSustainable supply chain management (SSCM) ensures integration of socially, environmentally and economically feasible practices in entire supply chain. SSCM principles can be implemented to improve efficiency and productivity of a system by different attributes of the system. The purpose of this article is to identify the most appropriate existing (SSCM) framework that can be implemented suitably in Indian smart manufacturing industries.Design/methodology/approachValidity and reliability analysis on the existing SSCM frameworks was carried out with the help of empirical data collected using questionnaire survey methodology from various Indian smart manufacturing organizations. The empirical data were gathered from various experts from top- and middle-level management in different smart manufacturing organizations across the country. Further, factor analysis was carried on the collected data to estimate the unidimensionality of each SSCM frameworks. Cronbach's alpha value was used to assess reliability of each framework. Subsequently, the frequency distribution analysis was done to obtain familiar elements in the segregated frameworks based on validity and reliability analysis.FindingsThe work observed that only five SSCM frameworks have shown unidimensionality in terms of the elements or constructs. The work further found that these segregated frameworks have not shown sufficiently high level of reliability. Additionally, this work attempted frequency distribution analysis and observed that there were very few elements which were being repeatedly used in numerous frameworks proposed by researchers. Based on the findings of this work, the work concluded that there is acute need of a new SSCM framework for Indian smart manufacturing industries.Research limitations/implicationsThis study gathered empirical data from 388 Indian smart manufacturing organizations. Thus, before generalizing the findings of the study across the sectors, there is a possibility of some more explication.Originality/valueThe main purpose of this article is to explore the feasibility of the existing SSCM frameworks in Indian smart manufacturing sector. The study also assumes that the manufacturing managers and executives may have the complete understanding on the existing sustainable manufacturing frameworks and a chance to executing proper suitable framework in the respective manufacturing organization.

The Need for a Paradigm Shift toward an Occupant-Centered Environmental Control Model

Office-based environmental control systems are centralized and designed to control entire spaces, ignoring use dynamics and requirements, and despite being regulated by standardized comfort models, they fail to satisfy real occupants, mainly due to their varied individual characteristics. This research is field-based with a quantitative approach and correlational design. Its objective is to empirically demonstrate that open-plan design, where different users share the same space and generalized environmental conditions, lacks a holistic view of IEQ criteria and the integration of other factors that affect health and well-being. Four buildings are chosen in different Chilean cities, measuring temperatures and CO2 levels at different desks, and applying a survey, which was designed as part of the research to analyze the estimation of relationships between variables and to reveal the factors that cause differences among occupants. The results show that people's satisfaction is multivariable and depends on other factors that positively or negatively stimulate their sensations and perceptions, such as, for example, the option to personally control their environmental conditions. Likewise, it is evident that to achieve comfort, health is being affected while in the building.

A Digital Twins Model for Analyzing and Simulating Cold Chain Risks

Due to the outbreak of COVID-19, increasing attention has been paid to designing a cold chain logistics mechanism to ensure the quality of vaccine delivery. In this study, a cold chain digital twins-based risk analysis model is constructed to handle and monitor the vaccine delivery process with a high level of reliability and traceability. The model integrates the Internet of Things (IoT) and digital twins to acquire data on environmental conditions and shipment movements and connect physical cold chain logistics to the digital world. Through the simulation of cold chain logistics in a virtual environment, the risk levels relating to physical operations at a certain forecast horizon can be predicted beforehand, to prevent a 'broken' cold chain. The result of this investigation will reshape the cold chain in the digital age, benefit society in terms of sustainability and environmental impact, and hence contribute to the development of cold chain logistics in Hong Kong. © 2023 IEEE.

Saliva Droplet Evaporation Experiment and Simple Correlation of Evaporation-falling Curve under Different Temperatures and RH

In the present study, water and saliva droplet evaporation rates are experimentally evaluated in various environmental conditions: temperature and relative humidity. We found that the ratio of saliva residue size to saliva initial droplet size is 0.216. We also found that the saliva correction factor which is defined as a ratio of water evaporation coefficient to saliva evaporation coefficient was not affected by environmental conditions and was determined as 0.857. By considering the evaporation and gravitational settling effects, the saliva airborne lifetime, i.e., the evaporation-falling curve is numerically calculated and characterized. In addition to this numerical calculation results, we present the simple correlation equation for obtaining the evaporation-falling curve under different temperatures and relative humidity. © 2023, AAGR Aerosol and Air Quality Research. All rights reserved.

SUSTAINABILITY OF GREEN TOURISM BY INTERNATIONAL TOURISTS AND ITS IMPACT ON GREEN ENVIRONMENTAL ACHIEVEMENT: PETRA HERITAGE, JORDAN

The environmental advantages of green tourism are attracting the attention of a wider range of stakeholders. The behavior of travelers toward green tourism sustainability and its impact on the accomplishment of a green environment has not been well studied empirically, particularly in Petra. In this research, we use an expanded framework of the theory of planned behavior to explore the behavioral features of foreign visitors toward the sustainability of green tourism (TPB). Descriptive analysis of the explanatory survey was the method of choice for the research project at hand. A large number of respondents were tourists. Office administrators are responsible for the formulation of a company's corporate strategy. 400 tourists took part in our survey for this research. According to our results, travelers' views toward green tourism were highly influenced by their opinions of the sustainability of green tourism and their environmental concerns. In addition, our findings show that visitors' intentions to engage in the sustainability of green tourism are negatively influenced by subjective norms, whereas tourists' attitudes are positively influenced by these norms. Both environmental concerns and the desire of visitors to engage in green tourism have a substantial influence on ecologically responsible tourism behavior, according to our findings.

Understanding the performance of truffle dogs

Trained dogs can detect many biochemical traces, from the most hostile, such as COVID-19, to the most expensive, such as truffles. However, it is still unclear how the interplay of genetic disposition, education, experience, personality, and environmental conditions influences the performance of dogs. Here, we combine published evidence with the knowledge of truffle hunters to assess direct and indirect factors that affect the hunting performance of truffle dogs. Since the transport of truffle aroma into the canine nasal cavity is most puzzling, we propose 5 experiments to further investigate the role of weather conditions, soil parameters, and bacterial composition on the dispersal of truffle volatiles perceived by trained dogs. We also suggest exploring whether the application of multiple dogs increases the success of truffle hunting. Moreover, we argue that interdisciplinary research on dog behavior and performance, including insights from veterinary science and comparative psychology as well as the experience of truffle hunters and farmers, is needed to improve the quantity and quality of truffle harvests. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

A System Design with Deep Learning and IoT to Ensure Education Continuity for Post-COVID

In this paper, an IoT and deep learning-based comprehensive study to reduce the effects of COVID-19 on the education system is presented. The proposed system consists of an edge device, IoT nodes, and a neural network that runs on a server. The purpose of the proposed system is to protect students and staff against infectious diseases and increase the students performance during classes by monitoring the environmental conditions via an IoT-based sensor network, during the current pandemic to ensure the use of masks in closed areas by training a customized deep learning model, and to monitor the student attendance data by deep learning and IoT-based solution. Furthermore, effective heating and cooling can be done to save energy by transmitting the environmental conditions of the indoor environment to the relevant destinations. The experiment is conducted with five different networks to classify the faces in the images as masked or unmasked, and their performances were examined. The networks were trained on the Face Mask Detection Dataset which contains a total of 7553 masked and unmasked images. The best results were obtained as 99.5% for the F1 Score and 99% for MCC by the model trained on the InceptionV3 network. IEEE

LIFESTYLE PATTERNS ASSOCIATED WITH BURNOUT DIMENSIONS DURING SARS-COV2 PANDEMIC. A WEB-BASED SURVEY OF DENTAL HEALTHCARE WORKERS

Multiple lines of evidence suggest that significant lifestyle changes, including diet, exercise, sleep, stress, job status, recreation, and use of modern technologies may lead to various COVID-19 related health problems in the general population, as well as among healthcare workers [3-8]. The first part contained 21 questions gathering information about dentists' demographic characteristics (e.g., age, gender, marital status), work environmental conditions (e.g., average working hours per day, dental equipment, auxiliary staff, self-assessed income, etc.), dentists' lifestyle patterns (hobbies/ spare time activities, insomnia, and use of antidepressants and sleeping pills), perceptions and attitudes towards the coronavirus pandemic (e.g., sources of stress, vaccination intentions, etc.) and retirement plans. In this group, a very high level of burnout was observed regarding EE (43.13±4.80) and DP (15.13±5.04) dimensions. [...]the high dimension of performance loss was significantly related to the regular use of these medicines (p<0.001) - Table 3. Various studies have shown that the outbreak of SARS-CoV-2 pandemic has profound psychological and social effects, identifying significant lifestyle changes and mental health problems [2,4,11].

Progress in the distribution characteristics and risks of bioaerosols from anthropogenic sources

In recent years, the global outbreak of COVID-19 has aroused public attention to the potential risks of bioaerosols and the studies about the potential health hazards of bioaerosols from anthropogenic sources have been increasing. We introduced the research status of four main anthropogenic bioaerosols in recent years, compared the distribution and composition characteristics of bioaerosols from different anthropogenic sources, and analyzed the main factors affecting the characteristics and potential risks of bioaerosols. The average concentration of bioaerosol is high in animal farms, moderate in wastewater treatment plants and landfills, and low in hospitals. The microbial composition of bioaerosols at different sites is closely associated with the bioaerosol source and affected by the environmental conditions. Furthermore, this work prospected the main research directions of anthropogenic bioaerosols in the future, aiming to lay a foundation for the establishment of bioaerosol control standards and the development of control technology.

Afforestation intentions for mitigating carbon emissions in the post-COVID-19 perspective: the case of green hotel visitors in Bangladesh

PurposeThis study aims to explore green hotel visitors' afforestation intentions by extending the theory of planned behavior, including post-COVID-19 personal norms (PCPN) and post-COVID-19 environmental concerns (PCECs). Moreover, this study examines the mediating effect of PCECs from the post-COVID-19 perspective.Design/methodology/approachThis study is based on existing literatures and collection of 384 usable responses using the convenience sampling technique. The partial least square structural equation modeling is used to analyze data using Smart PLS3.3.3.FindingsThe findings reveal that post-COVID-19 afforestation attitudes, subjective norms (SN), perceived behavioral control (PBC) and PCPN significantly influence post-COVID-19 afforestation intentions (PCAI) and PCECs. Further, PCEC partially mediates the between post-COVID-19 afforestation attitudes, SN, PBC and PCPN and PCAI.Practical implicationsThe findings of this study may be useful to green hotel operators in formulating business strategies enhancing visitors' positive perceptions toward green hotels and afforestation intentions coping with new normal environment and hospitality industry.Originality/valueThis research presents a distinguished case highlighting how the green hotel guests' perceptions toward afforestation for mitigating carbon emissions are changing because of COVID-19 pandemic. This study provides crucial insights for green hotel practitioners by integrating post-COVID-19 afforestation attitudes, SN, PBC, PCPN and PCEC of green hotel visitors in examining PCAI.

Thermal Assessment of a Ventilated Double Skin Façade Component with a Set of Air Filtering Photocatalytic Slats in the Cavity

Indoor air quality is a crucial factor when evaluating habitability, especially in developed countries, where people spend most of their time indoors. This paper presents a novel double skin façade (DSF) system that combines physical and photocatalytic filtering strategies. The air purification system is made up of fixed slats that are both solar protection and air purification system. The objective of this work is to determine the thermal behaviour of the proposed system, so that its suitability for use in various environments may be assessed. This was carried out using a physical 1:1 scale model and a computational fluid dynamics (CFD) model. The maximum temperature inside the scale model cavity was 17–20 °C higher than outdoor air. Additionally, it was discovered that the airflow through the DSF would require forced ventilation. To determine the emissivity values of the photocatalytic coating, additional experimental measurements were made. The CFD model was tested for summer and winter conditions in Barcelona, Chicago, and Vancouver. The average increase in the intake air temperature was around 14.5 °C in winter and 12 °C in summer, finding that the system has its main use potential in temperate or cold areas with many hours of solar radiation.

Environmental Aspects of City Participatory Budgeting in Poland

Participatory budgets are an increasingly common form of co-decision of residents about the quality of life and development directions of urban space. In Poland, participatory budgets have been realized for a decade, and projects submitted to these budgets respond to needs such as e.g. leisure infrastructure, environmental conditions, recreation, health, and education. The study aims to analyze the phenomenon of civic participation and the use of participatory budgets as a tool of co-governance in the context of environmental issues and urban development. A desk research analysis of national and foreign literature data was performed, and the existing statistical data on participatory budgets in Poland were analyzed. In addition, the websites of selected cities in Poland were analyzed in the context of implemented projects and citizen's activity within the framework of participatory budgets. The results indicate that the initial enthusiasm of the citizen's implementation has decreased, but the COVID-19 pandemic has aroused renewed interest in the topic. The study's implication is recommendations, e.g.: creating a civic budget database featuring uniform categories or creating Green Civic Budgets in every city.

Interpretation of Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation

Effectively blocking the transmission route of coronavirus and protecting the susceptible population play significant roles in the control of COVID-19 pandemic.Strengthening home-based medical observation is one of the key points in preventing the spread of SARS-CoV-2 virus in families and communities.Therefore, in order to meet the needs for COVID-19 prevention and control in Beijing, a group of experts organized by Beijing Association of Preventive Medicine developed the Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation（T/BPMA007.3-2020）, which offers the specific provisions for close contacts of COVID-19 cases who need home-based medical observation as well as home environmental condition, prevention and control requirements, waste disposal, disinfection, community prevention and control work requirements, basic requirements for training and education and management guidelines.It provides standard support for home-based medical observation of close contacts with COVID-19 cases.

Using a Human Health Standard for IAQ Management

Researching and testing water to protect fish might seem obvious. Surprisingly, a parallel approach of analyzing and managing the predominant human exposure--indoor air--to optimize occupant well-being and productivity is not a priority for building management. We are indoors approximately 90% of the time, and health is people's most valuable asset, yet there is a lack of data relating indoor air quality (IAQ) to health outcomes. The most understandable obstacle is that relating IAQ to health outcomes is complex. The very fact that humans are resilient and able to withstand mild physiological stress without immediately obvious consequences makes correlating indoor exposures with health changes a difficult task. Despite these challenges, they need to pay attention to what IAQ data would tell. In fact, paying attention is not enough. They need to agree on what levels are good or bad and manage IAQ accordingly.

Characterization of a Wearable LiDAR Sensor for Social Distancing

LiDAR sensors are widely used in autonomous driving, mobile robotics, aerospace, manufacturing, and many other fields. The speed, reliability, and range of LiDAR sensors can be affected by environmental conditions and usage patterns. Each application requires a deep understanding of sensor limitations. This paper explores the operational parameters of one of the most miniature and least expensive LiDAR sensors packaged in a wearable case. The target application, in this case, is social distancing during pandemics. This study focuses on the performance of miniature LiDAR sensors under different levels of light intensity, temperature, distance to the object, object size, angle of view, and object color. The experimental data enables a match between the sensor capabilities and application scenarios and provides direction for future work in improving the wearable sensors of this class. © 2022 IEEE.

A theory-based approach to travel behavior analysis using pattern recognition and latent group identification techniques

Human behavior is complex: the decisions people make are affected not only by their inner worlds, but also their personal and environmental conditions. In travel behavior research, there is very often a heavy focus on the conditions surrounding behaviors with a lack of focus on the mental processes underpinning the decision-making process. This dissertation presents a novel conceptual model of travel behavior that accounts for these important mental processes and develops data analysis techniques that can help answer research questions based on this framework. In this dissertation, first, the conceptual model is described. Next, an indicator for an important travel behavior concept called fragmentation is established. Common patterns of activities and travel are identified from detailed diaries of travel using sequence analysis, agglomerative nesting, and optimal matching techniques. The relationship between gender and fragmentation in different-sex couples is also analyzed. Then, the design, distribution, and analysis of a survey is presented. This survey looks at travel behavior when COVID-19 stay-at-home orders were in full effect. To the extent possible, the survey used the conceptual model as a guide for what questions to include. A method using latent class analysis to classify travel behavior is also established. Travel behavior attitude are also classified using latent profile analysis. To assess the relationship between attitudes and behavior, the results of these two classifications are compared using cross-classification. Then, a model is created with the goal of following the conceptual model as closely as possible with the data available in the 2017 and 2019 Puget Sound Regional Council Transportation Study. The previously discussed travel behavior classification methods, index of fragmentation, and activity-travel patterns are all used in this model, and it expands upon the research into the relationship between fragmentation and gender. Finally, there is a discussion of issues in travel behavior survey methodology, and suggestions for how to improve these methods. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Preface: The 4th International Conference on Environmental Resources Management (ICERM) 2021

Landscape is very dynamic [1,2,3]. In line with the development of an increasingly climate change [4] and high population, the dynamics of the landscape have also changed due to an increase in the intensity of the population in utilizing land. The condition of the corona virus pandemic since the beginning of 2020 has resulted in two impacts to the environment. On the one hand it has provided a positive impact in the form of improving environmental conditions due to reduction on population mobility and natural resources exploitation, but on the other hand it has also increased the number of dangerous waste, e.g. increasing mask waste accumulation.The Faculty of Geography Universitas Gadjah Mada, Yogyakarta-Indonesia, notably the Department of Environmental Geography has been working for a long time on environmental issues. In order to highlight the topic of environmental resource management in the global region and to broaden perspectives on this subject, the Faculty will organize the 4th International Conference on Environmental Resources Management in Global Region (ICERM).List of ICERM 2021 Committee are available in this pdf.

Secure meat-hungry food systems to prevent next pandemic

Speed read Intensive agriculture for animal protein source of emerging diseases, experts say But, understanding of animal pathogen spillover incomplete, making pandemic prediction difficult Investment needed in early warning systems, One Health preparedness Sustainable agriculture and better health monitoring needed to break chain of disease transmission in food systems. Environmental hotspots Agriculture and meat production are significant contributors of greenhouse gases, both directly and through land-use change — Andersen notes that the drivers of pandemics are often the same drivers of climate change and biodiversity loss. "Climate change results in changing environmental conditions, which impacts on the ecosystem characteristics and as a result, it changes the distribution of animal species, and therefore also of any microorganisms which they carry,” Dirk Pfeiffer, a professor of veterinary epidemiology at City University of Hong Kong and the Royal Veterinary College in London, tells SciDev.Net.

Influence of atmospheric environment on SARS-CoV-2 transmission: A review

The novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a public health emergency of international concern. Exposure to droplets produced in the coughs and sneezes of infected individuals has been perceived as the dominant transmission mode for COVID-19. However, increasingly more evidence supports claims of COVID-19 having airborne transmission. An in-depth understanding of the transmission pathways and influencing factors of SARS-CoV-2 is of great significance for formulating more effective intervention strategies. A large number of epidemiological investigations into the influence of atmospheric environmental conditions on virus transmission have been conducted. In this paper, we review current understandings of the association between COVID-19 and atmospheric environmental conditions. We first summarize the epidemiological investigations on the impact of atmospheric environmental factors (including solar radiation, temperature and humidity, wind speed, particulate matters, and gaseous pollutants) on the spread of COVID-19, and 164 epidemiological investigations are included, in which air temperature and relative humidity received the greatest attention. However, the impact of these factors on the prevalence of COVID-19 remains largely uncertain. 56% and 41% of investigations of temperature and humidity, respectively, show that cold and dry weather promotes COVID-19 transmission, while some studies come to the opposite conclusion, and still others do not show a significant relationship between them. Investigations of solar radiation are limited, but have come to the consistent conclusion that weak solar radiation is linked to increased severity of COVID-19 infection. Investigation of the impact of air pollution mainly focuses on particulate matters, and more than 70% of investigations indicate that PM2.5 likely contributes to the spread of COVID-19. Similarly, 62%, 51%, and 31% of investigations of NOx, O3, and SO2, respectively, indicate that the exposure to severe pollution can aggravate COVID-19 transmission. Therefore, the available findings reveal the complexity of the impact of atmospheric environmental conditions on the spread of COVID-19. We further discuss their mechanisms from three perspectives: (1) Atmospheric environmental conditions influence the generation of virus-laden aerosols and the occurrence of SARS-CoV-2 in the atmosphere. Relative humidity can affect the evaporation process of water on virus-laden aerosol, and thus affect its atmospheric life and probability of being inhaled by human body. (2) Atmospheric environmental conditions directly affect the stability of infection activity of SARS-CoV-2. Generally, high temperature, medium relative humidity, and intense solar radiation promote the inactivation of SARS-CoV-2. (3) Atmospheric environmental conditions indirectly affect the infection ability of SARS-CoV-2 by changing the defense ability of host cells. Air pollutants, especially PM2.5, can affect human susceptibility to the virus by increasing the expression of the SARS-CoV-2 receptor (angiotensin converting enzyme 2) in host cells. Meanwhile, meteorological conditions and air pollution can lead to respiratory system and other diseases in the human body, thus reducing human immunity and increasing the risk of virus infection, as well as the numbers of severely infected and fatal cases. All three mechanisms may contribute to the prevalence of COVID-19, but the dominant mechanism remains unclear. Finally, future directions of in-depth studies regarding the association between the epidemic and atmospheric conditions are proposed. © 2022 Chinese Academy of Sciences. All rights reserved.