Public Well-being Research Articles

Detecting health misinformation: A comparative analysis of machine learning and graph convolutional networks in classification tasks

In the digital age, the proliferation of health-related information online has heightened the risk of misinformation, posing substantial threats to public well-being. This research conducts a meticulous comparative analysis of classification models, focusing on detecting health misinformation. The study evaluates the performance of traditional machine learning models and advanced graph convolutional networks (GCN) across critical algorithmic metrics. The results comprehensively understand each algorithm's effectiveness in identifying health misinformation and provide valuable insights for combating the pervasive spread of false health information in the digital landscape. GCN with TF-IDF gives the best result, as shown in the result section.•The research method involves a comparative analysis of classification algorithms to detect health misinformation, exploring traditional machine learning models and graph convolutional networks.•This research used algorithms such as Passive Aggressive Classifier, Random Forest, Decision Tree, Logistic Regression, Light GBM, GCN, GCN with BERT, GCN with TF-IDF, and GCN with Word2Vec were employed. Performance Metrics: Accuracy: for Passive Aggressive Classifier: 85.75 %, Random Forest: 86 %, Decision Tree: 81.30 %, Light BGM: 83.29 %, normal GCN: 84.53 %, GCN with BERT: 85.00 %, GCN with TR-IDF: 93.86 % and GCN with word2Vec: 81.00 %•Algorithmic performance metrics, including accuracy, precision, recall, and F1-score, were systematically evaluated to assess the efficacy of each model in detecting health misinformation, focusing on understanding the strengths and limitations of different approaches. The superior performance of Graph Convolutional Networks (GCNs) with TF-IDF embedding, achieving an accuracy of 93.86 %

Comparison of deep learning models for weather forecasting in different climatic zones

Weather forecasting has become an integral part of our day-to-day life. Weather holds significant importance in our everyday lives, impacting areas such as how we travel, produce food, and maintain public well-being. Mostly, weather prediction is done with machines learning models, but the use of deep learning techniques in this field in growing. Still, the existing studies are not sufficient to get a clear concept of weather prediction in different climatic zones. Therefore, in this study, selected four deep learning models, RNN, CNN and LSTM, to predict temperature in four climatic zones. We selected four cities, Dhaka, Moscow, Dubai and Brasilia from four different climatic zones. It is seen that the overall accuracy (OA) of LSTM ranged between 85% to 95%, followed by CNN 78% to 91%, and RNN 64% to 94%. Though the OA values of these three models in four climatic zones differs significantly, high AUC values were seen in all scenario. The highest AUC value (0.999) was seen in continental climatic zone for LSTM model and lowest (0.963) in mil climatic zone for RNN.

Leading the Leader: Positive and Resilient Leadership (PRL) in Urban Public Schools through Filipino Public-School Teachers’ Metaphorical Perspectives

Positive leadership and resilient leadership are two types of leadership that share several commonalities, both of which seemingly respond and offer suitability to the unpredictable and volatile landscape and requirements of the times. While separately, there has been substantial empirical work on positivity and resilience in leadership, no study has been undertaken to combine both so that one type of leadership, i.e. Positive and Resilient Leadership (PRL), can emerge. Further, positivity and resilience in leadership have so far remained understudied among public organizations, particularly in urban public schools, a sector that considers ineffective leadership as among the major problems that hinder the quality of public education. Also, while previous studies have focused on such leadership from the perspective of school leaders, there remains a dearth of literature on understanding it from the standpoint of those being led, such as the teachers. To fill these gaps, this study examined the possible nature and characteristics of PRL by employing qualitative content analysis and thematic analysis in an attempt to (a) determine the metaphors Filipino teachers in urban schools use to describe leadership that is both positive and resilient, (b) identify how these metaphors capture the traits of positive and resilient school leaders in these schools, and (c) explore various situational practices of PRL in the Philippine urban public school sector. Findings showed five (5) categorizations of metaphors that were drawn from the responses of the public school teachers, indicating how PRL can provide them P.O.W.E.R., i.e. positivity, opportunity, wisdom, empathy, and reinforcement in six (6) aspects of school management, namely: (a) planning and implementation of school policies, programs, activities, and projects, (b) decision-making, (c) personnel management, (d) implementation of innovation and change, (e) resource generation and utilization, and (f) communication within and outside the organization that could improve urban public school teachers performance and well-being.

Efficiency and Elegance: Exploring Automated Solutions for Public Lighting

This paper explores the intersection of efficiency and elegance in the realm of automated solutions for public lighting. With the rapid advancement of technology, cities around the world are increasingly turning to automated systems to illuminate their streets, parks, and public spaces. These systems offer not only enhanced efficiency in energy consumption but also the opportunity to elevate the aesthetic appeal of urban environments. Through a comprehensive review of existing literature and case studies, this research examines the benefits and challenges associated with automated public lighting solutions. It delves into the technological innovations driving these systems, including sensor-based controls, adaptive lighting algorithms, and integration with smart city infrastructure. Furthermore, the paper explores the role of automated lighting in promoting sustainability and reducing carbon emissions, as well as its impact on public safety and community well-being. By considering factors such as cost-effectiveness, scalability, and user acceptance, it seeks to provide insights into the practical implementation of automated lighting solutions in diverse urban settings. Ultimately, this study aims to shed light on the potential of automated public lighting to not only enhance efficiency but also contribute to the creation of more elegant and livable cities. It underscores the importance of embracing innovation and leveraging technology to create vibrant and sustainable urban environments for current and future generations. When the lights are on it'll dependably stay on until any labor turns off them. So that the support and the fiscal consumption application is more. It might bear checking the board constantly. The crunches of conventional road lighting frame work not only convey premonitory burden to the near plutocrat related part. Yet in addition it confines the administration and keep of the lighting system which leads to the vexation to the public since several lights are n’t glowing and complaints for them has n’t been made. The advancement of green lighting is introductory. An crop among the most abecedarian mortal advancement records is the enhancement of a drop transportation association. These thorough fares and roads must be immaculately lit up with the target that an acceptable perceivable quality is assured to dwindle the failure rate and expansion of the shot of vehicle.

Increasing Safety: A Survey of Open Greenspace Usage during and after the Pandemic in Belgrade, Serbia

COVID-19 has severely affected almost every aspect of our everyday lives, especially the use of open greenspace (OGS) in urban settings, which has proven to have a significant role in increasing overall public health and well-being. Hence, the restricted usage of these spaces should be reconsidered. This research aims to analyze the sensitive nature of OGS usage (1) during the pandemic from the perspective of users’ perceived safety and (2) after the pandemic to assess the possible long-term effects. Additionally, this research proposed that location-tracking mobile applications could lead to an increased frequency of OGS visits. The methodology contains detailed background research and two surveys. One survey was conducted during the pandemic in 2020 (sample size n = 412) and was repeated post-pandemic in 2024 (sample n = 451). The 2020 questionnaire A includes questions about the duration, frequency, and activities of OGS usage while focusing on the perceived safety and possibilities of monitoring OGS visits using mobile apps. The 2024 survey represents the continuation of the 2020 survey, focusing on the post-pandemic state of OGS. The statistical analysis is separated into a descriptive data analysis, various χ2 independence tests and a machine learning safety prediction. The results indicate how COVID-19 could affect OGS usage and how app-related physical safety enhancements during the pandemic cannot be statistically distinguished from those in the post-pandemic period. Although the interest in location-tracking mobile applications has statistically decreased in 2024, the majority of the total 863 participants stated that applications could increase their feeling of perceived safety. The added value of this research is that it considers age and gender roles in analyzing OGS usage in the context of a pandemic.

Prevalence of Infectious Diseases in Children at Preschool Education Institutions and Stakeholder Opinions.

Preschool education institutions, where children have close contact and social interactions, can serve as potential environments for the transmission of infectious diseases. This issue poses a significant health concern, impacting both individual and public well-being. Thus, the present research set out to determine the prevalence of infectious diseases in preschool children and the views of parents and teachers on the prevention of infectious diseases. The study employed a mixed-method approach and involved 397 parents and 46 preschool teachers. The study was survey-based via in-person interviews. The results revealed that after they started school (almost in 5 months), children with a mean age of 4.7 ± 0.5 years experienced illness approximately 3.5 ± 2.0 times, of whom 91.5% used antibiotics. The prevalence of infectious diseases was found to be associated with the child's being born at term, maternal education level, and the public/private status of preschool institutions. The presence of a sick child in the classroom elicits negative emotions from both teachers and parents. They recommend that studies on education, safety, hygiene, school health, health screenings, regulation of the learning environment, legal regulations, and school exclusion policies be carried out to prevent infectious diseases. When children with infectious diseases come to school, nearly half of the teachers admit them to the classroom due to various reasons and pressures. Parents request teachers to monitor medication, control sweating, and use a nebulizer for their sick children. Some of the teachers meet these requests, but they claim that the educational process is negatively affected. At preschool education institutions, the risk factors of infectious diseases have a complex structure and can be influenced by variables related to teachers, children, parents and the institution itself. Infectious diseases not only pose a threat to health but also impact teachers' and parents' emotions, teacher-child relationships, and the overall atmosphere within schools and classrooms.

Relationship Between Stress, its Management and Public Well-being in Lithuania: Effect of Sociodemographic and Clinical Factors

The aim of the study was to assess the individual stress intensity and its management in Lithuania in the context of public well-being, concentrating on the effects of socio-demographic and clinical factors on stress intensity. To reach the aim, a quantitative study was conducted. 1137 residents of Lithuania participated in the online survey. A visual analogue scale (1–10, VAS) was used to determine stress intensity and management, and the Arizona Integrative Outcome Scale was used to determine the sense of well-being. The research results indicate that 98% of respondents experience stress with an average stress intensity and only 50% of respondents experience a higher-than-average sense of well-being formed by physical, mental, emotional, social and spiritual state. The measured relationships between stress, socio-demographic and clinical factors suggest that the marital status, education, profession, nature of work, salary, work experience, duration of work and rest, consequences of COVID-19 have the greatest potential for perceived stress. High-intensity stress is prevalent in Lithuania with moderate management. In the study it was identified, that the main tools for reducing stress are communication with supportive persons, daily regimen and sleep, leisure time for a hobby and rehabilitation, avoiding bad habits, appropriate medical SPA treatments or wellness practices.

Use of mind genomics for public health and wellbeing: Lessons from COVID 19 pandemic

ABSTRACT Background: Machine learning (ML) tools can be used to analyze human mindsets and forecast behavioral patterns. ML can be used to understand the psychological processes and behavioral principles underlying public decision-making patterns. The aim of this study was to explore participants’ mindsets using ML and accordingly build messages for each mindset to enhance compliance with a public health policy, specifically physical distancing during the coronavirus disease 2019 (COVID-19) pandemic. Methods: An online questionnaire was administered using systematically varied combinations of elements and science of mind genomics. The questions focused on the perceived risk level of COVID-19, strategies to enhance physical distancing compliance, appropriate communicators of the policy, and different physical distancing practices. Snowball sampling was used to recruit participants until sample saturation was achieved among residents of the United Arab Emirates (UAE), aged 18– 80 years. Results: A total of 117 patients were included in this study. In the total panel, the strongest performing elements were those communicated by the government (P<0.01) and clergy (P < 0.05), with no differences between sex and age groups. Three mindset segments were identified: (1) followers of general strategies for physical distancing, (2) those interested in novel ways of practicing physical distancing, and (3) fascinating onlookers of the pandemic. Conclusion: Our results revealed that COVID-19 health-related messages are best communicated by the government and clergy in the UAE. These strategies may aid in the implementation and adoption of other public health policies.

How health risk of COVID-19 resurgence may trigger individual tendencies regarding COVID-19-related cyberchondria: Investigating the I-PACE model

Cyberchondria during the COVID-19 pandemic has posed significant challenges to public well-being. Previous lstudies have implicated perceived health risk in COVID-19-related cyberchondria. However, the effect of perceived COVID-19 health risk on cyberchondria and potential underlying mechanisms remains unclear. In this study, we developed a model based on the general addictive behavior framework of the I-PACE (Interaction-Person-Affect-Cognition-Execution) model to describe how induction of health risk of COVID-19 resurgence may influence individual tendencies regarding COVID-19-related cyberchondria. Through a scenario-based experiment, we tested this model with a balanced sample of 984 participants from China. The results revealed that the effect of induction of health risk of COVID-19 resurgence on tendencies regarding COVID-19-related cyberchondria was fully mediated by individual's risk perception and health information craving. Additionally, moderation analysis showed that an individual's general inhibitory control did not moderate the development of cyberchondria. Theoretical and practical implications are provided.

An Overview of the Effect of Rising Traffic and Congestion in Bangalore on the Lives of General Public

Abstract: Bangalore, India's Silicon Valley, is experiencing widespread traffic congestion, which has a significant impact on the urban environment of the city. This study looks at the complex effects of traffic congestion on public health, social well-being, economic productivity, and air quality in Bangalore's metropolitan environment. By conducting a thorough examination of extant literature and statistics, the research clarifies the adverse consequences of traffic congestion, including elevated levels of air pollution, an increase in traffic accidents, extended travel times, and reduced productivity. The research also looks at possible mitigating measures, such as bettering the infrastructure for public transit, enacting congestion pricing plans, encouraging the use of alternate forms of transportation, and implementing clever urban design techniques. Policymakers can create successful measures to address traffic congestion by having a thorough understanding of the intricate relationship between the two.

Research on smart city public health detection system and improvement technology based on intelligent multi-objective.

With the increase of urban population density, urban sanitation becomes more severe; urban sanitation has important influence on public health. Therefore, in order to realize the detection of public health in smart cities, the research will use cutting-edge scientific and technological methods to improve urban environmental health, so as to promote the realization of public health achievements. This study introduces public health detection and optimizationtechnologies for smart cities. Firstly, a data detection system for urban public health environment was established using sensors and intelligent multi-objective technology to evaluate the water quality, air quality, and noise level of the city. Then, an intelligent garbage management system based on Tensor-flow was constructed to achieve efficient garbage collection and treatment. Finally, an intelligent traffic management system was developed to monitor and regulate urban traffic flow. The results of the simulation experiment demonstrated that the life data detection system was operationally stable, with a high success rate of 98%. Furthermore, its accuracy in detecting residents' living environment data was above 95%, the maximum relative error was only 0.0465, making it a reliable and efficient tool. The waste recycling system achieved a minimum accuracy of 83.6%, the highest accuracy rate was 95.3%, making it capable of sorting and recycling urban waste effectively. Additionally, the smart traffic management system led to a 20% reduction in traffic congestion rates, 20 tonnes less tailpipe emissions and an improvement in public health and well-being. In summary, the plan proposed in this study aims to create a more comfortable, safe, and healthy urban public health environment, while providing theoretical support for environmental health management in smart cities.

Auto311: A Confidence-Guided Automated System for Non-emergency Calls

Emergency and non-emergency response systems are essential services provided by local governments and critical to protecting lives, the environment, and property. The effective handling of (non-)emergency calls is critical for public safety and well-being. By reducing the burden through non-emergency callers, residents in critical need of assistance through 911 will receive a fast and effective response. Collaborating with the Department of Emergency Communications (DEC) in Nashville, we analyzed 11,796 non-emergency call recordings and developed Auto311, the first automated system to handle 311 non-emergency calls, which (1) effectively and dynamically predicts ongoing non-emergency incident types to generate tailored case reports during the call; (2) itemizes essential information from dialogue contexts to complete the generated reports; and (3) strategically structures system-caller dialogues with optimized confidence. We used real-world data to evaluate the system's effectiveness and deployability. The experimental results indicate that the system effectively predicts incident type with an average F-1 score of 92.54%. Moreover, the system successfully itemizes critical information from relevant contexts to complete reports, evincing a 0.93 average consistency score compared to the ground truth. Additionally, emulations demonstrate that the system effectively decreases conversation turns as the utterance size gets more extensive and categorizes the ongoing call with 94.49% mean accuracy.

Public health risk assessment and speciation of air-borne microorganisms in an office building

This study focuses on speciation of air borne microbes in an office building and health impacts of these microbes in terms of Quantitative Microbial Risk Assessment (QMRA), Hazard Quotient (HQ) and Hazard Index (HI). This is important in the wake of Sustainability Development Goal 3 (Public Health and well-being) specially when there is a lack of standards in terms of microbial air quality in office buildings where people spend 8–10 h indoors. Air borne bacterial and fungal species in different floors of the office building with varying occupancy and work profile were identified. The load of bacterial count on an average for the entire building was found to be 1917 CFU/m3. Overall, Gram-positive bacteria were predominant (>53%). Based on V3–V4 sequencing Staphylococcus scuiri (causing UTIs) was the most abundant (93.7%) and other bacterial species found were Lactobacillus hamsteri, Prevotella copri, Bacteroides plebeius Faecalibacterium prausnitzii, Bacillus coagulans (gut commensals), Shigella boydii (causes bacillary dysentery), and Propionibacterium acnes (acne producing). Fungal load was 4000 CFU/m3. Based on ITS sequencing Aspergillus (45.6%) was the dominant fungus and other fungi found were Cunninghamella, Lichtheimia, Fusarium, and Circinella Grammothele, Chondrostereum, and Pseudolagarobasidium, Candida sp., Chondrostereum, Sarocladium. The QMRA of gram-negative air borne bacteria showed a high disease burden, well over the WHO benchmark values even though Hazard Quotient (HQ) and Hazard Index (HI) was found to be negligible. These findings can contribute to the development of guidelines for seemingly safe workplaces that may harbour disease-causing microbes and calls for an immediate attention from policy makers as it is a major cause of concern for public health.

The International Classification of Functioning Disability and Health Framework (ICF): a new approach to enhance sport and physical activity participation among people with disabilities in Scotland.

This research provides a pilot study of the International Classification of Functioning Disability and Health Framework (ICF) involving persons with disabilities (PWD) with and without lived experience of sport participation in Scotland. National surveys in Scotland provide limited information on the nature of individual disability restricting the understanding of the relationship between disability and sport and physical activity participation. The ICF is a framework that aims to describe and classify functioning and thus can be used as a tool to provide a more detailed description of impairment for PWDs beyond their clinical condition. This knowledge has the potential to enhance the development of policies to increase the participation levels in this group. The ICF has also been used to inform the current IPC classification system at a competitive and elite level. As part of a larger study, 450 participants aged between 12 and 70 years completed an online questionnaire examining attitudes to, and participation in, sport and physical activity as well as completing the structural and functional components of the ICF. Subsequently, 18 people participated in focus groups aged between 13 and 61 years. The focus groups examined four meta-theme areas: physical, social, psychological, and sport-specific factors. The results confirm that the ICF provided a more detailed indicator of the key impairments that could have an impact on sport and physical activity participation. There was a clear lack of awareness of the links between the ICF and the classification system for competitive parasport. We concluded that a modified ICF-based assessment tool, incorporating social and environmental factors, has the potential to predict the likelihood of participation and offers a more comprehensive picture of both individual and national disability characteristics. This allows for the development of targeted policies and strategies to assist those with a disability to participate in sport. The overall framework presents a shift in thinking, in policy terms, for those in public health and in sport governance and delivery. The significance of this work is especially concerned with public health and wellbeing and sport development policy as pathways from recreational sport user to elite athlete parasport classification and performance.

The positive effect of blue luminescent pathways on urban park visitor’s affective states: A virtual reality online study measuring facial expressions and self-reports

The colour blue often elicits feelings of calmness and contentment, for which evidence has largely been provided in daytime settings. It is unclear whether pathways illuminated in blue, for example, in urban recreational park areas at night confers the same positive impact on night time park visitors. To tackle this open empirical question, we investigated how adding blue self-luminous pavement to park lighting at night time affects park visitors’ emotions compared to conventional white street light illumination. Our goal is to inform design decisions aimed at enhancing the emotional well-being of people outdoors at night in urban environments. Participants’ emotional response was captured at four different time points while watching a video of a walk in a virtual urban park at night, which was lit with white street lights only or with the addition of blue luminescent pavement on the walked paths (between-subject design). To capture visitor’s emotions, we used a simplified version of the Geneva Emotion Wheel (GEW) instrument and online facial expression recognition technology as subjective (self-reports) and objective (physiological) measures of emotion, respectively. The results of the GEW self-reports showed that the addition of a blue self-luminous pavement in a park during night time yielded more positive affect than standard white lighting in park visitors for the first half of the walk. In the second half of the walk through the park, participants’ affective states seemed to equalize between the two lighting conditions. In contrast, sensory data on facial expressions indicated no difference between participants’ emotional states over the whole walk in the two experimental conditions. Consistent with the positive emotional state perceived in the second half of the walk, the state of relaxation experienced after the walk also did not differ between the two lighting conditions. Furthermore, participants’ relaxation judgements after the park walk were more negative overall for females than the more neutral ratings of males. Our results highlight the importance of lighting colour at night for the design of future affect-smart cities that may consider individual and group characteristics with the ultimate intent of promoting public well-being.

Climate change, food security, and diarrhoea prevalence nexus in Tanzania

The impact of climate change on food security and public health has hindered poverty reduction efforts in developing nations, including Tanzania, resulting in the impoverishment of millions and compromising both health and food production. To unravel these complex interactions, rigorous scientific research is indispensable. Leveraging three waves of the Agriculture Sample Census (2002/03, 2007/08, 2019/20), this study meticulously examines the interplay between climate change, food security, and diarrhoea prevalence in Tanzania. Employing Instrumental Variable Probit and Control Function Approach models to address endogeneity and heterogeneity, temperature anomalies serve as instrumental variables. The findings reveal a substantial impact of climate change on both food security (−0.331142, p < 0.01) and diarrhoea incidence (0.214602, p < 0.01). These results signify that climate change places significant stress on food security, rendering households more susceptible to insecurities, and heightens health concerns through increased diarrhoea prevalence. This underscores the urgency of prioritizing public health and well-being through an agricultural lens in climate change mitigation. A comprehensive strategy is imperative, entailing a synergy of sustainable agricultural practices, robust public health interventions, and targeted policies to fortify the adaptive capacity of communities. Special emphasis should be placed on cultivating climate-resilient agricultural systems, ensuring food security, and implementing health programs tailored to address the unique challenges posed by climate-induced factors. Moreover, community engagement and awareness initiatives play a pivotal role in fostering a collective understanding and commitment to sustainable practices, contributing to the overall resilience of societies amidst the challenges of climate change.

Impact of trans fatty acids on human health

The detrimental impact of trans fatty acids (TFAs) on human health has been extensively studied. This comprehensive review provides a critical analysis of the significant adverse effects of TFAs on human health. Moreover, a comprehensive evaluation of methods to reduce trans fatty acid consumption and enhance public health is provided. The paper emphasizes successful interventions performed at many levels, offering useful insights into viable strategies for tackling the urgent problem of harm caused by TFA. The compilation of evidence emphasizes the pressing need to reduce TFA intake in order to improve human health outcomes. This extensive analysis provides a significant source of information for politicians, healthcare professionals, and individuals who want to understand and tackle the various harmful effects of TFAs on human health. By increasing knowledge and offering scientifically supported suggestions, it enables individuals involved to make well-informed decisions in order to decrease trans fatty acid consumption and protect public well-being.

Understanding the Experiences of COVID-19 Public Health Measures and Well-Being: A Qualitative Study Among Older Adults in Quebec, Canada.

This interpretative descriptive study explores how public health measures implemented during the first wave of the COVID-19 pandemic in Quebec, Canada, affected the well-being of older adults. Twenty-six participants aged 60-81 took photographs to depict how COVID-19 public health measures affected their well-being and were invited to discuss their photographs in virtual focus groups. Data were analyzed using thematic analysis. The impacts of health measures on the well-being of participants were framed according to three overarching themes. First, participants endured an intensification of ageism, feeling diminished and excluded from their social spheres. Second, they faced a burden of loneliness due to the loss of connections with their communities, particularly for those who were single and without children. Third, participants highlighted navigating a degradation of social cohesion. This manifested through tensions and distrust in both the public and private spheres, as well as acts of resistance in response to rules deemed unjust. While public health measures were essential to prevent onward transmission of COVID-19 and mortality, they negatively impacted older adults' self-image, loneliness, and trust in society. This study argues for a rethinking of public health norms specific to older adults to address potential sources of inequality. In particular, a greater emphasis is needed on social connectedness and addressing the unique needs of older adults during pandemics.

Assessing the growing threat of heat stress in the North Africa and Arabian Peninsula region connected to climate change

Climate change exacerbates extreme heat events in the North Africa and Arabian Peninsula (NAAP) region, posing a significant threat to human health and well-being. This study proposes a novel approach for reliable mapping of population exposure in NAAP to different UTCI levels under future climate change scenarios by improved prediction of UTCI using machine learning (ML) methods. Daily mean UTCI was calculated using hourly ERA-HEAT data from 1979 to 2022. Sobol's global sensitivity analysis was used to identify the most influential meteorological variables affecting UTCI. Three ML models were trained to predict monthly UTCI based on these variables. The best-performing model was used to generate historical and future projections of UTCI for four CMIP6 climate models under Paris Agreement goal scenarios. Finally, the projected change in population exposure to mean UTCI was assessed by comparing historical and future projections. The results showed a significant influence of air temperature, wind speed, surface pressure, solar radiation, and humidity on UTCI in NAAP. Estimation of UTCI using these variables showed a higher performance of random forest (RF) (Kling-Gupta Efficiency = 0.84) compared to other models. The projection of UTCI from CMIP6 climatic model simulations using the RF model revealed a decrease in UTCI for the 1.5 °C temperature rise scenario by 0.25–0.75 °C, while an increase by 0.25–0.75 °C for the 2.0 °C temperature rise scenario in most of NAAP. The study revealed that even a modest increase of 0.5 °C in global warming could lead to a 20-day increase in the number of days with moderate thermal stress in Egypt and Sudan and a significant increase in the number of days with strong thermal stress in the Arabian Peninsula. The population exposure to heat stress would increase significantly even under the most ambitious Paris Agreement goals. These findings highlight the urgent need for adaptation and mitigation strategies to protect public health and well-being in the NAAP region from escalating risks.

Green Oases in the Concrete Desert: Combatting Beijing’s Heat with Urban Greenery

In the face of rapid urbanization, Beijing confronts the escalating challenge of the Urban Heat Island (UHI) effect, characterized by significantly higher temperatures in urban areas compared to their rural surroundings. This phenomenon not only exacerbates the thermal discomfort in city environments but also poses a substantial risk to public health and well-being. Amidst this urban climate crisis, the potential of green spaces emerges as a crucial mitigative and adaptive strategy. This comprehensive study embarks on an in-depth exploration of the multifaceted role that urban greenery plays in combatting the UHI effect and bolstering the well-being of Beijing’s residents. Employing a triangulated research methodology, the study harnesses high-resolution satellite imagery to delineate the thermal footprint of green spaces within the urban matrix of Beijing. Through detailed temperature analysis, it meticulously quantifies the extent to which parks, gardens, and tree-lined avenues contribute to cooling urban environments. Complementing this quantitative analysis, the study engages with the urban populace through extensive surveys, capturing perceptions and lived experiences of the thermal environment and the subjective well-being associated with access to green spaces. The findings reveal a significant cooling effect attributed to urban greenery, with marked temperature reductions in areas with dense vegetation cover. Beyond the thermal benefits, the research uncovers a positive correlation between access to green spaces and improvements in residents’ physical and psychological health, highlighting the critical role of green spaces in promoting urban livability and sustainability. This study advances the discourse on urban planning and public health by providing empirical evidence of the benefits of integrating green spaces into the urban fabric of Beijing. It underscores the urgency of adopting green infrastructure as a standard in urban development projects, not only as a countermeasure to the UHI effect but also as a foundational element for enhancing the quality of life in densely populated urban centers. The research concludes with strategic recommendations for urban policymakers, advocating for the expansion and optimization of green spaces as indispensable assets for achieving a resilient and health-promoting urban environment in Beijing.