ABSTRACT
The identification of unknown human remains is a significant and ongoing challenge in South Africa, worsened by the country's high murder rate. The rate of decomposition in South Africa is significantly influenced by vertebrate scavenging, which, if not considered, can impede the accurate estimation of the post-mortem interval. Scavenging patterns vary greatly depending on the environment and ecological region, and there is limited data for the Western Cape province. To address this gap, two clothed and uncaged pig carcasses weighing 60 kg each were placed in the field in July 2021 and January 2022, respectively. Motion-activated infrared-capable trail cameras were used to observe decomposition, scavenger species, and their activities. Additionally, a comparative sample of 16 unclothed carcasses deployed between 2014 and 2016 in the same habitat were analyzed to assess the impact of clothing and biomass load. The study found three main results: (1) Regardless of habitat or biomass load, it took significantly less time to reach decomposition milestones (25%, 50%, and 75%) during the summer season; (2) the presence of mongoose scavengers had a greater impact on the time required to reach milestones during winter compared to summer; and (3) single carcass deployments reached the milestones faster than multi-carcass deployments in both seasons. This research highlights the potential inaccuracy of current methods for estimating the post-mortem interval when scavenging activity is not considered or documented in the underlying experimental data, particularly for environments or ecological biomes where scavengers actively impact decomposition rates.
Subject(s)
Biomass , Clothing , Feeding Behavior , Postmortem Changes , Seasons , Animals , South Africa , Swine , Models, Animal , Forensic Pathology/methodsABSTRACT
Urban air quality persists as a global concern, with critical health implications. This study employs a combination of machine learning (gradient boosting regression, GBR) and spatial analysis to better understand the key drivers behind air pollution and its prediction and mitigation strategies. Focusing on New York City as a representative urban area, we investigate the interplay between urban characteristics and weather factors, showing that urban features, including traffic-related parameters and urban morphology, emerge as crucial predictors for pollutants closely associated with vehicular emissions, such as elemental carbon (EC) and nitrogen oxides (NOx). Conversely, pollutants with secondary formation pathways (e.g., PM2.5) or stemming from nontraffic sources (e.g., sulfur dioxide, SO2) are predominantly influenced by meteorological conditions, particularly wind speed and maximum daily temperature. Urban characteristics are shown to act over spatial scales of 500 × 500 m2, which is thus the footprint needed to effectively capture the impact of urban form, fabric, and function. Our spatial predictive model, needing only meteorological and urban inputs, achieves promising results with mean absolute errors ranging from 8 to 32% when using full-year data. Our approach also yields good performance when applied to the temporal mapping of spatial pollutant variability. Our findings highlight the interacting roles of urban characteristics and weather conditions and can inform urban planning, design, and policy.
Subject(s)
Air Pollutants , Air Pollution , Air Pollutants/analysis , Particulate Matter/analysis , Environmental Monitoring/methods , Air Pollution/analysis , Weather , Machine LearningABSTRACT
Existing literature has widely explored the individual roles of housing and neighborhood quality, and there is limited research examining their interactive effects on mental health. This 3-year cohort study utilized a longitudinal design to investigate the individual and interactive effects of housing and neighborhood quality on mental health among 962 community-dwelling adults in Hong Kong. Participants were asked to rate their residential qualities over the 3-year period. Mental health outcomes, including levels of psychological distress and common mental disorders (CMD), were assessed using the Revised Clinical Interview Schedule (CIS-R). Logistic regression and generalized linear models were used to examine the association between housing and neighborhood quality and CMD/psychological distress, adjusting for sociodemographic and residential characteristics and baseline mental disorders. Housing quality was associated with the 3-year CMD (adjusted OR 0.95; 95% CI 0.91 to 0.98). Likewise, neighborhood quality was associated with CMD over 3 years (adjusted OR 0.92; 95% CI 0.87 to 0.96). In a separate model including both quality measures, the effect of housing quality on CMD was attenuated, whereas the neighborhood impact remained significant (adjusted OR 0.92; 95% CI 0.87 to 0.98). Generalized linear models indicated that for participants residing in substandard housing, those with high neighborhood quality had lower CIS-R scores at follow-up compared to those with low neighborhood quality (p = 0.041). Better neighborhood quality alleviated the detrimental effects of poor housing quality on mental health. Planning for an enhanced neighborhood would improve population mental health in an urban environment.
Subject(s)
Housing , Mental Disorders , Mental Health , Residence Characteristics , Humans , Hong Kong/epidemiology , Male , Female , Middle Aged , Housing/statistics & numerical data , Adult , Mental Disorders/epidemiology , Retrospective Studies , Residence Characteristics/statistics & numerical data , Neighborhood Characteristics , Aged , Longitudinal Studies , Socioeconomic FactorsABSTRACT
BACKGROUND: Cardiometabolic conditions are major contributors to the global burden of disease. An emerging body of evidence has associated access to and surrounding public open spaces (POS) and greenspace with cardiometabolic risk factors, including obesity, body mass index (BMI), hypertension (HTN), blood glucose (BG), and lipid profiles. This systematic review aimed to synthesize this evidence. METHODS: This systematic review was conducted based on the PRISMA guidelines. Four electronic databases including Web of Science, PubMed, Scopus, and Google Scholar were searched for eligible articles published until July 2023. All observational studies which assessed the association of greenspace and POS with cardiometabolic risk factors including obesity, BMI, HTN, BG, and lipid profiles were included and reviewed by two authors independently. Heterogeneity between studies was assessed using the I2 index and Cochrane's Q test. Random/fixed effect meta-analyses were used to combine the association between greenspace exposure with cardiometabolic risk factors. RESULTS: Overall, 118 relevant articles were included in our review. The majority of the articles were conducted in North America or Europe. In qualitative synthesis, access or proximity to greenspaces or POS impacts BMI and blood pressure or HTN, BG, and lipid profiles via various mechanisms. According to the random effect meta-analysis, more access to greenspace was significantly associated with lower odds of HTN (odds ratio (OR): 0.81, 95% confidence intervals (CIs): 0.61-0.99), obesity (OR: 0.83, 95% CIs: 0.77-0.90), and diabetes (OR:0.79, 95% CI: 0.67,0.90). CONCLUSIONS: Findings of this systematic review and meta-analysis suggested that greenspace accessibility is associated with some cardiometabolic risk factors. Improving greenspace accessibility could be considered as one of the main strategies to reduce cardiometabolic risk factors at population level.
Subject(s)
Cardiometabolic Risk Factors , Humans , Risk Assessment , Male , Female , Adult , Middle Aged , Obesity/epidemiology , Obesity/diagnosis , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/prevention & control , Cardiovascular Diseases/etiology , Protective Factors , Hypertension/epidemiology , Hypertension/diagnosis , Hypertension/physiopathology , Aged , Young Adult , Blood Glucose/metabolism , Body Mass Index , Residence CharacteristicsABSTRACT
Coastal cities are major centers of economic activity, which at the same time has negative consequences for the environment. The present study aimed to determine the concentrations and sources of PTEs in the urban soils of Taganrog, as well as to assess the ecological and human health risks. A total of 47 urban and 5 background topsoils samples were analyzed by ICP-MS and ICP-AES. A significant excess of Cu, Zn, and Sb was noted in urban soils compared to the upper continental crust and average world-soil (1.7-2.9 times). Statistical analysis showed that the elements in soils were of geogenic, mixed and anthropogenic origin. According to the single pollution index (PI), the greatest danger of soil pollution was represented by anthropogenic elements, namely Cu, W, Pb, Zn, Cd, and Sn, the levels of which were increased in residential and industrial areas. The median contents of As, Mn, Cr, Sr, Mo, Sb, Cu, W, Pb, and Zn were 1.1-2.1 times higher, while Cd and Sn were 2.5 folds higher in the urban soils compared to the background ones. The total pollution index (ZC) showed that only 15% of the soils had high level of pollution, which is typical for the industrial areas. Overall ecological risks were negligible or low in 92% of soils, and were mainly due to elevated levels of Cu, Zn, As, and Pb. Non-carcinogenic risks to humans were mainly related to exposure to La and Pb. The hazard index (HI) values for all PTEs were less than ten, indicating that overall non-carcinogenic risk for adults and children was low-to-moderate and, moderate, respectively. The total carcinogenic risk (TCR) exceeded threshold and corresponded to low risk, with Pb, As, and Co being the most important contributors. Thus, the industrial activities of Taganrog is the main source of priority pollutants.
Subject(s)
Cities , Environmental Monitoring , Soil Pollutants , Risk Assessment , Soil Pollutants/analysis , Humans , Soil/chemistry , Metals, Heavy/analysisABSTRACT
INTRODUCTION: Sleep disorders have a significant negative impact on mental and physical health, especially among the elderly. Various factors can affect the sleep quality of elderly people. The aim of this research to investigate the effect of urban and rural environments on the sleep quality of elderly people with emphasis on physical activity. METHOD: Four hundred and thirty-nine elderly people (226 city residents and 213 village residents) in urban and rural areas of Bushehr (Southern Iran), volunteered to participate in the present study. Information was collected via the General information questionnaire and Petersburg Sleep Questionnaire. RESULT: The results showed that active elderly women (p < 0.001), and total active elderly (male + female) (p < 0.001) living in urban areas compared to inactive elderly and also in rural areas active elderly women (p < 0.001), active elderly men (p < 0.001) and total active elderly (male + female) (p < 0.001) had better overall sleep quality in compared to inactive elderly. Also, elderly men (p < 0.001) and the total elderly (male + female) (p < 0.001) living in urban areas had better sleep quality than the elderly in rural areas. CONCLUSION: Based on the findings, it can be concluded that the way of life (being active) as well as the living environment can affect the sleep quality of elderly people, so that active elderly people and also elderly people living in urban environments had better sleep quality.
Subject(s)
Rural Population , Sleep Quality , Urban Population , Humans , Female , Male , Aged , Iran/epidemiology , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , Surveys and Questionnaires , Aged, 80 and over , Motor Activity , Middle AgedABSTRACT
The progressive growth of urban environments has increasingly forced populations of nonhuman primates to coexist with humans in many cities, which has resulted in problems such as behavioral alterations, conflicts with humans, and threats to the health of the monkeys, due to their consumption of anthropogenic foodstuffs. These anthropogenic foods, which are rich in calories, are the principal driver of the proximity between humans and primates, even though the acquisition of these foods tends to be risky for the monkeys and involve a variety of challenges derived from specific features of the urban environment. The present study evaluated the success/risk relationship of foraging for anthropogenic food by tufted capuchins (Sapajus libidinosus) in Brasília National Park. The data were analyzed using a binary logistic regression, with the backward-stepwise Wald method, to investigate the factors related to the foraging success of the capuchins, considering variables such as their sex and age, the type of approach and its context, and interactions with humans. The capuchins were influenced by the anthropogenic context, which affected their foraging strategies and diet. Interactions with humans reduced the success of foraging for anthropogenic foods. Conflicts between humans and the capuchins were common, especially in the context of access to food. The capuchins thus preferred to access feeding resources directly, probably due to the reduced human interference, which resulted in greater foraging success for unattended food brought by park visitors and the raiding of trash cans. Based on the observed behavior patterns, a number of measures can be proposed to mitigate these conflicts. These recommendations include not bringing food into areas frequented by the capuchins, not reacting to approaching animals, and removing all trash generated during a visit. A cleaning team dedicated to the maintenance of the visitation area free of anthropogenic waste is also be recommended.
Subject(s)
Cebinae , Feeding Behavior , Parks, Recreational , Animals , Brazil , Male , Female , Humans , Cebinae/physiology , Human-Animal Interaction , Diet/veterinaryABSTRACT
Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.
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Agent-based models represent a promising approach for simulating transport systems and assessing their environmental noise impact, potentially enhancing standard noise exposure assessments. However, it is very important to understand the relevance of these assessments within the context of models initially designed for transport studies. Then, this research investigates the utilization of agent-based transport models when coupled with environmental models to assess individual exposure to transport-related noise. This is achieved by proposing a method to evaluate this approach across four dimensions: spatial, temporal, individual, and activity patterns. This evaluation is demonstrated and discussed with an exemplification model applied in the Lyon Metropolitan Area using open-source tools (MATSim, EQASim, NoiseModelling), which is a representative framework of the current literature. The findings encompass a range of issues, including the conceptualization of exposure contexts and activity spaces, the resolution of the acoustic content, the disaggregation of data at the individual level, the variability in noise reactions, and the correlation structures between social and exposure profiles. The study contributes to the advancement of exposure assessment with insights for future improvements in the field. Further, it underscores the need for more quantitative analyses and scientific research into momentary noise exposure and social epidemiology.
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There are significant gaps in air quality monitoring across many low- and middle-income countries, which can be filled by bioindicators like lichen. This study examined the links between lichen and air quality across urban environments in Nigeria. Lichen surveys and air quality monitoring were carried out across four major cities focusing on NO2, SO2, PM2.5, and PM10. Association rule mining was used to identify robust rules defining the association between lichen and air quality categories. For the maximal frequent set with Lichen in the antecedent, 9 and 5 rules were identified by A priori and Eclat, respectively. These indicated that three genera: Diorygma, Pyxine, and Physcia are the most commonly associated lichen with poor air quality particularly NO2 and SO2. This showed that these lichens are viable indicators of long-term air quality due to their consistent occurrence across the rules from different algorithms.
Subject(s)
Air Pollutants , Air Pollution , Lichens , Air Pollutants/analysis , Environmental Monitoring , Nitrogen Dioxide , Air Pollution/analysis , Data Mining , Particulate Matter/analysisABSTRACT
Oxidation of volatile organic compounds (VOCs) forms oxygenated organic molecules (OOMs), which contribute to secondary pollution. Herein, we present measurement results of OOMs using chemical ionization mass spectrometry with nitrate as the reagent ion in Shanghai. Compared to those in forests and laboratory studies, OOMs detected at this urban site were of relatively lower degree of oxygenation. This was attributed to the high NOx concentrations (â¼44 ppb), which overall showed a suppression on the propagation reactions. As another result, a large fraction of nitrogenous OOMs (75%) was observed, and this fraction further increased to 84% under a high NO/VOC ratio. By applying a novel framework on OOM categorization and supported by VOC measurements, 50 and 32% OOMs were attributed to aromatic and aliphatic precursors, respectively. Furthermore, aromatic OOMs are more oxygenated (effective oxygen number, nOeff = 4-6) than aliphatic ones (nOeff = 3-4), which can be partly explained by the difference in initiation mechanisms and points to possible discrimination in termination reactions. This study highlights the roles of NOx in OOM formation in urban areas, as well as the formation of nitrogenous products that might show discrimination between aromatic and aliphatic VOCs.
Subject(s)
Air Pollutants , Ozone , Volatile Organic Compounds , Air Pollutants/analysis , Volatile Organic Compounds/analysis , China , Ozone/analysis , Environmental Monitoring , Nitrogen/analysisABSTRACT
Built environment stocks have attracted much attention in recent decades because of their role in material and energy flows and environmental impacts. Spatially refined estimation of built environment stocks benefits city management, for example, in urban mining and resource circularity strategy making. Nighttime light (NTL) data sets are widely used and are regarded as high-resolution products in large-scale building stock research. However, some of their limitations, especially blooming/saturation effects, have hampered performance in estimating building stocks. In this study, we experimentally proposed and trained a convolution neural network (CNN)-based building stock estimation (CBuiSE) model and applied it to major Japanese metropolitan areas to estimate building stocks using NTL data. The results show that the CBuiSE model is capable of estimating building stocks at a relatively high resolution (approximately 830 m) and reflecting spatial distribution patterns, although the accuracy needs to be further improved to enhance the model performance. In addition, the CBuiSE model can effectively mitigate the overestimation of building stocks arising from the blooming effect of NTL. This study highlights the potential of NTL to provide a new research direction and serve as a cornerstone for future anthropogenic stock studies in the fields of sustainability and industrial ecology.
Subject(s)
Built Environment , Deep Learning , Cities , Industry , JapanABSTRACT
Urban areas are characterized by the presence of certain potentially toxic elements including molybdenum (Mo). Therefore, compositional data analysis combined with geospatial mapping was applied in this study to reveal the spatial distribution characteristics of Mo in courtyard surface dust (dust), soils, and river sediments (sediments), to identify potential sources of Mo, and to reveal Mo geochemical associations in different urban environmental mediums. The mean contents of Mo decreased in the following order: dust (11.9 mg/kg) - soil (5.84 mg/kg) - sediment (4.87 mg/kg). The highest maximum Mo content among the studied mediums (61.8 mg/kg) was detected in dust. It was the only investigated medium where a very high level of Mo enrichment was observed (4.4% of samples). Moreover, a significant level of enrichment predominated in dust (47% of samples) whereas in soil, moderate enrichment prevails (68.5%). A significant correlation of Mo contents was observed with Zn contents in all the studied mediums, and with Ca contents in soil and sediments. A significant negative correlation was observed only between Mo contents in dust and sampling site altitudes suggesting that high-rise buildings might play the role of geochemical barriers. Principal component analysis, k-means and hierarchical clustering showed that in the geogenic elements soil group Mo showed an affinity to be bound by Fe/Mn oxide/hydroxides whereas the Mo coprecipitation, complexation and absorption by carbonates predominated in the Mo-related soil group (geochemical compositional association of Mo, Zn, Cu, Pb, and Ca) under anthropogenic influence. For dust, the geochemical compositional association was the same, but in the geogenic-related group, Cu was the most closely associated element instead of Zn. The spatial location of the Mo-related group of samples identified by k-means clustering indicates that Mo concentrate processing plant may be a potential source of Mo introduction into the urban environment.
Subject(s)
Altitude , Molybdenum , Cluster Analysis , Dust , SoilABSTRACT
Earth observation environmental features measured through remote sensing and models of vector mosquitoes species Aedes aegypti and Ae. albopictus provide an advancement with regards to dengue risk in urban environments of subtropical areas of Argentina. The authors aim to estimate the effect of landscape coverage and spectral indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Water Index [NDWI] and Normalized Difference Built-up Index [NDBI]) on the larvae abundance of Ae. aegypti and Ae. albopictus in Eldorado, Misiones, Argentina using remote satellite sensors. Larvae of these species were collected monthly (June 2016 to April 2018), in four environments: tire repair shops, cemeteries, dwellings and an urban natural park. The proportion of landscape coverage (water, urban areas, bare soil, low vegetation and high vegetation) was determined from the supervised classification of Sentinel-2 images and spectral indices, calculated. The authors developed spatial models of both vector species by generalized linear mixed models. The model's results showed that Ae. aegypti larvae abundance was better modelled by NDVI minimum values, NDBI maximum values and the interaction between them. For Ae. albopictus proportion of bare soil, low vegetation and the interaction between both variables explained better the abundance.
Subject(s)
Aedes , Dengue , Animals , Mosquito Vectors , Argentina/epidemiology , Soil , Larva , Dengue/epidemiology , Dengue/veterinaryABSTRACT
BACKGROUND: The association of the built environment and the structural availability of services/amenities with adolescent birth rates (ABR) has been overlooked in Latin America. We investigated the association of the availability, and changes in the availability, of services/amenities with ABR in 92 Mexican cities. METHODS: We estimated ABR using data on live birth registration linked to municipality of residence at the time of birth from 2008-2017. The number of services/amenities were obtained from the National Statistical Directory of Economic Units in 2010, 2015, and 2020 and grouped as follows: education, health care, pharmacies, recreation, and on- and off-premises alcohol outlets. Data were linearly interpolated to obtain yearly estimates. We estimated densities per square km by municipality. We fitted negative binomial hybrid models, including a random intercept for municipality and city, and adjusted for other social environment variables. RESULTS: After adjustment a 1-unit increase in the density of recreation facilities, pharmacies, and off-premises alcohol outlets within municipalities was associated with a 5%, 4% and 12% decrease in ABR, respectively. Municipalities with higher density of education, recreational and health care facilities had a lower ABR; in contrast, municipalities with a higher density of on-premises alcohol experienced a higher ABR. CONCLUSION: Our findings highlight the importance of economic drivers and the need to invest in infrastructure, such as pharmacies, medical facilities, schools, and recreation areas and limit the availability of alcohol outlets to increase the impact of current adolescent pregnancy prevention programs.
Subject(s)
Birth Rate , Parturition , Female , Pregnancy , Humans , Adolescent , Cities/epidemiology , Ethanol , Educational StatusABSTRACT
BACKGROUND: Living in urban environments is associated with several health risks (e.g., noise, and air pollution). However, there are also beneficial aspects such as various opportunities for social activities, which might increase levels of social participation and (physically) active mobility that in turn have positive effects on health and well-being. However, how aspects of the environment, active mobility, and social participation are associated is not well established. This study investigates the moderating effect of low vs. high walkability neighborhoods on the associations between active mobility, and social participation and integrates individuals' subjective perception of the neighborhood environment they are living in. METHODS: Cross-sectional data from 219 adults (48% female, mean age = 46 ± 3.8 years) from 12 urban neighborhoods (six low, six high walkability) were analyzed: First, social participation, active mobility, and subjective neighborhood perceptions were compared between people living in a low vs. high walkability neighborhood via t-tests. Second, multigroup path analyses were computed to explore potential differences in the associations between these variables in low vs. high walkability neighborhoods. RESULTS: Social participation, active mobility, and subjective neighborhood perceptions didn't differ in low vs. high walkability neighborhoods (p: 0.37 - 0.71). Active mobility and subjective neighborhood perceptions were significantly stronger related to social participation in low vs. high walkability neighborhoods (active mobility in low: ß = 0.35, p < .01 vs. high: ß = 0.09, p = .36; subjective neighborhood perceptions in low: ß = 0.27, p < .01 vs. high: ß = 0.15, p = .18). CONCLUSIONS: Despite living in neighborhoods with objectively different walkability, participants rated social participation and active mobility equally and perceived their neighborhoods similarly. However, zooming into the interrelations of these variables reveals that social participation of residents from low walkability neighborhoods depends stronger on active mobility and perceiving the environment positively. Positive perceptions of the environment and active mobility might buffer the objectively worse walkability. Future research should focus on underlying mechanisms and determinants of subjective neighborhood perceptions and active mobility, especially in low walkability neighborhoods.
Subject(s)
Social Participation , Walking , Adult , Humans , Female , Middle Aged , Male , Cross-Sectional Studies , Residence Characteristics , Cities , Environment DesignABSTRACT
Convoy driving, a specialized form of collaborative autonomous driving, offers a promising solution to the multifaceted challenges that transportation systems face, including traffic congestion, pollutant emissions, and the coexistence of connected autonomous vehicles (CAVs) and human-driven vehicles on the road, resulting in mixed traffic flow. While extensive research has focused on the collective societal benefits of convoy driving, such as safety and comfort, one critical aspect that has been overlooked is the willingness of individual vehicles to participate in convoy formations. While the collective benefits are evident, individual vehicles may not readily embrace this paradigm shift without explicit tangible benefits and incentives to motivate them. Moreover, the objective of convoy driving is not solely to deliver societal benefits but also to provide incentives and reduce costs at the individual level. Therefore, this research bridges this gap by designing and modeling the societal benefits, including traffic flow optimization and pollutant emissions, and individual-level incentives necessary to promote convoy driving. We model a fundamental diagram of mixed traffic flow, considering various factors such as CAV penetration rates, coalition intensity, and coalition sizes to investigate their relationships and their impact on traffic flow. Furthermore, we model the collaborative convoy driving problem using the coalitional game framework and propose a novel utility function encompassing incentives like car insurance discounts, traffic fine reductions, and toll discounts to encourage vehicle participation in convoys. Our experimental findings emphasize the need to strike a balance between CAV penetration rate, coalition intensity, size, and speed to realize the benefits of convoy driving at both collective and individual levels. This research aims to align the interests of road authorities seeking sustainable transportation systems and individual vehicle owners desiring tangible benefits, envisioning a future where convoy driving becomes a mutually beneficial solution.
ABSTRACT
This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O3, a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH4, it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO2: - 40.0% and NO: - 33.3%) and VOCs (C7H8: - 36.3% and C6H6: - 32.8%), followed by SO2 (- 27.0%), PM10 (- 19.7%), CO (- 16.6%), CH4 (- 14.7%), TH (- 11.6%) and PM2.5 (- 10.1%), the O3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO2, CO, C6H6, C7H8, TH and CH4, suburban zones for PM2.5 and O3, urban traffic sites for NO and PM10, and keeping variations reasonably similar at all the stations in the case of NO2. Those pollution changes were not translated in variations on geospatial pattern, except for NO, O3 and SO2. Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments. Supplementary Information: The online version contains supplementary material available at 10.1007/s13762-022-04464-6.
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Recreation and sports environment is an essential part of the urban space, which is the most important factor in improving and maintaining health of the citizens, contributing to better mental health, cognitive functions, lower overall mortality, higher life expectancy, lower morbidity and mortality from cardiovascular diseases, prevalence of obesity and type 2 diabetes, better pregnancy and birth outcomes. Recreation and sports environment of the urban space includes the city's greenery, recreational areas, areas for physical activities and sports, and waterfront areas. This study uses a correlation analysis to analyze the impact of the city recreation and sports environment on health of the working and post-working population. The study was conducted in 2019 on the example of large and huge urban cities of the Moscow region populated with more than 125,000 people. Based on the correlation analysis results, the authors have demonstrated the impact of the overall set of all sports facilities, sports structures, flat sports structures, swimming pools, sports halls, and public green spaces in cities on health of the post-working population. The study has also shown the impact of swimming pools, the overall set of all types of sports facilities, sports structures, flat sports structures, sports halls, and public green spaces in cities on health of the working-age population. The authors come to the conclusion that development and ongoing support and maintenance of the city recreation and sports environment serve as an important objective of the city administrations, resulting in the improved physical activity of the citizens and lower morbidity among the urban population.
Subject(s)
Diabetes Mellitus, Type 2 , Recreation , Humans , Cities , Urban Population , ExerciseABSTRACT
The analysis of various social, economic, and demographic factors demonstrates different degrees and directions of their impact on human body systems and human health in general. The examination of residents of several cities of Russia and neighboring countries provides an opportunity to assess strength and direction of relationship between socioeconomic factors and morphofunctional health. The comprehensive morphofunctional examination was applied to 722 young females aged 18.8±0.05 years from six cities: Moscow, Samara, Saransk, Arkhangelsk (the Russian Federation), Tiraspol (the Transdniestria Moldavian Republic), and Baku (the Republic of Azerbaijan). The economic, demographic, social and ecological indicators of the city and relevant region were considered as factors of urban environment. The Spearman's rank correlation coefficient (RS). was used as measure of relation between attributes. The variability of morphophysiological characteristics is hardly related to the population density (RS -0.18-0.15). At the same time the greatest contribution was demonstrated by complex of economic factors and environmental pollution (RS up to -0.29 for both). The relationships between functional indicators of cardiovascular system and economic status of the region, associated demographic factors, and indicators of air pollution were established in the surveyed cities. In overall, the results suggest that cardiovascular system is the most susceptible area to influence of city-level social economic factors and demonstrates deterioration of functional indicators under economic decline at the regional level. In other morphophysiological systems, adaptive changes were established only as tendencies. The deterioration conditions of human body systems under impact of urban environment factors is evident in some cities. The observed deterioration potentially can adversely affect health during growth and will further be aggravated by ongoing negative environmental influences. In this regard, it is necessary to enhance knowledge about impact of external influences on human health and body systems to develop directed preventive measures improving quality of life.