Aedes aegypti oviposition dynamics in towns with low human population density in yungas and dry chaco, Salta, Argentina

We assessed the presence of Aedes aegypti in five ecorregions of Salta province and compared the oviposition activity of Ae. aegypti using ovitraps in towns of two contrasting ecoregions (yungas and Chaco dry forests) in the province of Salta, Argentina, a major contrast in these ecoregions are rain patterns and altitude. Our aim was to estimate how oviposition activities were associated with the ecoregion and site scale local environmental variables. Mosquito oviposition activity was monitored weekly during the summer using ovitraps. Predictor variables were ecoregion, town, and meteorological variables. The effect of the predictor variables was measured on the response variables using multi-model inference. Besides yungas, the presence of Aedes aegypti was confirmed in towns of dry Chaco and High Monte. The only factor that had a significant effect on the presence of eggs in the ovitraps was the ecoregion, with the frequency of positives being higher in yungas. For the number of eggs, the ecoregion, the night temperature of the first week and the NDVI would explain said variable. Overall, results indicate that the variations between towns would be more related with their ecological and climatic characteristics than with the more immediate meteorological variations.

The impact of urban rain on the changes of bare and artificially patinated bronze during 9-year exposure

Atmospheric pollutants in the air form acid rain which interacts with bronze surfaces exposed in urban outdoor environment. In this study, different types of patinas on bronze were investigated during and after 9 years of exposure to urban environment in moderately polluted continental city. Natural bronze patina and artificial brown sulphide, green chloride, and green-blue nitrate patinas were investigated. Visual assessment was carried out at defined periods. After 9 years of exposure, an electrochemical study was performed to investigate the electrochemical activity of the patinas in artificial urban rain. Additionally, the patinas were characterised using a variety of techniques, including metallographic examination, scanning electron microscopy/energy dispersive X-ray spectroscopy, Raman spectroscopy, X-ray diffraction analysis, X-ray-photoelectron spectroscopy, and time-of-flight secondary ion mass spectrometry to analyse the surface morphology, chemical composition, and stratigraphic features of the patinas. Evolution of the patinas was shown to be a result of both, the composition of the acid rain and the hydrophobicity of the patinated surfaces.

Smartphone-based ecological momentary assessment reveals an incremental association between natural diversity and mental wellbeing

Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

Assessing sustainable waste management practices in Rajshahi City Corporation: an analysis for local government enhancement using IoT, AI, and Android technology

This study addresses the pressing challenge of inefficient waste management practices within the Rajshahi City Corporation (RCC), Bangladesh. Despite rapid urbanization and escalating waste generation rates, RCC struggles with diverse waste disposal practices, limited supervision, irregular waste collection schedules, and inadequate disposal infrastructure. In this context, this study examines the possible improvements that could be made by combining the Internet of Things (IoT), artificial intelligence (AI), and Android application to improve waste management methods in the RCC. The study's foundation is a vast amount of information gathered from residents, with particular attention paid to waste disposal methods, the role of the local government, the frequency of waste collection, and public attitudes toward waste management. The results point to a complicated waste management environment with a range of waste disposal practices, little supervision, irregular waste collection, and insufficient disposal methods. The importance of RCC in waste management is emphasized, highlighting the need for proactive measures including effective monitoring, constant waste collection, and routine drain cleaning. Additionally, it is suggested that combining IoT, AI, and Android technology is a possible way to improve waste management procedures. These technologies have the potential to increase productivity, lessen their negative effects on the environment, and produce cleaner, more sustainable urban environments.

Urban environment during pregnancy and childhood and white matter microstructure in preadolescence in two European birth cohorts

Growing evidence suggests that urban environment may influence cognition and behavior in children, but the underlying pollutant and neurobiological mechanisms are unclear. We evaluated the association of built environment and urban natural space indicators during pregnancy and childhood with brain white matter microstructure in preadolescents, and examined the potential mediating role of air pollution and road-traffic noise. We used data of the Generation R Study, a population-based birth cohort in Rotterdam, the Netherlands (n = 2725; 2002-2006) for the primary analyses. Replication of the main findings was attempted on an independent neuroimaging dataset from the PELAGIE birth cohort, France (n = 95; 2002-2006). We assessed exposures to 12 built environment and 4 urban natural spaces indicators from conception up to 9 years of age. We computed 2 white matter microstructure outcomes (i.e., average of fractional anisotropy (FA) and mean diffusivity (MD) from 12 white matte tracts) from diffusion tensor imaging data. Greater distance to the nearest major green space during pregnancy was associated with higher whole-brain FA (0.001 (95%CI 0.000; 0.002) per 7 m increase), and higher land use diversity during childhood was associated with lower whole-brain MD (-0.001 (95%CI -0.002; -0.000) per 0.12-point increase), with no evidence of mediation by air pollution nor road-traffic noise. Higher percentage of transport and lower surrounding greenness during pregnancy were associated with lower whole-brain FA, and road-traffic noise mediated 19% and 52% of these associations, respectively. We found estimates in the same direction in the PELAGIE cohort, although confidence intervals were larger and included the null. This study suggests an association between urban environment and white matter microstructure, mainly through road-traffic noise, indicating that greater access to green space nearby might promote white matter development.

Association of greenspaces exposure with cardiometabolic risk factors: a systematic review and meta-analysis

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.

The generation R study

The urban environment during pregnancy may influence child's respiratory health, but scarce evidence exists on systematic evaluation of multiple urban exposures (e.g., air pollution, natural spaces, noise, built environment) on children's lung function, wheezing, and asthma development. We aimed to examine the association of the urban environment during pregnancy with lung function, preschool wheezing, and school-age asthma. We included 5624 mother-child pairs participating in a population-based prospective birth cohort. We estimated 30 urban environmental exposures including air pollution, road traffic noise, traffic, green spaces, blue spaces, and built environment during pregnancy. At 10 years of age, lung function was measured by spirometry. Information on preschool wheezing and physician-diagnosed school-age asthma was obtained from multiple questionnaires. We described single-exposure associations with respiratory outcomes using an exposome-wide association study. We also identified patterns of urban exposures with hierarchical clustering on principal components analysis and examined their associations with respiratory outcomes using multivariate regression models. Single-exposure analyses showed associations of higher particulate matter (PM) with lower mid-expiratory flow (FEF25-75%) (e.g., for PM < 2.5 μm of diameter [PM2.5] z-score = -0.06 [-0.09, -0.03]) and higher forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) (e.g., for PM2.5 FEV1 0.05 [0.02, 0.08]) after correction for multiple-hypothesis testing. Cluster analysis described three patterns of urban exposures during pregnancy and showed that the cluster characterised by higher levels of air pollution, noise, walkability, street connectivity, and lower levels of natural spaces were associated with lower FEF25-75% (-0.08 [-0.17, 0.00]), and higher odds of preschool wheezing (1.21 [1.03, 1.43]). This study shows that the characteristics of the urban environment during pregnancy are of relevance to the offspring's respiratory health during childhood.

Comparative study and effects of urban green scape on the land surface temperature of a large metropolis and green city

Previous studies have provided valuable insights into the impact of green space (GS) on land surface temperature (LST). However, there is a need for in-depth comparative research on changing landscape patterns in cities and their effects on the urban thermal environment. This study investigates the spatial arrangement of GS and the influence of impervious surfaces on LST in urban areas, examining their cooling and warming effects in the urban landscapes of Beijing and Islamabad. The study aims to assess the impact of the spatial arrangement of GS on LST using a moving window of 1 km2 to analyze the overall effect of landscape patterns on the urban environment. Using Gaofen (GF-2) and Landsat-8 satellite data, we examined the biophysical surface properties of core urban areas. The results indicate a significant difference in the mean LST of 5.44 °C and 3.31 °C between impervious surfaces and GS in Beijing and Islamabad, respectively. The barren land and GS in Islamabad experience a higher LST of 3.39 °C compared to Beijing, which accounts for 1.39 °C. In Beijing, configuration metrics show no significant effect on urban LST, while edge density (ED) exhibits a slightly negative trend. In contrast, in the city of Islamabad, the landscape shape index (LSI), patch density (PD), and number of patches (NP) metrics have a significant influence on LST. The cooling effect of GS patches (0.1-0.5 ha) is more pronounced, while that of GS patches of 15-20 ha shows no significant effect on LST. The temperature difference (TD) of 5.01 °C was observed from the edge of GS in Beijing and 3.3 °C in Islamabad. Considering Islamabad's lush green scape compared to Beijing, this study suggests that Islamabad may experience an increase in LST in the future due to urbanization. This study's findings may assist urban policy-makers in designing sustainable green city layouts that effectively address future planning considerations.

Correlation between microbial communities and volatile organic compounds in an urban soil provides clues on soil quality towards sustainability of city flowerbeds

Soil functionality is critical to the biosphere as it provides ecosystem services relevant for a healthy planet. The soil microbial composition is significantly impacted by anthropogenic activities, including urbanization. In this context, the study of soil microorganisms associated to urban green spaces has started to be crucial toward sustainable city development. Microbes living in the soil produce and degrade volatile organic compounds (VOCs). The VOC profiles may be used to distinguish between soils with various characteristics and management practices, reflecting variations in the activity of soil microbes that use a variety of metabolic pathways. Here, a combined approach based on DNA metabarcoding and GC-MS analysis was used to evaluate the soil quality from urban flowerbeds in Prato (Tuscany, Italy) in terms of microbial biodiversity and VOC emission profiles, with the final aim of evaluating the possible correlation between composition of microbial community and VOC patterns. Results showed that VOCs in the considered soil originated from anthropic and biological activity, and significant correlations between specific microbial taxa and VOCs were detected. Overall, the study demonstrated the feasibility of the use of microbe-VOC correlation as a proxy for soil quality assessment in urban soils.

Social media insights into spatio-temporal emotional responses to COVID-19 crisis

The Coronavirus pandemic has presented multifaceted challenges in urban emotional well-being and mental health management. Our study presents a spatio-temporal sentiment mining (STSM) framework to address these challenges, focusing on the space-time geography and environmental psychology. This framework analyzes the distribution and trends of 6 categories of public sentiments in Shanghai during the COVID-19 crisis, considering the potential urban spatial influencing factors. The research specifically draws on social media data temporally coinciding with the spread of COVID-19 and the pre-trained language model RoBERTa-wwm-ext to classify public sentiment, in order to characterize the distribution and trends of dominant urban sentiment under the influence of epidemic at different phases. The interactions between urban geospatial features and sentiments are further modelled and explained using LightGBM algorithm and SHapley Additive exPlanations (SHAP) technique. The experimental findings reveal the subtle yet dynamic impact of the urban environment on the long-term spatial variation and trends of public sentiment under the epidemic, with green spaces and socio-economic status emerging as significant factors. Regions with higher permanent population consumption demonstrated more positive sentiments, underscoring the significance of socio-economic factors in urban planning and public health policy. This research offers the most extensive analysis to date on the influence of urban characteristics on public sentiment during Shanghai's epidemic life cycle also lays the groundwork for applying the STSM framework in future crises beyond COVID-19.

Comprehensive exploration approach of coal mine water-conducting channels in urban environment: a case study in Xintai, China

In the process of coal mining, prevention and control of water hazard is essential. It is the precondition for water hazard control to detect and determine the distribution of underground water-conducting channels. In urban environments, traditional methods such as active source seismic exploration and transient electromagnetic exploration commonly used in the field are difficult to carry out effectively due to various factors. In this paper, the microtremor survey method (MSM) and the opposing coils transient electromagnetic method (OCTEM) are adapted to conduct the surface exploration of the coal mine water-conducting channels in the urban environment. Combined with the detection results of the low-velocity area and the low-resistivity area, the distribution of water-conducting channels is preliminarily analyzed and determined, which is basically consistent with the drilling and coring results. It verifies the feasibility and accuracy of the comprehensive exploration method used in this paper.

Temporal variation of allergenic potential in urban parks during the vegetation period: a case study from Bratislava, Slovakia

Park greenery represents an oasis for urban residents; however, during the flowering period of trees that produce allergenic pollen grains, these areas threaten individuals suffering from seasonal allergic respiratory diseases. In this study, we evaluated the temporal distribution of the allergenic potential of three most important urban parks in Bratislava over the vegetation period, using a modification of the Urban Green Zone Allergenicity Index (IUGZA) and Individual-Specific Allergenic Potential Index (IISA) designed as a running index - rIUGZA and rIISA. We found that rIUGZA gives better information for park management and revitalization, since it considers the potential size of woody plants, while rIISA, considering the actual size of the vegetation, provides more relevant information for pollen-allergy sufferers. Based on rIISA, the allergenic potential was highest in May for the Grassalkovich Garden (formal baroque garden) and Janko Kráľ Park (English landscape park) and in April for the Medic Garden (repurposed baroque garden). We also found differences in the duration of the period of increased allergenic potential in these parks, ranging from 1 to 3 months. Based on the total annual sums of rIISA, we found the highest allergenic potential in the Medic Garden and lowest in the Janko Kráľ Park. This variance is caused mainly by the different density of trees and percentage of allergenic species. The biggest contributors to the allergenic potential were Platanus, Acer and Tilia. Based on the information on temporal variation of the allergenic potential during the vegetation period provided by the running indices, it is possible to improve the planning of park revitalization based on the flowering period of allergenic species and provide better information to the pollen-allergy sufferers for minimizing the allergenic effect of urban green areas on their health during a particular month.

Characterization of subsurface pathways contributing to freshwater salinization of urban streams using electrical and electromagnetic imaging techniques

Salinization of inland fresh surface waters in temperate climates is a growing concern due to increasing salt inputs from sources including chloride (Cl)-containing road salt de-icers, industrial waste, and landfill leachate. Groundwater pathways play an important role in the year-round delivery of Cl to streams, but quantifying this pathway, including spatiotemporal variability and amount of Cl mass stored in the subsurface, is challenging. The objective of this study was to demonstrate, evaluate, and compare the potential applications of the geoelectrical techniques - electromagnetics (EM) and direct current (DC) resistivity - for mapping salt contamination in shallow urban groundwater and characterizing the groundwater pathways delivering Cl to urban streams. EM and DC surveys were conducted (3D mapping and 2D time-lapse) across a 20 m salt-impacted stream section and surrounding riparian zone that is located near an arterial road and parking lot. Groundwater samples and soil cores were also collected to validate the geoelectrical results. Both the EM and DC surveys detected high salt concentrations in the shallow subsurface (up to 3 m depth) near the road, parking lot, and stream; however, DC more accurately represented groundwater Cl concentrations. DC results were used to calculate the total Cl mass in the subsurface, with the spatial mass distribution used to infer the temporal variability in the subsurface salt plume. Finally, time-lapse DC showed that the highest groundwater salt concentrations existed near the stream between June and October - this is expected to contribute to the elevated salt concentrations in the stream during summer months. This study has shown that EM and DC can be useful for identifying groundwater salt concentration, storage, and transport in a non-intrusive and efficient manner, making them valuable field tools for characterizing and quantifying groundwater salt pathways to urban streams.

Geospatial patterns and geochemical compositional characteristics of molybdenum in different mediums of an urban environment

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.

Intraspecific variations of leaf hydraulic, economic, and anatomical traits in Cinnamomum camphora along an urban-rural gradient

Urbanization brings numerous benefits to residents, but it also introduces complex, variable, and heterogeneous habitat conditions to urban plants, resulting in an arid and hot urban environment that decreases tree growth and the ecological service capacity of trees. In this study, we evaluated leaf hydraulic, economic, and anatomical traits and their covariations of Cinnamomum camphora along an urban-rural gradient in Hefei, Eastern China. We found that Cinnamomum camphora in urban adopted a conservative hydraulic strategy with low leaf turgor loss point (Tlp), leaf hydraulic conductance (Kleaf), and leaf water potential resulting in 50 % loss of hydraulic conductance (P50), as well as a quick investment-return economic strategy with low unit leaf dry matter content (LMA) and high leaf nitrogen content (Leaf N). P50, Kleaf and LMA were significantly positively correlated with the urban-rural gradient (PC1urban-rural gradient), while Leaf N exhibited a negative correlation with it. The results showed a trade-off between intraspecific safety and efficiency in leaf hydraulic traits along the urban-rural gradient and an intraspecific coordinated variation in leaf hydraulic and economic traits. In addition, based on the analysis of a trait coordination network, it was revealed that leaf mesophyll and stomata were key structures for trait adjustment and coordination. Furthermore, our findings offer a significant theoretical underpinning for the effective management of landscape trees and the strategic planning of urban tree species.

Social participation in the city: exploring the moderating effect of walkability on the associations between active mobility, neighborhood perceptions, and social activities in urban adults

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.

Urban surface classification using semi-supervised domain adaptive deep learning models and its application in urban environment studies

High-resolution urban surface information, e.g., the fraction of impervious/pervious surface, is pivotal in studies of local thermal/wind environments and air pollution. In this study, we introduced and validated a domain adaptive land cover classification model, to automatically classify Google Earth images into pixel-based land cover maps. By combining domain adaptation (DA) and semi-supervised learning (SSL) techniques, our model demonstrates its effectiveness even when trained with a limited dataset derived from Gaofen2 (GF2) satellite images. The model's overall accuracy on the translated GF2 dataset improved significantly from 19.5% to 75.2%, and on the Google Earth image dataset from 23.1% to 61.5%. The overall accuracy is 2.9% and 3.4% higher than when using only DA. Furthermore, with this model, we derived land cover maps and investigated the impact of land surface composition on the local meteorological parameters and air pollutant concentrations in the three most developed urban agglomerations in China, i.e., Beijing, Shanghai and the Great Bay Area (GBA). Our correlation analysis reveals that air temperature exhibits a strong positive correlation with neighboring artificial impervious surfaces, with Pearson correlation coefficients higher than 0.6 in all areas except during the spring in the GBA. However, the correlation between air pollutants and land surface composition is notably weaker and more variable. The primary contribution of this paper is to provide an efficient method for urban land cover extraction which will be of great value for assessing the urban surface composition, quantifying the impact of land use/land cover, and facilitating the development of informed policies.

Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe

This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017-2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00-8:00 UTC) and late evening (19:00-22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.

Horneros consider their neighbors as precious foes regardless of territory size and human disturbance

Research on neighbor-stranger discrimination theory has revealed the significance of social context and biological traits affecting the mechanisms that drive social discrimination, such as the dear enemy or nasty neighbor effects (strangers or neighbors more threatening, respectively). Nevertheless, the effects of territory size and human activity on neighbor-stranger experiments have yet to be explored. By examining behavioral responses to spontaneous duets of neighbors and playbacks of strangers' duets, we tested whether rufous horneros (Furnarius rufus) in smaller territories show heightened aggression, responding more strongly to strangers and less to neighbors than those in larger territories. This could be expected because birds in larger territories might struggle to differentiate competitors due to limited interactions, hindering familiarity with neighbors. Meanwhile, birds in smaller territories are likely to treat neighbors as dear enemies due to the need to minimize territorial costs caused by presumed frequent intrusions or to protect limited resources. Contrary to predictions, rufous horneros responded more strongly to strangers than neighbors, regardless of owner territory sizes. This suggests that the presumed higher intruder frequency in smaller territories does not necessarily lead to adjusted dear enemy relationships. Yet, small territory holders exhibited heightened vocal responses to duets of unfamiliar intruders, indicating a stronger 'dear enemy' effect compared to birds with larger territories. We also tested whether dear enemy relationships would be heightened during weekends. This is linked to the difficulty urban birds might face in distinguishing neighbors from strangers during high human activity days (i.e., on weekdays), due to factors like noise masking intruder acoustic cues and heightened vigilance. Territorial owners exhibited consistent dear enemy behavior towards neighbors, regardless of our proxy for human activity. This underscores their ability in identifying competitor identities within urban settings.

Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning

Cities in the developing world are expanding rapidly, and undergoing changes to their roads, buildings, vegetation, and other land use characteristics. Timely data are needed to ensure that urban change enhances health, wellbeing and sustainability. We present and evaluate a novel unsupervised deep clustering method to classify and characterise the complex and multidimensional built and natural environments of cities into interpretable clusters using high-resolution satellite images. We applied our approach to a high-resolution (0.3 m/pixel) satellite image of Accra, Ghana, one of the fastest growing cities in sub-Saharan Africa, and contextualised the results with demographic and environmental data that were not used for clustering. We show that clusters obtained solely from images capture distinct interpretable phenotypes of the urban natural (vegetation and water) and built (building count, size, density, and orientation; length and arrangement of roads) environment, and population, either as a unique defining characteristic (e.g., bodies of water or dense vegetation) or in combination (e.g., buildings surrounded by vegetation or sparsely populated areas intermixed with roads). Clusters that were based on a single defining characteristic were robust to the spatial scale of analysis and the choice of cluster number, whereas those based on a combination of characteristics changed based on scale and number of clusters. The results demonstrate that satellite data and unsupervised deep learning provide a cost-effective, interpretable and scalable approach for real-time tracking of sustainable urban development, especially where traditional environmental and demographic data are limited and infrequent.

Visual design of green information in urban environment based on global similarity calculation and multi-dimensional visualization technology

In recent years, the escalating prevalence of elevated consumption and carbon emissions within urban operations has reached a disconcerting extent. This surge in resource depletion and environmental pollution exerts an adverse influence on the well-being of individuals, while impeding societal progress and hindering the enhancement of overall quality of life. Within the domain of urban environmental design, the integration of visual displays emerges as a superior approach to facilitate the assimilation and analysis of green and low-carbon information. However, urban environmental data usually contains multiple dimensions, so it is a problem to realize the data representation of multiple dimensions while maintaining the correlation and interactivity between data. To surmount the challenge of visualizing such intricate information, this investigation initially employs a sophisticated memory-based clustering algorithm for information extraction, accompanied by a global similarity algorithm that meticulously computes attribute component quantities within specific dimensions of the vector. Furthermore, leveraging the inherent power of Vue's bidirectional data binding capabilities, the study adopts the esteemed MVVM (Model-View-View-Model) pattern, fostering seamless two-way interaction through the established logical relationship. As a result, the amalgamation of multidimensional visualization technology empowers comprehensive data mining through a captivating visual augmentation. Concurrently, the application of data visualization dimension control delivers tailored displays tailored to green and low-carbon scenarios within urban environmental design. Experimental results impeccably validate the effectiveness of the proposed algorithm, substantiated by a mere 1.77% false alarm rate for data stream difference detection and a clustering difference of 1.34%. The aforementioned algorithm accentuates the efficacy of visual displays, thus engendering a profound synergy between the industrial and supply chains. Moreover, it facilitates the design, production, and utilization of environmentally friendly products and energy sources. This, in turn, serves as a catalyst, propelling the widescale adoption of green and low-carbon practices throughout the entire industrial chain, fueled by the seamless integration of multimedia data.

Inside and outside the neighborhood: Short-term and long-term subjective well-being by geographical context

The value of linking urban environment and subjective well-being (SWB) is now well recognized. But whether the geographical context inside and outside the neighborhood has differential influence on long- and short-term SWB remains unclear. Based on the activity perspective, we used survey data from Guangzhou, China, integrating GPS data, portable environmental sensors data to analyze time-weighted and real-time geographical context inside and outside the neighborhood on long- and short-term SWB. The results show that SWB is not only influenced by the neighborhood environment, but also the geographical context outside the neighborhood. Time-weighted geographical environment inside the neighborhood has a higher impact and explanatory ability on long-term SWB, while real-time geographical environment outside the neighborhood has a higher impact and explanatory ability on short-term SWB. This study provides a new understanding for geographies of SWB through the extension of time and space, and also provides reference for more refined urban planning and governance in the future.

Micro urban spaces and mental well-being: Measuring the exposure to urban landscapes along daily mobility paths and their effects on momentary depressive symptomatology among older population

The urban environment plays an important role for the mental health of residents. Researchers mainly focus on residential neighbourhoods as exposure context, leaving aside the effects of non-residential environments. In order to consider the daily experience of urban spaces, a people-based approach focused on mobility paths is needed. Applying this approach, (1) this study investigated whether individuals' momentary mental well-being is related to the exposure to micro-urban spaces along the daily mobility paths within the two previous hours; (2) it explored whether these associations differ when environmental exposures are defined considering all location points or only outdoor location points; and (3) it examined the associations between the types of activity and mobility and momentary depressive symptomatology. Using a geographically-explicit ecological momentary assessment approach (GEMA), momentary depressive symptomatology of 216 older adults living in the Ile-de-France region was assessed using smartphone surveys, while participants were tracked with a GPS receiver and an accelerometer for seven days. Exposure to multiple elements of the streetscape was computed within a street network buffer of 25 m of each GPS point over the two hours prior to the questionnaire. Mobility and activity type were documented from a GPS-based mobility survey. We estimated Bayesian generalized mixed effect models with random effects at the individual and day levels and took into account time autocorrelation. We also estimated fixed effects. A better momentary mental wellbeing was observed when residents performed leisure activities or were involved in active mobility and when they were exposed to walkable areas (pedestrian dedicated paths, open spaces, parks and green areas), water elements, and commerce, leisure and cultural attractors over the previous two hours. These relationships were stronger when exposures were defined based only on outdoor location points rather than all location points, and when we considered within-individual differences compared to between-individual differences.

Association of service facilities and amenities with adolescent birth rates in Mexican cities

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.

Is there a relationship between socioeconomic level, vegetation cover, free-roaming cats and dogs, and the diversity of native birds? A study in a Latin American capital city

Understanding how social and environmental factors influence biodiversity can contribute to sustainable development and promote environmental justice in cities. This knowledge is especially important in developing countries with strong social and environmental inequalities. This study investigates native bird diversity in relation to the socioeconomic level of neighborhoods, their plant cover, and the abundance of free-roaming cats and dogs in a Latin American city. Two causal hypotheses were tested: 1) socioeconomic level (defined by education and income) influence native bird diversity indirectly, as an effect mediated by plant cover, as well as directly; 2) in addition socioeconomic conditions also influence free-roaming cats and dogs which could affect native bird diversity. To test these hypotheses, data were collected at 120 sites located in neighborhoods of different socioeconomic levels across the city of Santiago de Chile and fit to Structural Equation Models. Evidence supported the second hypothesis: in wealthier neighborhoods there was greater plant cover that, in turn, positively influenced native bird diversity; in addition, fewer free-roaming cats and dogs were found in these neighborhoods but they had no effect on native bird diversity. Results suggest that increasing plant cover, especially in more socioeconomically vulnerable neighborhoods, would contribute to urban environmental justice and more equitable opportunities to access native bird diversity.

High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures

Air pollution and poor air quality is impacting human health globally and is a major cause of respiratory and cardiovascular disease and damage to human organ systems. Automated air quality monitoring stations continuously record airborne pollutant concentrations, but are restricted in number, costly to maintain and cannot document all spatial variability of airborne pollutants. Biomonitors, such as lichens, are commonly used as an inexpensive alternative to assess the degree of pollution and monitor air quality. However, only a few studies combined lichen carbon, nitrogen and sulfur contents, with their stable-isotope-ratio signatures (δ¹³C, δ¹⁵N and δ³⁴S values) to assess spatial variability of air quality and to 'fingerprint' potential pollution sources. In this study, a high-spatial resolution lichen biomonitoring approach (using Xanthoria parietina and Physcia spp.) was applied to the City of Manchester (UK), the centre of the urban conurbation Greater Manchester, including considerations of its urban characteristics (e.g., building heights and traffic statistics), to investigate finer spatial detail urban air quality. Lichen wt% N and δ¹⁵N signatures, combined with lichen nitrate (NO₃^-) and ammonium (NH₄⁺) concentrations, suggest a complex mixture of airborne NO_x and NH_x compounds across Manchester. In contrast, lichen S wt%, combined with δ³⁴S strongly suggest anthropogenic sulfur sources, whereas C wt% and δ¹³C signatures were not considered reliable indicators of atmospheric carbon emissions. Manchester's urban attributes were found to influence lichen pollutant loadings, suggesting deteriorated air quality in proximity to highly trafficked roads and densely built-up areas. Lichen elemental contents and stable-isotope-ratio signatures can be used to identify areas of poor air quality, particularly at locations not covered by automated air quality measurement stations. Therefore, lichen biomonitoring approaches provide a beneficial method to supplement automated monitoring stations and also to assess finer spatial variability of urban air quality.

Shedding light on the effects of LED streetlamps on trees in urban areas: Friends or foes?

Streetlamp illumination disturbs the natural physiological processes and circadian rhythms of living organisms, including photosynthesizing "citizens". The light-emitting diode (LED) technology has replaced high-pressure sodium lamps. Therefore, the effects of LED streetlamps on urban trees need to be elucidated as these new lamps have a different light spectrum (with a peak in the blue and red regions of the spectrum, i.e., highly efficient wavebands for photosynthesis) compared to older technologies. To address the above-mentioned issue, two widely utilised tree species in the urban environment, including Platanus × acerifolia (P) and Tilia platyphyllos (T), were grown with or without the effect of LED streetlamps using two realistic illumination intensities (300 and 700 μmol m^-2 s^-1). Gas exchanges and biochemical features (starch, soluble sugar, and chlorophyll content) of illuminated vs non-illuminated trees were compared during the whole vegetative season. Our results showed that both tree species were strongly influenced by LED streetlamps at physiological and biochemical levels. Specifically, the mature leaves of P and T streetlamp-illuminated trees had a lower CO₂ assimilation rate at dawn and had higher chlorophyll content, with lower starch content than controls. Our results showed that the differences between the effects of the two selected light intensities on the physiochemical attributes of P and T trees were not statistically significant, suggesting the absence of a dose-dependent effect. The most significant difference between T and P trees concerning the LED-triggered species-specific effect was that the delay in winter dormancy occurred only in P individuals. This study provided insights into the extent of LED streetlamp disturbance on trees. Our findings might raise awareness of the necessity to provide less impacting solutions to improve the wellness of trees in the urban environment.

Contamination levels and source apportionment of potentially toxic elements in size-fractionated road dust of Moscow

The distributions of potentially toxic elements (PTEs) among PM₁, PM_1-10, PM_10-50, and PM_50-1000 fractions of the road dust were studied in the western and eastern parts of Moscow, impacted mainly by the road transport and the industrial sector, respectively. The partitioning of PTEs in road dust can provide more precise information on pollution sources and its further interpretation regarding human health risks. The concentrations of PTEs were analyzed by mass and atomic emission inductively coupled plasma spectrometry. Differences in the results between the western and eastern parts of the city were caused by the dissimilarity between traffic and industrial emissions. The source apportionment of the PTEs was carried out using absolute principal component analysis with multiple linear regressions (PCA/APCS-MLR). The contribution from anthropogenic sources was significant to PM₁ and PM_1-10 particles. In coarser fractions (PM_10-50, PM_50-1000), it decreased due to the input with the wind-induced resuspension of soil and rock particles. In the eastern part of the city, the accumulation of PTEs (especially Mo, Sb, Cd, Sn, Bi, Co, and As) is the most active in PM_1-10, while in the western part, it is most pronounced in PM₁ (especially Pb, Cu, Cr, and W) which is associated with differences in the size of particles coming from traffic and industrial sources. In the eastern part of Moscow, in comparison with the western part, the contribution from industrial sources to the accumulation of PTEs in all particle size fractions was higher by 10-30%. In the western part of Moscow, the finest particles PM₁ and PM_1-10 demonstrate the trend of rising pollution levels with the increase in road size, while in the eastern part of the city, only coarse particles PM_50-1000 show the same trend. In the fractions PM₁ and PM_1-10 of road dust, a significant contribution was made by anthropogenic sources; however, its role decreased in the coarse fractions-PM_10-50 and especially in PM_50-1000- due to the influence of roadside soils and their parent material.

Mental health and air temperature: Attributable risk analysis for schizophrenia hospital admissions in arid urban climates

Health researchers have examined the physiological impacts of extreme air temperature on the human body. Yet, the mental health impacts of temperature have been understudied. Research has shown that the environment can create circumstances that exacerbate mental health issues. This may be particularly challenging for some of the fastest growing cities, located in hot, dry climates. Given the theoretical relationship between air temperature and mental health, we seek to measure the association between temperature and schizophrenia hospital admissions in an arid urban climate and quantify the associated public health burden. We collected 86,672 hospitalization records for schizophrenia from 2006 to 2014 in Maricopa County, Arizona, USA. Using a distributed lag non-linear model (DLNM), we tested for a statistical association between temperature and schizophrenia hospital admissions after controlling for year, season, weekends, and holidays. We calculated the cumulative attributable risk of nighttime temperature on schizophrenia for the entire dataset as well as among demographic subgroups. The relative risk of schizophrenia hospital admissions increased with both high and low temperatures. Statistical models using daily minimum temperature were more strongly associated with hospitalization than those using mean or maximum. Schizophrenia hospital admissions increased on days with minimum temperatures above 30 °C and below 3 °C, with some subgroups experiencing higher rates of hospitalization. The total fraction of schizophrenia hospital admissions attributable to non-optimal minimum temperature is 3.45 % (CI: -4.91-10.80 %) and high minimum temperature is 0.28 % (CI: -1.18-1.78 %). We found that non-whites and males appear to be at a slightly increased risk than the general population, although there did not appear to be a statistically significant difference. A conservative estimate of healthcare costs annually from non-optimal temperature attributed schizophrenia hospitalization is $1.95 million USD. Therefore, nighttime cooling strategies and efforts could increase the accessibility of shelters to reduce overnight exposure to extreme air temperature.

Smaller is better? Unduly nice accuracy assessments in roof detection using remote sensing data with machine learning and k-fold cross-validation

Deriving the thematic accuracy of models is a fundamental part of image classification analyses. K-fold cross-validation (KCV), as an accuracy assessment technique, can be biased because existing built-in algorithms of software solutions do not handle the high autocorrelation of remotely sensed images, leading to overestimation of accuracies. We aimed to quantify the magnitude of the overestimation of KCV-based accuracies and propose a method to overcome this problem with the example of rooftops using a WorldView-2 (WV2) satellite image, and two orthophotos. Random split to training/testing subsets, independent testing and different types of repeated KCV sampling strategies were used to generate input datasets for classification. Results revealed that applying the random splitting of reference data to training/testing subsets and KCV methods had significantly biased the accuracies by up to 17%; overall accuracies (OAs) can incorrectly reach >99%. We found that repeated KCV can provide similar results to independent testing when spatial sampling is applied with a sufficiently large distance threshold (in our case 10 m). Coarser resolution of WV2 ensured more reliable results (up to a 5-9% increase in OA) than orthophotos. Object-based pixel purity of buildings showed that when using a majority filter for at least of 50% of objects the final accuracy approached 100% with each sampling method. The final conclusion is that KCV-based modelling ensures better accuracy than single models (with better pixel purity on the object level), but the accuracy metrics without spatially filtered sampling are not reliable.

Identification and characteristic analysis of urban vegetation spectra under different dust deposition

Urban atmospheric environmental problems have raised increasing attention in recent years. To confirm the impact of plant dust deposition capacity on urban atmosphere and spectral characteristics, this study carried out experiments in Xuhui District and Minhang District of Shanghai, and 4 common greening species were selected as research objects. In order to explore the changes in vegetation spectral characteristics, ASD FieldSpec 3 Spectrometer and 1/10000 electronic balance were used to measure the spectral data and dust data of samples. The results show as follows: (1) 380-680 nm and 750-1350 nm are the best spectral wavelengths to analyze the influence of dust deposition on spectrum. (2) The canopy reflectance spectra of tree species decrease with the increase of dust deposition, especially in the wavelength range of 750-1350 nm. (3) The first derivative and the second derivative are beneficial to observe the spectral changes and judge the position of the red edge. The red edge position of some tree species is easy to move under the interference of dust deposition. (4) Among the four tree species, the spectrum of Osmanthus fragrans is relatively undisturbed by dust deposition, and Osmanthus fragrans is a great tree species for urban greening. The research made a foundation for the future use of spectral information to estimate vegetation dust.

Phenomenology of ultrafine particle concentrations and size distribution across urban Europe

The 2017-2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN_10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN_10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN_25-800, was positively correlated with BC, NO₂, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.

Mining association rules between lichens and air quality to support urban air quality monitoring in Nigeria

Urban environments represent the most intense human-environment interaction. This interaction can result in negative outcomes like air pollution and its health implications. There is a significant data deficit in air quality monitoring across many developing nations, which prevents effective policies and measures from being taken to promote the accomplishment of sustainable development. Around the world, lichens have been used to track environmental changes due to their sensitivity to changes and concentration of atmospheric pollutants. This study investigated the relationships between lichen and air quality across some Nigerian cities. Lichen surveys were conducted in four cities. At various periods during the day, NO₂, SO₂, PM_2.5, and PM₁₀ levels were measured. Association rule mining was carried out to investigate the relationship between lichen found and air quality categories. Results showed that the most prevalent lichen Genera are Pyxine in Abuja and Kano, Diorygma in Lagos, and Dirinaria in Port Harcourt. Out of the 40 rules found from the rule mining, 17 are important (lift values ≥ 1.1), capturing six of the fourteen lichen genera identified in the field. The findings indicated that there are important relationships between lichens and air quality indices, suggesting that some lichen species in Nigeria may serve as indicators of long-term air quality. To develop a network of urban environmental quality bioindicators across Nigerian cities, surveying and transplanting are advised. The use of lichen for air quality monitoring can provide information for sustainable management of air quality and environmental quality in Nigeria.

Impacts of COVID-19 on bike-sharing usages in Seoul, South Korea

The COVID-19 pandemic and social distancing restrictions have had a significant impact on urban mobility. As micro mobility offers less contact with other people, docked or dockless e-scooters and bike-sharing have emerged as alternative urban mobility solutions. However, little empirical research has been conducted to investigate how COVID-19 might affect micro mobility usage, especially in a major Asian city. This research aims to study how COVID-19 and other related factors have affected bike-sharing ridership in Seoul, South Korea. Using detailed urban telecommunication data, this study explored the spatial-temporal patterns of a docked bike-sharing system in Seoul. Stepwise negative binomial panel regressions were conducted to find out how COVID-19 and various built environments might affect bike-sharing ridership in the city. Our results showed that open space areas and green infrastructure had statistically significant positive impacts on bike-sharing usage. Compared to registered population factors, real-time telecommunication floating population had a significant positive relationship with both bike trip count and trip duration. The model showed that telecommunication floating population has a significant positive impact on bike-sharing trip counts and trip duration. These findings could offer useful guidelines for emerging shared mobility planning during and after the COVID-19 pandemic.

Urban environment and physical activity and capacity in patients with chronic obstructive pulmonary disease

BACKGROUND

Physical activity and exercise capacity are key prognostic factors in chronic obstructive pulmonary disease (COPD) but their environmental determinants are unknown.

OBJECTIVES

To test the association between urban environment and objective physical activity, physical activity experience and exercise capacity in COPD.

METHODS

We studied 404 patients with mild-to-very severe COPD from a multi-city study in Catalonia, Spain. We measured objective physical activity (step count and sedentary time) by the Dynaport MoveMonitor, physical activity experience (difficulty with physical activity) by the Clinical visit-PROactive (C-PPAC) instrument, and exercise capacity by the 6-min walk distance (6MWD). We estimated individually (geocoded to the residential address) population density, pedestrian street length, slope of terrain, and long-term (i.e., annual) exposure to road traffic noise, nitrogen dioxide (NO₂) and particulate matter (PM_2.5). We built single- and multi-exposure mixed-effects linear regressions with a random intercept for city, adjusting for confounders.

RESULTS

Patients were 85% male, had mean (SD) age 69 (9) years and walked 7524 (4045) steps/day. In multi-exposure models, higher population density was associated with fewer steps, more sedentary time and worse exercise capacity (-507 [95% CI: 1135, 121] steps, +0.2 [0.0, 0.4] h/day and -13 [-25, 0] m per IQR). Pedestrian street length related with more steps and less sedentary time (156 [9, 304] steps and -0.1 [-0.1, 0.0] h/day per IQR). Steeper slope was associated with better exercise capacity (15 [3, 27] m per IQR). Higher NO₂ levels related with more sedentary time and more difficulty in physical activity. PM_2.5 and noise were not associated with physical activity or exercise capacity.

DISCUSSION

Population density, pedestrian street length, slope and NO₂ exposure relate to physical activity and capacity of COPD patients living in highly populated areas. These findings support the consideration of neighbourhood environmental factors during COPD management and the attention to patients with chronic diseases when developing urban and transport planning policies.

Use of geospatial tools to predict the risk of contamination by SARS-CoV-2 in urban cemeteries

Urban cemeteries are increasingly surrounded by areas of high residential density as urbanization continues world-wide. With increasing rates of mortality caused by the novel coronavirus, SARS-CoV-2, urban vertical cemeteries are experiencing interments at an unprecedented rate. Corpses interred in the 3rd to 5th layer of vertical urban cemeteries have the potential to contaminate large adjacent regions. The general objective of this manuscript is to analyze the reflectance of altimetry, normalized difference vegetation index (NDVI) and land surface temperature (LST) in the urban cemeteries and neighbouring areas of the City of Passo Fundo, Rio Grande do Sul, Brazil. It is assumed that the population residing in the vicinity of these cemeteries may be exposed to SARS-CoV-2 contamination through the displacement of microparticles carried by the wind as a corpse is placed in the burial niche or during the first several days of subsequent fluid and gas release through the process of decomposition. The reflectance analyses were performed utilizing Landsat 8 satellite images applied to altimetry, NDVI and LST, for hypothetical examination of possible displacement, transport and subsequent deposition of the SARS-CoV-2 virus. The results showed that two cemeteries within the city, cemeteries A and B could potentially transport SARS-CoV-2 of nanometric structure to neighboring residential areas through wind action. These two cemeteries are located at high relative altitudes in more densely populated regions of the city. The NDVI, which has been shown to control the proliferation of contaminants, proved to be insufficient in these areas, contributing to high LST values. Based on the results of this study, the formation and implementation of public policies that monitor urban cemeteries is suggested in areas that utilize vertical urban cemeteries in order to reduce the further spread of the SARS-CoV-2 virus.

Air pollution and green spaces in relation to breast cancer risk among pre and postmenopausal women: A mega cohort from Catalonia

BACKGROUND

The association between air pollution and green spaces with breast cancer risk stratified by menopausal status has not been frequently investigated despite its importance given the different impact of risk factors on breast cancer risk depending on menopausal status.

OBJECTIVES

To study the association between air pollution, green spaces and pre and postmenopausal breast cancer risk.

METHODS

We conducted a population-based cohort study using electronic primary care records in Catalonia. We included women aged 17-85 years free of cancer at study entry between 2009 and 2017. Our exposures were particulate matter <2.5 μm (PM_2.5) & <10 μm (PM₁₀), nitrogen dioxide (NO₂), normalized difference vegetation index (NDVI), and percentage of green spaces estimated at the census tract level. Breast cancer was identified with ICD-10 code C50. We estimated cause-specific hazard ratios (HR) for the relationship between each individual exposure and pre and postmenopausal breast cancer risk, using linear and non-linear models.

RESULTS

Of the 1,054,180 pre and 744,658 postmenopausal women followed for a median of 10 years, 6,126 and 17,858 developed breast cancer, respectively. Among premenopausal women, only very high levels of PM₁₀ (≥46 μg/m³) were associated with increased cancer risk (compared to lower levels) in non-linear models. Among postmenopausal women, an interquartile range increase in PM_2.5 (HR:1.03; 95%CI:1.01-1.04), PM₁₀ (1.03; 1.01-1.05), and NO₂ (1.05; 1.02-1.08) were associated with higher cancer risk. NDVI was negatively associated with decreased cancer risk only among postmenopausal women who did not change residence during follow-up (0.84; 0.71-0.99) or who were followed for at least three years (0.82; 0.69-0.98).

DISCUSSION

Living in areas with high concentrations of PM_2.5, PM₁₀, and NO₂ increases breast cancer risk in postmenopausal women while long-term exposure to green spaces may decrease this risk. Only very high concentrations of PM₁₀ increase breast cancer risk in premenopausal women.

Biochar as a soil amendment in the tree establishment phase: What are the consequences for tree physiology, soil quality and carbon sequestration?

Trees play a pivotal role in the urban environment alleviating the negative impacts of urbanization, and for this reason, local governments have promoted strongly tree planting policies. However, poor soil quality and neglect tree maintenance (e.g., irrigation and fertilization) can seriously mine the plant health status during the tree establishment phase. The use of biochar to provide long-lasting C to the soil and, at the same time, improving soil properties (e.g., improved water holding capacity), soil enzymes activities and NPK concentrations, is a promising research field. Therefore, with a two-step experiment, the study aimed to assay the physiological responses of a commonly used urban tree species (Tilia × europaea L.) to 1.5 % (w/w) biochar amendment (B), and secondly, to assess the ability of trees, grown in biochar amended soil, to tolerate a period of drought. Biochar amendment increased P and K availability in the soil, resulting in higher P and K concentrations in B than control leaves, according to the leaf stage. This induced B trees, higher values in both total biomass than controls (+22 %) in well-watered plants. Moreover, the higher water availability in soil amended with biochar helped B trees to tolerate water stress, with better leaf photosynthetic performances and a faster recovery than stressed controls after the re-watering. This study highlights the dual function of the biochar, improving CO₂ sequestration and soil properties, and at the same time, enhancing plant physiological responses to environmental constraints. The use of biochar at the tree planting, especially in an urban environment, is a feasible and environmentally sustainable strategy to improve the success during the tree establishment phase.

Delineation of urban expansion influences urban heat islands and natural environment using remote sensing and GIS-based in industrial area

Land transformation monitoring is essential for controlling the anthropogenic activities that could cause the degradation of natural environment. This study investigated the urban heat island (UHI) effect at the Asansol and Kulti blocks of Paschim Bardhaman district, India. The increasing land surface temperature (LST) can cause the UHI effect and affect the environmental conditions in the urban area. The vulnerability of the UHI effect was measured quantitatively and qualitatively by using the urban thermal field variation index (UTFVI). The land use and land cover (LULC) dynamics are identified by utilizing the remote sensing and maximum likelihood supervised classification techniques for the years 1990, 2000, 2010, and 2020, respectively. The results indicated a decrease around 19.05 km², 15.47 km², and 9.86 km² for vegetation, agricultural land, and grassland, respectively. Meanwhile, there is an increase of 35.69 km² of the built-up area from the year 1990 to 2020. The highest LST has increased by 11.55 °C, while the lowest LST increased by 8.35 °C from 1990 to 2020. The correlation analyses showed negative relationship between LST and vegetation index, while positive correlation was observed for built-up index. Hotspot maps have identified the spatio-temporal thermal variations in Mohanpur, Lohat, Ramnagar, Madhabpur, and Hansdiha where these cities are mostly affected by the urban expansion and industrialization developments. This study will be helpful to urban planners, stakeholders, and administrators for monitoring the anthropological activities and thus ensuring a sustainable urban development.

Assessing myocardial infarction severity from the urban environment perspective in Wuhan, China

Health inequalities are globally widespread due to the regional socioeconomic inequalities. Myocardial infarction (MI) is a leading health problem causing deaths worldwide. Yet medical services for it are often inequitably distributed by region. Moreover, studies concerning MI's potential spatial risk factors generally suffer from difficulties in focusing on too few factors, inappropriate models, and coarse spatial grain of data. To address these issues, this paper integrates registered 1098 MI cases and urban multi-source spatio-temporal big data, and spatially analyses the risk factors for MI severity by applying an advanced interpretable model, the random forest algorithm (RFA)-based SHapley Additive exPlanations (SHAP) model. In addition, a community-scale model between spatio-temporal risk factors and MI cases is constructed to predict the MI severity of all communities in Wuhan, China. The results suggest that those risk factors (i.e., age of patients, medical quality, temperature changes, air pollution and urban habitat) affect the MI severity at the community scale. We found that Wuhan residents in the downtown area are at risk for high MI severity, and the surrounding suburb areas show a donut-shape pattern of risk for medium-to-high MI severity. These patterns draw our attention to the impact of spatial environmental risk factors on MI severity. Thus, this paper provides three recommendations for urban planning to reduce the risk and mortality from severe MI in the aspect of policy implication.

Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic

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.

Urbanization hampers biological control of insect pests: A global meta-analysis

Biological control is a major ecosystem service provided by pest natural enemies, even in densely populated areas where the use of pesticides poses severe risks to human and environmental health. However, the impact of urbanization on this service and the abundance patterns of relevant functional groups of arthropods (herbivores, predators, and parasitoids) remain contested. Here, we synthesize current evidence through three hierarchical meta-analyses and show that advancing urbanization leads to outbreaks of sap-feeding insects, declining numbers of predators with low dispersal abilities, and weakened overall biological pest control delivered by arthropods. Our results suggest that sedentary predators may have the potential to effectively regulate sap-feeders, that are one of the most important pests in urban environments. A well-connected network of structurally diverse and rich green spaces with less intensive management practices is needed to promote natural plant protection in urban landscapes and sustainable cities.

Multiple pathways and mediation effects of built environment on kidney disease rate via mitigation of atmospheric threats

Air pollution and high temperatures can increase kidney disease rate, especially under climate change. A well-designed urban environment has mediating effects on atmospheric environmental threats and promoting human health, but previous studies have overlooked these effects. This study used partial least squares modeling and urban-scale data from Taiwan to identify the crucial effects (i.e., direct, indirect, and total effects) and pathways of urban form (i.e., urban development intensity, land-use mix, and urban sprawl), urban greening (i.e., green coverage), urban industrial status (e.g., industrial level), atmospheric environment (i.e., high temperature and air pollution), and socioeconomic status (i.e., elderly ratio, medical resources, and economic status) on kidney disease rate. Maximizing land-use mix and green coverage and minimizing urban development intensity, urban sprawl, and industrial levels could help reduce kidney disease rate. Air pollution and high temperature had a mediation effect of built environment on kidney disease rate; with the mediation effect of air pollution was greater than that of high temperature. Furthermore, air pollution, high temperature, and elderly ratio increased kidney disease rate, whereas medical resources decreased kidney disease rate. This study is the first to consider the impact (i.e., direct, indirect, and total effects) and pathways of built environment characteristics on kidney disease rate. The findings revealed that an appropriate urban policy might be a practical strategy and lower kidney disease rate for a healthy city development. Moreover, this study provides a new approach for clarifying complex relationships and identifying crucial factors.

Inputs and sources of Pb and other metals in urban area in the post leaded gasoline era

The contamination status of heavy metals in urban environment changes frequently with the industrial structure adjustment, energy conservation and emission reduction and thus requires timely investigation. Based on enrichment factor, multivariate statistical analysis and isotope fingerprinting, we assessed comprehensively the inputs and sources of heavy metals in different samples from an urban area that was less impacted by leaded gasoline exhaust. The road dust contained relatively high levels of Cr, Pb and Zn (with enrichment factor >2) that originated from both exhaust and non-exhaust traffic emissions, while the moss plants could accumulate high levels of Pb and Zn from the deposition of traffic exhaust emission. This suggest that the traffic emission is still an important source of metals in the urban area although gasoline is currently lead free. On the contrary, the occurrences of metals in the urban soils were controlled by natural sources and non-traffic anthropogenic emission. These findings revealed that different samples would receive different inputs of metals from different sources in the urban area, and the responsiveness and sensitiveness of these urban samples to metal inputs can be ranked as moss ≥ dust > soil. Taken together, our results suggested that in order to avoid generalizing and get detail source information, multi-samples and multi-measures must be adopted in the assessment of integrated urban environmental quality.

Community assembly of microbial habitat generalists and specialists in urban aquatic ecosystems explained more by habitat type than pollution gradient

Urban freshwater ecosystems have important ecosystem functions, provide habitats for diverse microbial communities and are susceptible to multiple interconnected factors such as environmental pollution. Despite the ecological significance of bacteria and microeukaryotes, little is known about how their community assembly responds to various environmental factors across water and sediment habitats and ecological processes shaping them. Here, environmental DNA-based approaches were used to investigate the community assembly processes of bacteria and microeukaryotes (including habitat generalists and specialists) in urban water and sediment across an urban-pollution gradient in Wuhan, central China. The diversity, community composition and potential function of bacteria and microeukaryotes showed significantly stronger variation between water and sediment than across an urban pollution gradient. Although, bacterial and microeukaryotic community assemblies were dominated by strong selection processes in both water and sediment habitats, but a contrasting community assembly mechanism was identified between habitat generalists and specialists. Bacterial and microeukaryotic communities showed a greater response to physicochemical variability in water, while a strong distance-decay relationship was found in sediment. Further, cross-kingdom microbial network analysis revealed strong modular associations of bacteria and microeukaryotes, meanwhile, microeukaryotic habitat specialists might be keystone, but generalists have higher proportion of connections in the networks. This study provides significant insights into the response of bacteria and microeukaryotes to different urban pollutions between water and sediment, and the ecological processes structuring microbial community dynamics across habitat types under anthropogenic disturbances.

Urban environment and health behaviours in children from six European countries

BACKGROUND

Urban environmental design is increasingly considered influential for health and wellbeing, but evidence is mostly based on adults and single exposure studies. We evaluated the association between a wide range of urban environment characteristics and health behaviours in childhood.

METHODS

We estimated exposure to 32 urban environment characteristics (related to the built environment, traffic, and natural spaces) for home and school addresses of 1,581 children aged 6-11 years from six European cohorts. We collected information on health behaviours including total amount of overall moderate-to-vigorous physical activity, physical activity outside school hours, active transport, sedentary behaviours and sleep duration, and developed patterns of behaviours with principal component analysis. We used an exposure-wide association study to screen all exposure-outcome associations, and the deletion-substitution-addition algorithm to build a final multi-exposure model.

RESULTS

In multi-exposure models, green spaces (Normalized Difference Vegetation Index, NDVI) were positively associated with active transport, and inversely associated with sedentary time (22.71 min/day less (95 %CI -39.90, -5.51) per interquartile range increase in NDVI). Residence in densely built areas was associated with more physical activity and less sedentary time, and densely populated areas with less physical activity outside school hours and more sedentary time. Presence of a major road was associated with lower sleep duration (-4.80 min/day (95 %CI -9.11, -0.48); compared with no major road). Results for the behavioural patterns were similar.

CONCLUSIONS

This multicohort study suggests that areas with more vegetation, more building density, less population density and without major roads are associated with improved health behaviours in childhood.

Spatiotemporal representativeness of air pollution monitoring in Dublin, Ireland

The importance of selecting appropriate air pollution monitoring sites in a city is vital for accurately reporting air quality, enhancing the quality of high-resolution modelling and informing policy to implement measures to deliver cleaner air in the urban environment. COVID-19 restrictions impacted air quality in urban centres worldwide as reduced mobility led to changes in traffic-related air pollution (TRAP). As such, it offered a unique dataset to examine the spatial and temporal variations in air quality between monitoring stations in Dublin, Ireland. Firstly, an analysis of mobility data showed reductions across almost all sectors after COVID-19 restrictions came into place, which was expected to lower TRAP. In addition, similar changes in air quality were evident to other cities around the world: reductions in fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations and an increase in ozone (O₃) concentrations. Average daily and diurnal concentrations for these three pollutants presented more statistically significant spatial and temporal changes during COVID-19 restrictions at monitoring sites with urban or traffic classifications than suburban background sites. Furthermore, substantial reductions in the range of average hourly pollutant concentrations were observed, 79% for PM_2.5 and 75% for NO₂, with a modest 24% reduction for O₃. Correlation analysis of air pollution between monitoring sites and years demonstrated an improvement in the R² for NO₂ concentrations only, suggesting that spatiotemporal homogeneity was most notable for this TRAP due to mobility restrictions during COVID-19. The spatiotemporal representativeness of monitoring stations across the city will change with greener transport, and air quality during COVID-19 can provide a benchmark to support the introduction of new policies for cleaner air.

Zoonotic Campylobacter spp. and Salmonella spp. carried by wild boars in a metropolitan area: occurrence, antimicrobial susceptibility and public health relevance

Campylobacter spp. and Salmonella spp. are the most reported zoonotic agents in Europe. They can be transmitted from wildlife to humans, and wild boars (Sus scrofa) can harbour them. In the Metropolitan Area of Barcelona (MAB, NE Spain) wild boars are found in urbanized areas. To assess the potential public health risk of this increasing wild boar population, we collected stool samples from 130 wild boars from the MAB (June 2015 - February 2016), to determine the Campylobacter and Salmonella occurrence and the antimicrobial susceptibility of the isolates. We also investigated the genetic diversity and virulence potential of Campylobacter. Campylobacter prevalence in wild boars was 61%. Forty six percent of wild boars carried Campylobacter lanienae, 16% carried Campylobacter coli, and 1% carried Campylobacter hyointestinalis; 4% carried both C. lanienae and C. coli, and 1% carried both C. lanienae and C. hyointestinalis. This is the first report of C. hyointestinalis in wildlife in Spain. Using pulse-field gel electrophoresis and multilocus sequence typing, we observed a high genetic diversity of Campylobacter and identified new sequence types. Thirty-three percent of C. coli and 14% of C. lanienae isolates showed a high virulence potential. All of the Campylobacter isolates analysed were resistant to at least one antimicrobial agent. Multidrug resistance was only detected in C. coli (67%). Salmonella enterica subsp. enterica was detected in four wild boars (3%) and included a S. Enteritidis serovar (1/4 wild boars) and a multidrug-resistant (ASSuT) monophasic S. Typhimurium serovar (1/4 wild boars) which is associated with human infections and pig meat in Europe. The characteristics of some of the Campylobacter and Salmonella isolates recovered suggest an anthropogenic origin. Wild boars are a reservoir of Campylobacter and have the potential to spread antimicrobial resistant Campylobacter and Salmonella in urbanized areas in the MAB.

Stress and emotional arousal in urban environments: A biosocial study with persons having experienced a first-episode of psychosis and persons at risk

This article examines the entanglement between feelings of stress and discomfort, physiological arousal and urban experiences of persons living with early psychosis. It adopts a biosocial approach, using mixed methods combining ambulatory skin conductance monitoring, mobile interviews and contextual data, collected through GPS and video recordings. The study draws on and strives to cross-fertilize two recent strands of research. The first relates to the use of digital phenotyping in mental health research. The second explores stress and emotional arousal in cities using ambulatory physiological measures. Empirically, the paper is based on fieldwork in Basel, Switzerland, with nine participants recruited within the Basel Early Treatment Service (BEATS), and four controls. We focus on three salient elements in our results: visual perception of moving bodies, spatial transitions and openness and enclosure of the built environment. The analysis shows how these elements elicit physiological responses of arousal and expressed feelings of discomfort. In the concluding section we discuss the methodological implications of these results and suggest the notion of regime of attention as a focus for future biosocial research on urban mental health.

A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery

High-spatial-resolution air quality (AQ) mapping is important for identifying pollution sources to facilitate local action. Some of the most populated cities in the world are not equipped with the infrastructure required to monitor AQ levels on the ground and must rely on other sources, like satellite derived estimates, to monitor AQ. Current satellite-data-based models provide AQ mapping on a kilometer scale at best. In this study we focus on producing hundred-meter-scale AQ maps for urban environments in developed cities. We examined the feasibility of an image-based object-detection analysis approach using very high-spatial-resolution (2.5 m) commercial satellite imagery. We fed the satellite imagery to a deep neural network (DNN) to learn the association between visual urban features and air pollutants. The developed model, which solely uses satellite imagery, was tested and evaluated using both ground monitoring observations and land-use regression modeled PM2.5 and NO2 concentrations over London, Vancouver (BC), Los Angeles, and New York City. The results demonstrate a low error with a total RMSE < 2 µg/m3 and highlight the contribution of specific urban features, such as green areas and roads, to continuous hundred-meter-scale AQ estimation. This approach offers promise for scaling to global applications in developed and developing urban environments. Further analysis on domain transferability will enable application of a parsimonious model based merely on satellite images to create hundred-meter-scale AQ maps in developing cities, where current and historical ground data is limited.