Urban Environment Research Articles

Molecular Detection of Viral and Bacterial Pathogens in Red Foxes (Vulpes vulpes) from Italy.

Animals, including wildlife, are part of One-Health concept since many infectious diseases can affect both humans and animals. In this study, 126 red foxes (Vulpes vulpes) from Northern Italy in 2022-2023 were tested by molecular assays for Protoparvovirus carnivoran 1 (PPVC-1), Canine adenovirus type 1 and 2 (CAdV-1 and CAdV-2), Circovirus canine (CanineCV), Canine distemper virus (CDV), and Leptospira spp. A total of 39 of 126 (30.9%) red foxes were infected with at least one pathogen and five of these were coinfected: 20/126 (15.9%) red foxes tested positive for PPVC-1, 3/126 (2.4%) for CAdV, 20/126 (15.9%) for CanineCV, and 2/126 (1.6%) for Leptospira spp. DNA. No foxes tested positive for CDV RNA. The pathogens identified were genetically analysed. New findings were reported such as a fox with multiple feline panleukopenia virus (FPV) and canine parvovirus type 2b (CPV-2b) infection associated with quasispecies dynamics, typical genetic characteristics of the identified CanineCV, and the first detection in red foxes of Leptospira ST198 related to L. interrogans serogroup Australis. Further studies are necessary to investigate the transmission between domestic animals and wildlife and to understand the role of red foxes in the maintenance of these pathogens not only in the wild but also in urban and peri-urban environments.

Augmented reality navigation method based on image segmentation and sensor tracking registration technology

With the rapid development of modern science and technology, navigation technology provides great convenience for people's life, but the problem of inaccurate localization in complex environments has always been a challenge that navigation technology needs to be solved urgently. To address this challenge, this paper proposes an augmented reality navigation method that combines image segmentation and multi-sensor fusion tracking registration. The method optimizes the image processing process through the GA-OTSU-Canny algorithm and combines high-precision multi-sensor information in order to achieve accurate tracking of positioning and guidance in complex environments. Experimental results show that the GA-OTSU-Canny algorithm has a faster image edge segmentation rate, and the fastest start speed is only 1.8 s, and the fastest intersection selection time is 1.2 s. The navigation system combining the image segmentation and sensor tracking and registration techniques has a highly efficient performance in real-world navigation, and its building recognition rates are all above 99%. The augmented reality navigation system not only improves the navigation accuracy in high-rise and urban canyon environments, but also significantly outperforms traditional navigation solutions in terms of navigation startup time and target building recognition accuracy. In summary, this research not only provides a new framework for the theoretical integration of image processing and multi-sensor data, but also brings innovative technical solutions for the development and application of practical navigation systems.

Insights Into Urban Heat Island and Heat Waves Synergies Revealed by a Land‐Surface‐Physics‐Based Downscaling Method

AbstractResearchers have recently focused on the interplay of the urban heat island (UHI) effect and heat waves (HWs). However, the synergies of these two phenomena remains inconclusive at present. To address this gap, this study investigated UHIs and HWs synergies during the last 30 years in the Tokyo metropolitan area, through a unique and novel approach named Land‐Surface‐Physics‐Based Downscaling (LSP‐DS). LSP‐DS integrates the widely used Noah‐Multiparameterization (Noah‐MP) land‐surface model coupled with urban canopy‐process physics, aiming to conduct high‐resolution, long‐term urban‐specific simulations with much less computational resources. Our comprehensive analysis combining observation data and numerous LSP‐DS simulations confirms exacerbated UHIs during HWs. Specifically, HWs amplify the temperature differences between urban and rural environments, which is quantified by UHI intensity (UHII). During HWs, UHII increased more at night in inland areas and more during daytime in coastal areas. HWs present especially a heightened threat to coastal regions where daytime UHII increased by approximately 1°C during HWs. The Bowen ratio can explain the increase in the daytime UHII, and the daytime accumulated storage heat increase during HWs can explain the increase in nighttime UHII. Based on future projections of the increasing frequency of high temperatures, our findings highlight the impending heat‐related health challenges faced by urban residents.

Location Selection Methods for Urban Terminal Co-Distribution Centers with Air–Land Collaboration

Urban terminal logistics and distribution enterprises face the problems of duplicated network layouts, high costs, and inefficient urban environments. Recently, collaborative distribution using unmanned aerial vehicles (UAVs) and ground vehicles has been considered as a means of reducing costs and enhancing efficiency, thus overcoming the issues created by the high-density layout of enterprises’ relatively independent networks. This essentially involves constructing an air–ground collaborative common distribution network. To optimize the economic cost and distribution time of network operations, we established a site selection planning model for air–ground cooperative urban co-distribution centers and designed a solution method based on gray wolf optimization with K-means clustering. Taking the Wangsheren area of Jinan City, China, as an example, 15 UAV co-distribution centers and 13 vehicle co-distribution centers were identified. Although the average distribution cost of the network rose by 35–50% compared to traditional terminal distribution, the time saving was 80–85%, greatly improving the high-value-added service capacity. The end-distribution efficiency and customer satisfaction were also enhanced, which fully verifies the feasibility, validity, and applicability of the proposed model. Our approach can be applied to landing sites and the planning and optimization of large-scale commercial operations using logistics UAVs in urban areas.

Resilient trees for urban environments: The importance of intraspecific variation

Societal Impact StatementTrees in urban environments provide us with shade, heat mitigation, flood abatement, noise and pollution reduction, pollination, beauty, and much more. However, many of these benefits are strongly connected to tree size and vitality, with larger, healthier trees providing ecosystem services more effectively, which means that selecting the right tree for site and function is crucial in order to gain all benefits from our urban trees.SummaryTrees play a major role in the Earth's biogeochemical processes, influencing soil production, hydrological, nutrient and carbon cycles, and the global climate. They store about 50% of the world's terrestrial carbon stocks, and provide habitats for a wide range of other species, supporting at least half of the Earth's known terrestrial plants and animals. Trees are not only found in forests and other natural ecosystems, but also in urban environments. Most of the human population is concentrated in cities, towns and villages, so urban trees are critical to meet on‐going and future social, economic and environmental challenges. However, many urban tree populations are strongly challenged by a changing climate, outbreaks of pests and pathogens and an urban development with increasingly dense cities and a high proportion of impermeable surface materials. The importance of intraspecific variation needs to be better acknowledged in this context, since poor matching of trees and the local climate and growing conditions can lead to extensive loss of valuable trees. By using the right genetic plant material for the challenging urban environments, a more resilient tree population with a greater diversity and higher capacity for delivering ecosystem services can be gained. Here, we wish to discuss the need to consider intraspecific variation when planning resilient tree populations for urban environments and how seed banks and botanical garden play important roles in efforts to improve the matching of genetic plant material for future environmental challenges. Strategies to enrich urban tree diversity and increase resilience are outlined.

MINERALOGICAL AND GEOCHEMICAL PARAMETERS OF SNOW COVER WITHIN THE ANTHROPOGENICALLY DISTURBED SITES OF THE NADYM-PUR INTERFLUVE (NORTHERN PART OF WESTERN SIBERIA)

The article analyzes the content of metals in solid aerosols and snow water sampled in the anthropogeni-cally disturbed and background sites of the Nadym-Pur interfluve. The results of microscopic studies of solid aerosols showed the presence of secondary minerals, technogenic formations, as well as a large amount of pyrite in samples from the eastern part of the study area. The maximum concentrations of metals in solid aero-sols were found in snow of the sanitary protection zones of waste disposal facilities, with the exception of Ca, which prevails in snow cover of Novy Urengoy (up to 10% of dry matter). The urbanized area is characterized by the highest values of dust load (up to 111 mg/m2 a day). The local contamination with Ba within the waste landfills in Novy Urengoy is associated with the sites of barite and drilling waste processing. We applied the factor analysis to identify the main metal associations characteristic of solid aerosols from different functional zones: Ca-Co-V-Mn (city), Ba-Sr-K-Na and Cd-Cu-Pb (waste disposal sites), Cu-Ni-Cd (the entire studied area). Based on the study of the content of dissolved forms in snow water, a high mobility of metals in the northern landscapes and its decrease in urban environment were revealed. The mineralogical and geochemical analysis of snow suggests the influence of the Norilsk industrial region on the eastern part of the Nadym-Pur interfluve, Zn, Cu, Ni, Pb and the mineral pyrite being the indicators. The risks of environmental pollution under the aerotechnogenic transport are associated with high content of Zn, Cu, Ni, Pb and Ba in solid aero-sols. The calculation of the Toxicity Probability Index (MERMQ) showed that some aerosol samples from the landfill sites have a high probability of biological effects. Using data on the chemical composition of soils and soil water, no visible effect of snow pollution on the growth of metal concentrations in soil and soil water was revealed, with the exception of local contamination with Ba, which led to a twofold increase in the content of the metal in the upper soil horizon.

Distribution Profile of Benthic Macroinvertebrates in Some Rivers of Yaoundé City and Its Surroundings Using Self Organizing Map and Indicator value methods

Urban sprawl leads to the degradation of aquatic environments and, consequently, to the destruction of biodiversity. With the aim of highlighting the distribution profile of benthic macroinvertebrates in the city of Yaoundé and its surroundings according to the level of degradation, this study was carried out in seven rivers. A total of 144 taxa of benthic macroinvertebrates, belonging to 74 families, 15 orders, five classes, and three phyla, were collected from seven rivers in urban, peri-urban, and forest environments on Yaoundé and its surroundings. The self-organizing map (SOM) analysis tool was used to group the collected taxa from all stations into three clusters or affinity cores. The indicator value analysis (IndVal) method was employed to determine, based on their ecological preferences, which organisms were most likely to belong to each group. Out of the 144 collected taxa, only 44 were indicated to represent the three different groups. Thus, three communities were defined: the Hydropsyche community, with Hydropsyche sp. as the predominant taxon in Group III, characterizing well-oxygenated and low-mineralized stations; the Hydrocyrius community, where the species Hydrocyrius sp. predominates in Group I, describing stations with low oxygenation and moderate mineralization; and the Lumbriculidae community, where Lumbriculidae is the taxon associated with environments with high mineralization and critical oxygenation. These two methods contribute to the biomonitoring of tropical aquatic environments, firstly by grouping organisms by affinity and then identifying those that reflect the environment conditions. This facilitates the detection of changes in the quality of hydrosystems and guides management and conservation efforts.

Low-Cost IoT Air Quality Monitoring Station Using Cloud Platform and Blockchain Technology

Air pollution is a growing concern due to severe threats to public health and the environment. The need for reliable air quality monitoring solutions has never been more critical. This research paper introduces an innovative approach to addressing this challenge by deploying a low-cost Internet of Things (IoT) air monitoring station and providing a blockchain technology solution to enhance environmental data transparency, reliability, and accessibility. Our paper adopts a concept of merging IoT and blockchain technologies and collecting some parameters that help to assess air quality by using three sensors, DHT11, MQ7, and MQ135, to collect temperature, humidity, carbon monoxide, and carbon dioxide parameters, respectively, to measure the gases and thus indicate the air quality within the surrounding area. Collecting and sharing these types of valuable data will be very important for various stakeholders, such as governmental bodies, researchers, and the public. This approach is consistent with the principles of sustainable development, facilitating informed decision-making and promoting eco-friendly policies. This research explores the technical architecture of the IoT air monitoring stations, offering a promising solution for addressing air pollution concerns while promoting sustainable development goals. The proposed system is a model for leveraging emerging technologies to advance environmental monitoring and create smarter, livable cities. This approach aligns with the principles of sustainable development and eco-friendly initiatives. This research offers a promising model for enhancing environmental monitoring efforts and advancing the creation of smarter, more sustainable urban environments. The proposed IoT, cloud platform and blockchain-based system not only addresses pressing air pollution challenges but also sets a benchmark for leveraging emerging technologies in environmental science.

Linking the macroclimatic niche of native lithophytic ferns and their prevalence in urban environments.

Vertical surfaces in urban environments represent a potential expansion of niche space for lithophytic fern species. There are, however, few records of differential success rates of fern species in urban environments. The occurrence rates of 16 lithophytic fern species native to the northeastern USA in 14 biomes, including four urban environments differentiated by percentage of impervious surfaces, were evaluated. In addition, the natural macroclimatic ranges of these species were analyzed to test whether significant differences existed in climatic tolerance between species that occur in urban environments and species that do not. Three species appear to preferentially occur in urban environments, two species may facultatively occur in urban environments, and the remaining 11 species preferentially occur in nondeveloped rural environments. The natural range of fern species that occur in urban environments had higher summer temperatures than the range of species that do not, whereas other macroclimatic variables, notably winter temperatures and precipitation, were less important or insignificant. Vertical surfaces in urban environments may represent novel niche space for some native lithophytic fern species in northeastern USA. However, success in this environment depends, in part, on tolerance of the urban heat island effect, especially heating of impervious surfaces in summer.

Application of polyhedral meshes in large-eddy simulation of building array flow fields within neutral and unstable boundary layers

Urbanization has intensified the urban heat island phenomenon, a critical concern for human habitation in recent decades. Analyzing flow fields around building arrays is vital for mitigating issues such as heatstroke and air pollution, thereby enhancing human comfort in urban environments. However, challenges in accuracy and computational efficiency persist in simulating urban thermal environments. This study evaluates how boundary layer meshes in polyhedral meshes affect wind and temperature distributions in neutral and unstable boundary layers, utilizing large-eddy simulations. A total of ten cases were examined, including eight with local mesh refinement and two without. The study demonstrates that local mesh refinement is an effective strategy to reduce mesh count by approximately 60%, thereby reducing computational time by 60% using the same computational configuration. The performance of the polyhedral meshes was found to be comparable to that of the hexahedral meshes. For the mean velocity and temperature, the discrepancies between the hexahedral and polyhedral cases were within 10%, while for the second-order statistics, the discrepancies were within 20%. Within the neutral boundary layer, boundary layer meshes on the ground and building surfaces had minimal impact on the wind field. However, these meshes enhanced the accuracy of low percentile wind speed estimations by approximately 20% within the unstable boundary layer. Moreover, this study lays the foundation for research on the thermal environment in actual urban areas and contributes to the guidelines for LES with non-isothermal inflow conditions.

Behavioural changes in the city: The common black garden ant defends aphids more aggressively in urban environments.

Urbanisation alters biodiversity patterns and threatens to disrupt mutualistic interactions. Aside from pollination, however, little is known about how mutualisms change in cities. Our study aimed to assess how urbanisation affects the protective mutualism between ants and aphids, investigating potential behavioural changes in mutualistic ants and their implications for aphids in urban environments. To do so, we studied the protective mutualism between the pink tansy aphid (Metopeurum fuscoviride) and the black garden ant (Lasius niger) along an urbanisation gradient in Berlin, Germany. In nine locations along this gradient, we measured aphid colony dynamics and proxies for parasitism, quantified the investment of ants in tending aphids and conducted behavioural assays to test the aggressiveness of ant responses to a simulated attack on the aphids. We found that aphid colonies flourished and were equally tended by ants across the urbanisation gradient, with a consistent positive density dependence between aphid and ant numbers. However, ants from more urbanised sites responded more aggressively to the simulated attack. Our findings suggest that this protective mutualism is not only maintained in the city, but that ants might even rely more on it and defend it more aggressively, as other food resources may become scarce and more unpredictable with urbanisation. We thereby provide unique insights into this type of mutualism in the city, further diversifying the growing body of work on mutualisms across urbanisation gradients.

A new equilibrium temperature inflow profile for modelling the non-isothermal atmospheric boundary layer in CFD simulation

The atmospheric boundary layer (ABL) flow in urban morphologies, ranging from micro-scale to local-scale, will become non-isothermal due to the combined effects of solar radiation, wall heat transfer, the urban heat island, and anthropogenic heat, resulting in a mutually coupled urban thermal and wind environment. An appropriate temperature inflow profile is the key prerequisite for Computational Fluid Dynamics (CFD) simulations of the non-isothermal ABL flow and the urban thermal and wind environment, as it must coincide with actual thermal characteristics while being compatible with CFD. Based on the equilibrium ABL model, a new equilibrium temperature inflow profile compatible with the energy equation, the standard gradient diffusion hypothesis, and the turbulence model is derived, which is proportional to the turbulent kinetic energy inflow profile, with the ratio further determined by the wall heat flux, demonstrating that turbulent thermal diffusion is strongly related to turbulent characteristics and atmospheric stability. To address the scaled effect, its full expression is provided based on thermodynamic similarity criteria. Using a numerical model of empty domain based on the SST k-ω model, the horizontal homogeneity of the equilibrium thermal and wind field modeled by the new set of inflow profiles is verified. Taking the flow around a single square building model as an example, its applicability in simulating the urban thermal and wind environment around buildings has been numerically validated, where the comparison of numerical and test results reveals tolerable errors overall.

A scaling region identification method for the divider dimension of urban thermal environments

Abstract A scaling region identification method for divider dimensions using the coefficient of determination is proposed to improve the estimation accuracy of the divider dimension in the study of urban thermal environment differentiation characteristics. The effectiveness of this method was verified by analyzing the urban surface thermal field differentiation characteristics by applying the estimated divider dimensions of Nanjing’s thermal environment surfaces and transect lines. The research results show that the urban thermal environment has fractal characteristics only within a certain temperature threshold range. When the constraint of scaling regions is considered, the calculated divider dimension of the surface thermal field surface increases, reflecting the more complex fractal structure of the thermal field. For each temperature grade, the “trough” position of the thermal field divider dimension surface estimated by the line-divider method is near the determination level of the high-temperature region based on robust statistics, allowing the spatial extent of the urban heat island (UHI) to be determined based on the “trough” feature of the thermal field divider dimension surface.

Landscape configuration as a proxy for the occurrence and conservation of forest birds in peri-urban and urban environments

Landscape configuration as a proxy for the occurrence and conservation of forest birds in peri-urban and urban environments

GPU implementation of the Frenet Path Planner for embedded autonomous systems: A case study in the F1tenth scenario

Autonomous vehicles are increasingly utilized in safety-critical and time-sensitive settings like urban environments and competitive racing. Planning maneuvers ahead is pivotal in these scenarios, where the onboard compute platform determines the vehicle’s future actions. This paper introduces an optimized implementation of the Frenet Path Planner, a renowned path planning algorithm, accelerated through GPU processing. Unlike existing methods, our approach expedites the entire algorithm, encompassing path generation and collision avoidance. We gauge the execution time of our implementation, showcasing significant enhancements over the CPU baseline (up to 22x of speedup). Furthermore, we assess the influence of different precision types (double, float, half) on trajectory accuracy, probing the balance between completion speed and computational precision. Moreover, we analyzed the impact on the execution time caused by the use of Nvidia Unified Memory and by the interference caused by other processes running on the same system. We also evaluate our implementation using the F1tenth simulator and in a real race scenario. The results position our implementation as a strong candidate for the new state-of-the-art implementation for the Frenet Path Planner algorithm.

Outage probability analysis for downlink NOMA ARS-assisted cooperative communication system with trajectory optimization

In this paper, we propose and investigate the performance of a downlink non-orthogonal multiple access multi-user system with the assistance of an aerial relay station (ARS). The ARS is equipped with multiple antennas, mounted on an unmanned aerial vehicle (UAV), and serves as a relay for cooperative communication between a terrestrial base station (BS) and users. The system performance is evaluated via the outage probability of each user in the urban environment where the ARS and BS are configured with a different number of antennas. More interestingly, the optimization of the ARS trajectory to maximize the data rate of the considered system is also proposed by using the successive convex approximation technique. The results show that the best system performance can be obtained by adjusting the altitude and designing the optimum trajectory of the ARS. Monte-Carlo simulation results are provided to demonstrate the performance of the proposed system and the accuracy of the developed analytical frameworks.

Towards Mass-Scale IoT with Energy-Autonomous LoRaWAN Sensor Nodes.

By 2030, it is expected that a trillion things will be connected. In such a scenario, the power required for the trillion nodes would necessitate using trillions of batteries, resulting in maintenance challenges and significant management costs. The objective of this research is to contribute to sustainable wireless sensor nodes through the introduction of an energy-autonomous wireless sensor node (EAWSN) designed to be an energy-autonomous, self-sufficient, and maintenance-free device, to be suitable for long-term mass-scale internet of things (IoT) applications in remote and inaccessible environments. The EAWSN utilizes Low-Power Wide Area Networks (LPWANs) via LoRaWAN connectivity, and it is powered by a commercial photovoltaic cell, which can also harvest ambient light in an indoor environment. Storage components include a capacitor of 2 mF, which allows EAWSN to successfully transmit 30-byte data packets up to 560 m, thanks to opportunistic LoRaWAN data rate selection that enables a significant trade-off between energy consumption and network coverage. The reliability of the designed platform is demonstrated through validation in an urban environment, showing exceptional performance over remarkable distances.

Environment adaptive navigation (EAN): A data-driven approach for improved navigation accuracy

The quality of GNSS-based navigation services is highly influenced by the type of operating environment. The urban environments with buildings and structures pose substantial challenges for GNSS navigation accuracy. To address this challenge, we propose a data-driven approach Environment Adaptive Navigation (EAN) because complex mathematical models for GNSS environments are impractical for real-time use due to their processing load. This data-driven approach analyzes real-time GNSS data to understand how the environment affects performance and optimize receiver settings for each scenario. Keeping this in view, raw GNSS data was collected through field trials including the three environments: clear sky, partially degraded, and highly degraded. We then analyzed this data to pinpoint factors affecting accuracy, such as the number of available satellites and standard error measurements. The proposed solution, the EAN algorithm, tackles these limitations of the GNSS due to the urban environments and improves the navigation performance. This data-driven approach analyzes real-time GNSS data to identify the specific environment (clear, partially degraded, or highly degraded). Based on this assessment, EAN dynamically adjusts receiver settings, like tracking loop bandwidth, to achieve optimal performance under those conditions. Integrating the EAN model into GNSS receivers allows for real-time environment detection and adaptive configuration. This EAN-based GNSS receiver holds significant promise for safety-critical applications like Intelligent Transportation Systems (ITS). Precise navigation is crucial for functionalities within ITS, such as route optimization and autonomous vehicle operation. The effectiveness of the EAN-based receiver was validated through a field experiment demonstrating a notable increase in tracked satellites and a substantial reduction in outages within a highly degraded environment.

Line-of-sight Cox percolation on Poisson-Delaunay triangulation

In this work, percolation properties of device-to-device (D2D) networks in urban environments are investigated. On a street system modeled by a Poisson-Delaunay triangulation (PDT), users are of two types: given either by a Cox process supported by the edges of the PDT (i.e. on streets) or by a Bernoulli process on the vertices of the PDT (i.e. at crossroads). We state several percolation regimes for the resulting connectivity graph according to the parameters of the model. This work completes and specifies results of Le Gall et al. (2021). To do it, we take advantage of a percolation tool, inspired by enhancement techniques, used to our knowledge for the first time in the context of communication networks.

Water-energy-food-greenhouse gases nexus management in urban environments: A robust multi-agent decision-support system

Conceptual urban water metabolism (CUWM) models provide a holistic view of the efficiency of urban water systems. These models can be linked with multi-agent reinforcement learning (MARL) models to mimic stakeholders' reactions to various strategies. However, the outcomes derived from CUWM-MARL models come with uncertainty. As a result, this paper introduces a decision support system (DSS) that is aware of these uncertainties and uses this information to select robust management strategies based on the output of CUWM-MARL models. First, future scenarios are generated by exploring all combinations of critical values of deeply uncertain variables and values of uncertain variables sampled from an appropriate multivariate copula distribution. Then, a computationally efficient surrogate model is developed to alleviate the computational load of the MARL sub-model. The surrogate model is run through all future scenarios to calculate the system's key performance indicators (KPIs) for each management strategy. Urban water managers can use these KPIs and social choice methods to find consensus management strategies. The proposed methodology has been implemented in the western part of the Tehran metropolitan area, Iran. This study evaluates 26 management strategies consisting of various projects, including reducing water distribution network leakage, implementing urban demand control projects, and utilizing semi-centralized or decentralized wastewater treatment plants. The strategy chosen by the uncertainty-aware DSS enhances the total utility and fairness indices by 125% and 4%, respectively. Moreover, it effectively improves groundwater quality, reduces energy consumption and greenhouse gas emissions, and enhances water supply reliability, ultimately contributing to farmers' job security.