Respiratory health is negatively influenced by the dimensions and constituents of particulate matter (PM). Although mass concentration is widely acknowledged to be key to assessing dust retention by urban trees, the role of plant leaves in filtering PM from the urban atmosphere, particularly regarding the particle dimensions and chemical constituents of retained PM on the leaf, remains elusive. Here we combined single-particle aerosol mass spectrometry and a particle resuspension chamber to investigate how urban tree species capture PM constituents. Results indicate that leaves are efficient in capturing relatively larger particles (1.0-2.0 μm). Compositionally, airborne particles were mostly composed of elemental carbon (EC, 20%), organic carbon (OC, 17%), and secondary reaction products (13%). However, leaf surfaces revealed a preference for retaining crustal species, comprising 55% of captured particulates. Notably, specific tree species demonstrated varied affinities for different PM constituents: Osmanthus fragrans Lour. predominantly captured levoglucosan (LEV), indicative of its efficiency against biomass burning particles, whereas Cinnamomum camphora (L.) J.Presl and Sabina chinensis var. kaizuca W.C.Cheng & W.T.Wang were more effective in capturing heavy metals (HMs). XGBoost modelling identified indicator ions, e.g., CN-, NO3-, NO2-, PO3-, with SHAP values surpassing 0.035, suggesting a preferential adsorption of these ions among different tree species. These findings demonstrate that the particulate capture efficiency of urban tree species varies with species-specific leaf properties, particularly in their ability to selectively adsorb particles containing hazardous constituents such as LEV and HMs. This study provides a scientific basis for the strategic selection of tree species in urban forestry initiatives aimed at improving air quality and public health.

Human health risks from particles with a diameter of less than 2.5 µm (PM2.5) highlight the role of urban trees as bio-filters in air pollution control. However, whether the size and composition of particles captured by various tree species differ or not remain unclear. This study investigates how leaf attributes affect the capture of PM2.5, which can penetrate deep into the lungs and pose significant health risks. Using a self-developed particulate matter (PM) resuspension chamber and single-particle aerosol mass spectrometer, we measured the size distribution and mass spectra of particles captured by ten tree species. Notably, Cinnamomum camphora (L.) J.Presl and Osmanthus fragrans Lour. are more effective at capturing particles under 1 µm, which are most harmful because they can reach the alveoli, whereas Ginkgo biloba L. and Platanus × acerifolia (Aiton) Willd. tend to capture larger particles, up to 1.6 µm, which are prone to being trapped in the upper respiratory tract. Leaf physiological traits such as stomatal conductance and water potential significantly enhance the capture of larger particles. The Adaptive Resonance Theory neural network (ART-2a) algorithm classified a large number of single particles to determine their composition. Results indicate distinct inter-species variations in chemical composition of particles captured by leaves. Moreover, we identified how specific leaf wax compositions-beyond the known sticky nature of hydrophobic waxes-contribute to particle adhesion, particularly highlighting the roles of fatty acids and alkanes in adhering particles rich in organic carbon and heavy metals, respectively. This research advances our understanding by linking leaf physiological and wax characteristics to the selective capture of PM2.5, providing actionable insights for urban forestry management. The detailed exploration of particle size and composition, tied to specific tree species, enriches the current literature by quantifying how and why different species contribute variably to air quality improvement. This adds a crucial layer of specificity to the general knowledge that trees serve as bio-filters, offering a refined strategy for planting urban trees based on their particulate capture profiles.

Trees in cities perform important environmental functions: they produce oxygen, filter pollutants, provide habitat for wildlife, mitigate stormwater runoff, and reduce the effects of climate change, especially in terms of lowering temperatures and converting carbon dioxide from the atmosphere into stored carbon. Generally, to increase the environmental benefits of urban forests, the number of trees is increased, directly influencing the canopy coverage. However, little is known about potential of modifying the species composition of urban tree communities in order to increase ecological benefits. Planting and managing trees to increase canopy is particularly challenging in city centres, where the dense, often historic infrastructure of buildings and roads do not allow for a significant increase in greenspace. Estimations of canopy cover obtained through i-Tree Canopy analysis unveiled significant potential to increase canopy cover in historical urban areas in Polish cities from 15-34% to 31-51%. This study models the ecological benefits of urban forests in Polish cities, focusing on how different species compositions can enhance environmental functions such as carbon sequestration and pollution filtration. Two main scenarios were analyzed: one involving the addition of trees based on the most common species currently planted (\"standard option\" SO), and another incorporating changes to the species composition to enhance ecological benefits (\"city specific option\" SCO). Acer platanoides (14.5%) and Tilia cordata (11.45%) were the most frequently species of Polish cities. Betula pendula, Quercus robur, Robinia pseudoacacia, Fraxinus excelsior, Acer pseudoplatanus, Aesculus hippocastanum and Acer campestre were also common species in urban forest communities (up to 5%). The diverse range of tree species in Polish cities contributes significantly to the overall carbon sequestration potential. The results suggest that modifying species composition could significantly increase carbon sequestration rates by 47.8%-114% annually, with the city specific option (SCO) being the most effective in enhancing carbon sequestration potential. This highlights the importance of strategic species selection in urban forestry practices to maximize environmental benefits and mitigate climate change effects.

Solitary bees and wasps that nest in cavities in tree trunks are important components of terrestrial ecosystems, providing pollination services, and in the case of wasps, the regulation of their prey populations. However, little is known about the vertical strata where bees and wasps build their nests. This is especially the case of urban forest remnants in the Amazon, which is relevant in the context of the global crisis in insect losses. We investigated the existence of vertical stratification in the nesting of solitary bees and wasps in an urban forest in Rio Branco, state of Acre, in the western Brazilian Amazon. We focused on whether wood temperature, ants, and termites are predictors of bee and wasp nesting. We sampled bee and wasp nests in the forest using trap-nests made with wooden blocks containing cavities with three different diameters for twelve months. Trap-nests were installed randomly at three heights in the forest. We collected 145 nests of 25 species, belonging to 11 genera and 6 families. A higher number of nests and species were collected in the upper stratum of the forest, strengthening the hypothesis that there is vertical stratification in the assemblage of solitary bees and wasps. Wood surface temperature and termite attacks on trap-nests were significantly different between strata, which may explain the vertical stratification of bee and wasp assemblages. Considering the importance of these insects for tropical forest ecosystems, the conservation of structurally complex and stratified forests is of paramount importance to maintain the diversity of this insect group.

The BeiDou Navigation Satellite System (BDS) provides real-time absolute location services to users around the world and plays a key role in the rapidly evolving field of autonomous driving. In complex urban environments, the positioning accuracy of BDS often suffers from large deviations due to non-line-of-sight (NLOS) signals. Deep learning (DL) methods have shown strong capabilities in detecting complex and variable NLOS signals. However, these methods still suffer from the following limitations. On the one hand, supervised learning methods require labeled samples for learning, which inevitably encounters the bottleneck of difficulty in constructing databases with a large number of labels. On the other hand, the collected data tend to have varying degrees of noise, leading to low accuracy and poor generalization performance of the detection model, especially when the environment around the receiver changes. In this article, we propose a novel deep neural architecture named convolutional denoising autoencoder network (CDAENet) to detect NLOS in urban forest environments. Specifically, we first design a denoising autoencoder based on unsupervised DL to reduce the long time series signal dimension and extract the deep features of the data. Meanwhile, denoising autoencoders improve the model\'s robustness in identifying noisy data by introducing a certain amount of noise into the input data. Then, an MLP algorithm is used to identify the non-linearity of the BDS signal. Finally, the performance of the proposed CDAENet model is validated on a real urban forest dataset. The experimental results show that the satellite detection accuracy of our proposed algorithm is more than 95%, which is about an 8% improvement over existing machine-learning-based methods and about 3% improvement over deep-learning-based approaches.

Urban forest soil is often disturbed by frequent human activity. Organic mulching is effective for improving soil quality; however, the effects of organic mulching on soil bacterial communities in urban forests are still largely unexplored. This study evaluated how organic mulching changed the urban forest soil bacterial community through an incubation experiment. Four treatments were applied: (1) no organic mulch (CK); (2) wood chips alone (5 g, Mw); (3) wood compost alone (5 g, Mc); and (4) wood chips + wood compost (This mulch was divided into two layers, i.e., the upper layer of wood chips (2.5 g) and the lower layer wood compost (2.5 g, Mw+c).) We found significant differences in the soil physicochemical properties under organic mulching after incubation. Overall, organic mulching can alter soil bacterial community structure. Soil alkali-hydrolyzable nitrogen, soil organic carbon, soil total nitrogen, and carbon-nitrogen ratio were the main factors affecting soil microbial community structures. Soil bacterial groups under organic mulching treatments mainly acted on the C and N cycling of functional pathways in soil. This study suggests that organic mulching could maintain the development of soil bacteria, which establishes a theoretical foundation for enhancing the microbiological environment of urban forest soils.

Urban forests as nature-based solutions (UF-NbS) play a crucial role for promoting the health and well-being of urban populations. Despite increasing recognition of their importance, knowledge gaps remain regarding UF-NbS implementation, particularly with respect to their performance, their perception, and on decision-making and governance practices for their implementation and management. Grounded in a project-as-practice approach and based on sixteen UF-NbS case histories, this paper seeks to gain insights into UF-NbS project actualities by an identification of characteristic trends as a function of a projects\' scope and purpose, or challenge-orientation, respectively. A particular emphasis is on project structure and coordination, on the scope and depth of participation and stakeholder involvement, and on funding mechanisms. Identified trends reveal centrally coordinated, single-responsible public authorities as the most common project structure, but with certain feature contents, i.e., regeneration and reclamation, as being associated with more decentralised forms of governance. It is concluded that irrespective of challenge-orientation, comparatively broad participation appears to be realised within the UF-NbS framework, however, the depth of participation differs considerably. With respect to funding, a strong reliance on public capital is asserted for the UF-NbS context, however, various forms of private contributions appear reasonably common across the assessed case histories. Recommendations for policy-making and avenues of future research are identified, including the validation of identified trends, the fostering of collaboration, the dispersal of decision-making authority, the encouragement for implementing non-tokenistic modes of participation in UF-NbS governance, and the promotion of potentially under-utilised funds.

Nitrogen (N) and phosphorus (P) are the two most important macronutrients supporting forest growth. Unprecedented urbanization has created growing areas of urban forests that provide key ecosystem services for city dwellers. However, the large-scale patterns of soil N and P content remain poorly understood in urban forests. Based on a systematic soil survey in urban forests from nine large cities across eastern China, we examined the spatial patterns and key drivers of topsoil (0-20 cm) total N content, total P content, and N:P ratio. Topsoil total N content was found to change significantly with latitude in the form of an inverted parabolic curve, while total P content showed an opposite latitudinal pattern. Variance partition analysis indicated that regional-scale patterns of topsoil total N and P contents were dominated by climatic drivers and partially regulated by time and pedogenic drivers. Conditional regression analyses showed a significant increase in topsoil total N content with lower mean annual temperature (MAT) and higher mean annual precipitation (MAP), while topsoil total P content decreased significantly with higher MAP. Topsoil total N content also increased significantly with the age of urban park and varied with pre-urban soil type, while no such effects were found for topsoil total P content. Moreover, topsoil N:P ratio showed a latitudinal pattern similar to that of topsoil total N content and also increased significantly with lower MAT and higher MAP. Our findings demonstrate distinct latitudinal trends of topsoil N and P contents and highlight a dominant role of climatic drivers in shaping the large-scale patterns of topsoil nutrients in urban forests.

Urban forests play a crucial role in the overall health and stability of urban ecosystems. Soil microorganisms are vital to the functioning of urban forest ecosystems as they facilitate material cycling and contribute to environmental stability. This study utilized high-throughput sequencing technology to examine the structural characteristics of bacterial and fungal communities in the bulk soil of six different forest stands: Phyllostachys pubescens (ZL), Metasequoia glyptostroboides (SSL), Cornus officinalis (SZY), mixed broad-leaved shrub forest (ZKG), mixed pine and cypress forest (SBL), and mixed broad-leaved tree forest (ZKQ). Soil samples were collected from each forest stand, including the corners, center, and edges of each plot, and a combined sample was created from the first five samples. The results revealed that among the bacterial communities, ZKG exhibited the highest alpha diversity in spring, while ZL demonstrated the highest alpha diversity in both summer and autumn. Proteobacteria was the most abundant bacterial phylum in all six forest stand soils. The dominant fungal phylum across the six forest stands was identified as Ascomycota. Notably, the microbial community diversity of SBL bulk soil exhibited significant seasonal changes. Although ZL exhibited lower bacterial community diversity in spring, its fungal community diversity was the highest. The bulk soil microbial diversity of ZL and SSL surpassed that of the other forest stands, suggesting their importance in maintaining the stability of the urban forest ecosystem in the Zhuyu Bay Scenic Area. Furthermore, the diversity of the bulk soil microbial communities was higher in all six stands during spring compared to summer and autumn. Overall, this study provides valuable insights into the seasonal variations of bulk soil microbial communities in urban forests and identifies dominant tree species, offering guidance for tree species\' selection and preservation in urban forest management.

Litter decomposition is an important source of soil organic carbon, and it plays a key role in maintaining the stability of forest ecosystems. The microbial mechanism of soil organic carbon (SOC) formation in different urban forest planting patterns during litter lignocellulose degradation is still unclear. The key genes, microbes, and metabolites in the process of lignocellulose degradation and SOC formation were determined by metagenomics and metabolomics in different litter decomposition layers and soil layers in different urban forest planting patterns, including three types of broadleaf forests (BP forests), three types of coniferous forests (CP forests), and two types of mixed coniferous and broadleaf forests (MCBP forests). The results indicated that the cellulose, hemicellulose, and lignin concentrations from the undecomposed layer to the totally decomposed layer decreased by 70.07, 86.83, and 73.04% for CP litter; 74.30, 93.80, and 77.55% for BP litter; and 62.51, 48.58, and 90.61% for MCBP litter, respectively. The soil organic carbon of the BP forests and MCBP forests was higher than that of the CP forests by 38.06 and 94.43% for the 0-10 cm soil layer and by 38.55 and 20.87% for the 10-20 cm soil layer, respectively. Additionally, the gene abundances of glycoside hydrolases (GHs) and polysaccharide lyases (PLs) in the BP forests were higher than those in the MCBP forests and CP forests. Amino acid metabolism, sugar metabolism, TCA metabolism, and cAMP signaling metabolism were mainly between the CP forests and BP forests, while the TCA cycle, pyruvate metabolism, phenylalanine metabolism, and tyrosine metabolism were mainly between the BP forests and MCBP forests during litter decomposition. Additionally, ammonia nitrogen and hemicellulose were key factors driving SOC formation in the CP forests, while ammonia nitrogen, hemicellulose, and lignocellulose-degrading genes were key factors driving SOC formation in the BP forests. For the MCBP forests, cellulose, pH, ammonia nitrogen, and lignin were key factors driving SOC formation. Our findings revealed that the BP forests and MCBP forests had stronger lignocellulose degradation performance in the formation of SOC. This study provided a theoretical basis for the flow and transformation of nutrients in different urban forest management patterns.