Search Results (45)

Urban roadside forests are vital components of green infrastructure that provide multiple ecosystem services, contributing to climate regulation, environmental quality, and urban resilience. This study assessed the multifunctional ecosystem services of roadside tree communities along four representative road types—Coastal Scenic, Commercial Arterial, Residential Secondary, and Industrial Park Roads—in Weihai, a coastal city in eastern China. Based on a complete tree inventory (6742 individuals from 38 species) integrated with the i-Tree Eco model, we quantified three key ecosystem services, carbon storage and annual sequestration, air-pollutant removal, and stormwater interception, and monetized their benefits. Results indicate that roadside forests stored approximately 1120 tons of carbon and sequestered 78 tons annually (≈USD 0.53 million; CNY 3.85 million), removed 1.28 tons of air pollutants per year (≈USD 9370; CNY 68,400), and intercepted 1560 m³ of stormwater (≈USD 5560; CNY 40,600). Commercial Arterial and Coastal Scenic Roads yielded the highest total ecosystem-service values, while Residential Secondary Roads achieved the greatest per-area efficiency. These findings highlight the significant contribution of urban roadside forests to sustainable and climate-resilient city development and underscore their potential role in urban forest planning and management. Full article

The rapid urbanization process has led to deteriorating air quality and elevated carbon dioxide levels, highlighting an urgent need for effective urban greening strategies. This study aims to quantify and compare the air pollution removal (APR), carbon sequestration (CS), and oxygen production (OP) capacities of different green space renovation plans in residential areas of a typical arid to semi-arid city in Northwest China. Using the i-Tree Eco model, we simulated the ecological benefits of various vegetation configurations. Our results demonstrated that tree species selection is a critical determinant of ecological performance. Ligustrum (Privet), Magnolia, and Populus (Poplar) were identified as the predominant species, exhibiting distinct effectivities in providing these services. Specifically, we found that species with high APR and CS efficiencies should be prioritized for green space renewal in this water-limited region. Correlation analysis revealed that both APR and CS capacities were most strongly correlated with vegetation greenness, followed by species identity. In contrast, the planning layout of vegetation showed no significant correlation with greenness. For OP, tree species was the most influential factor, ahead of vegetation quantity. This study provides a scientific basis for optimizing plant species selection and spatial arrangement in urban greening projects, offering practical guidance for enhancing ecological benefits in arid and semi-arid cities undergoing renewal. Full article

This study provides the first comprehensive, field-inventory-based assessment of urban ecosystem services within a Russian university campus, focusing on the woody vegetation of the Lobachevsky State University of Nizhny Novgorod. Utilizing a detailed field tree inventory combined with the i-Tree framework (including i-Tree Eco, i-Tree Canopy, UFORE, and i-Tree Hydro models), we quantified the campus’s capacity for carbon storage and sequestration, air pollutant removal, and stormwater runoff mitigation. The campus green infrastructure, comprising 1887 trees across 32 species with a density of 145.5 stems per hectare, demonstrated significant ecological value. Results show a carbon storage density of 26.61 t C ha⁻¹ and an annual gross carbon sequestration of 11.43 tons. Furthermore, the campus trees removed 1213.7 kg of air pollutants annually (a deposition rate of 9.35 g m⁻²), with ozone, particulate matter, and sulfur dioxide showing the highest deposition. The campus also retained 956.1 m³ of stormwater annually. These findings, particularly the high carbon sequestration rates, are attributed to the dominance of relatively young, fast-growing tree species. This research establishes a critical baseline for understanding urban ecosystem services in a previously under-researched geographical context. The detailed, empirical data offers crucial insights for urban planners and policymakers in Nizhny Novgorod and beyond, advocating for the strategic integration of ecosystem services assessments into campus planning and broader urban green infrastructure development across Russian cities. The study underscores the significant role of university campuses as vital components of urban green infrastructure, contributing substantially to environmental sustainability and human well-being. Full article

Urban expansion intensifies population exposures to fine particulate matter (PM_2.5). Trees mitigate pollution by dry deposition, in which particles settle on plants. However, city-scale models frequently overlook differences in tree species and structure. This study assesses PM_2.5 removal by individual city-owned street trees in Mississauga, Canada, throughout the 2019 leaf-growing season (May to September). Using a modified i-Tree Eco framework, we evaluated the removal of PM_2.5 by 200,560 city-owned street trees (245 species) in Mississauga from May to September 2019. The model used species-specific deposition velocities (V_d) from the literature or leaf morphology estimates, adjusted for local winds, a 3 m-resolution satellite-derived Leaf Area Index (LAI), field-validated, crown area modelled from diameter at breast height, and 1 km² resolution PM_2.5 data geolocated to individual trees. About twenty-eight tons of PM_2.5 were removed from 200,560 city-owned trees (245 species). Coniferous species (14.37% of trees) removed 25.62 tons (92% of total), much higher than deciduous species (85.63%, 2.18 tons). Picea pungens (18.33 tons, 66%), Pinus nigra (3.29 tons, 12%), and Picea abies (1.50 tons, 5%) are three key species. Conifers’ removal efficiency originates from the faster deposition velocities, larger tree size, and dense foliage, all of which enhance particle deposition. This study emphasizes species-specific approaches for improving urban air quality through targeted tree planting. Prioritizing coniferous species such as spruce and pine can improve pollution mitigation, providing actionable strategies for Mississauga and other cities worldwide to develop green infrastructure planning for air pollution. Full article

Ecosystem-based adaptation (EbA) provides a practical framework for enhancing urban resilience. This study had three objectives: (i) to quantify the structural attributes and ecosystem services (ESs) of campus street trees, (ii) to integrate LiDAR-derived metrics with the i-Tree Eco model to improve assessment accuracy, and (iii) to evaluate how quantified ESs contribute to climate resilience and inform localized EbA strategies. Field surveys were complemented with LiDAR data to enhance estimation of leaf area index (LAI), canopy dimensions, and tree height. Results show that 2643 street trees representing 29 species provide substantial ESs, including carbon storage of 508,230 kg, annual carbon sequestration of 48,580.5 kg, removal of major air pollutants totaling 2132 kg/year, and stormwater runoff reduction of 2351.8 m³/year, with a combined annual economic value of USD 202,822.10. A small number of species dominated ES delivery, with C. camphora and M. indica contributing disproportionately to canopy structure and ecological benefits. These findings highlight the critical role of urban vegetation in carbon mitigation, air-quality regulation, and flood adaptation at the parcel scale. The study provides a replicable framework for integrating LiDAR-enhanced i-Tree assessments into urban greening policies. It also emphasizes the need for species diversification and the inclusion of omitted services (e.g., biodiversity support, microclimate regulation) in future work to deliver more comprehensive EbA planning. Full article

Urban trees play a crucial role in regulating hydrological processes within urban ecosystems by intercepting rainfall to effectively reduce surface runoff and mitigate urban flooding. Current research lacks a systematic quantification of rainfall interception capacity and its community-level impacts at the urban scale. This study adopts a city-scale perspective, integrating field survey data with the i-Tree Eco model to systematically explore the contributions of 20 factors to the average annual rainfall interception of tree species and the average annual rainfall interception efficiency of communities. The study revealed that Deciduous broadleaf trees (1.28 m³ year⁻¹) and Pure coniferous forests (90.7 mm year⁻¹) exhibited substantial rainfall interception capacity. Relative Height, Average Tree Height, Average Crown Width, and Planting Density of trees significantly influence interception capacity. Urban planning can optimize the selection of tree species (e.g., Paulownia, Populus tomentosa, etc.) and community structure (e.g., mixed planting of conifers and deciduous broadleaf trees) to improve rainfall interception capacity, thereby effectively reducing stormwater runoff, mitigating the risk of urban flooding. These findings provide a scientific basis for designing urban vegetation to mitigate flooding, support water management, and advance sponge city development. Full article

Carbon sinks are of great significance for mitigating the greenhouse effect and climate change. However, only a few carbon sink measurement methods are suitable for small-scale research, such as at the city-region scale. Methods that can accurately distinguish the high–low gradients of forest carbon sinks within small-scale areas have not yet been established. To fill this gap, we used a tree allometric growth model—the i-Tree Eco model—and applied it to Tai’an, which is a National Forest City in China. By using indicator conversion methods, we innovatively combined the China Forest Resources Inventory Geographic Information Database with i-Tree Eco. The results showed that i-Tree Eco successfully estimated the carbon sinks provided by urban–rural forests (in 2019)—the total carbon storage in Tai’an forest was 5,828,165.90 t; the average carbon storage per hectare was 37.19 tC·ha⁻¹; the total carbon sequestration was 936,789.03 tC·yr⁻¹; and the annual carbon sequestration was, on average, 5.97 tC·ha⁻¹·yr⁻¹. Our method improved the spatial resolution of carbon sequestration and storage compared to the commonly used InVEST model, from about 350 m × 350 m to 195 m × 195 m. Compared to the traditional IPCC method, the i-Tree Eco model provided greater accuracy and timeliness in small-scale carbon sequestration measurements, eliminating the need to wait for the next forest inventory to be published. Our method yielded results that covered the entire city region and better reflected the spatial heterogeneity of carbon sinks. We conclude that the innovative application of the i-Tree Eco model to urban–rural-scale carbon sink measurements provides stronger technical support for urban green space planning, as well as data guidance, in relation to local carbon mitigation strategies. Full article

Urban expressway interchanges, though primarily engineered for traffic efficiency, also serve as crucial ecological nodes within urban landscapes. This study evaluates the ecological functions of arborous vegetation across four typical interchange configurations—cloverleaf, single trumpet, double trumpet, and irregular—along the Nanjing Ring Expressway. Using the i-Tree Eco model, we quantified key ecosystem services, including carbon sequestration and storage, air pollutant removal, and stormwater mitigation. Field surveys documented 7985 trees from 45 species, with the 10 most abundant accounting for over two-thirds of total individuals. Results revealed that the trees sequester around 115 tons of carbon annually and store nearly 1850 tons in total, equivalent to an estimated economic benefit of ¥5.8 million. Trees also removed more than 1.5 tons of air pollutants and intercepted nearly 2400 cubic meters of stormwater each year. Species such as Sophora japonica, Phoebe zhennan, and Cinnamomum camphora emerged as key contributors to ecological performance. Among interchange types, double trumpet configurations yielded the highest overall service value, while single trumpet interchanges demonstrated superior efficiency per unit area. These findings highlight the underutilized ecological potential of transport-adjacent green spaces and underscore the importance of species selection and spatial design in maximizing multifunctional benefits. Full article

PM_2.5 is an air pollutant that has a direct link to increased cardiovascular and respiratory morbidity and mortality, which has been demonstrated in numerous studies. Existing research highlights species-specific variations in the capacity of trees to capture and retain particulate matter (PM). However, a critical gap remains regarding sensitivity analyses of i-Tree Eco model assumptions. Such analyses are crucial for validating the model’s PM deposition estimates against empirically derived efficiencies, a deficiency that the present study addresses. The study consisted of two steps: a tree inventory was carried out at three selected sites, based on which, an ecosystem service analysis was performed using i-Tree Eco, and samples were taken from the leaves of trees at the analysed sites, which were the basis for comparing the data from the i-Tree Eco method and laboratory methods. The study focused on comparing PM_2.5 and PM₁₀ removal estimates derived from both the model and laboratory measurements. The results revealed significant discrepancies between the modelled and laboratory values. A comparison of the average annual PM₁₀ accumulation measured using laboratory methods for individual tree species showed that Tilia sp. achieved 24%, Fraxinus sp. 47.6%, Aesculus sp. 50.77%, and Quercus robur 23.4% of the PM₁₀ uptake efficiency estimated by the i-Tree Eco model. For PM_2.5 uptake, the values obtained through both methods were more consistent. Furthermore, trees growing under more challenging environmental conditions exhibited smaller diameter at breast height (DBH) and lower PM₁₀ and PM_2.5 removal efficiency according to both methods. While I-Tree Eco incorporates tree biophysical characteristics and health status, its methodology currently lacks the resolution to reflect site-specific environmental conditions and local pollutant concentrations at the individual tree level. Therefore, laboratory methods are indispensable for calibrating, validating, and supplementing i-Tree Eco estimates, especially when applied to diverse urban environments. Only the combined application of empirical and model-based methods provides a comprehensive understanding of the potential of urban greenery to improve air quality. Full article

Urban parks, a type of urban green space, help mitigate environmental pollution and climate change by absorbing and storing atmospheric carbon. Optimizing their carbon-sink capacity requires thoughtful plant community design considering multiple factors. This study analyzed South Korean urban parks using QGIS and i-Tree Eco, integrating satellite imagery with field surveys at both spatial and tree scales. Park spaces were classified into six types based on the biotope criteria established in this study. Random forest regression was applied to each type to identify key variables influencing annual carbon sequestration and storage. The relationship between maturity and sequestration was examined for ten dominant tree species, offering insights for plant selection. Higher tree coverage and more deciduous species were linked to efficiency in carbon sequestration and storage. While variable importance varied slightly across biotope types, tree density was most influential for sequestration, and diameter at breast height and age were key for storage. These findings provide integrated insights into short-term sequestration and long-term storage, as well as strategic directions for structuring plant communities in urban ecosystems. The study offers empirical evidence for designing carbon-efficient urban parks, contributing to sustainable landscape strategies. Full article

Urban forests, as vital components of green infrastructure, provide essential ecosystem services (ESs) that support urban sustainability. However, rapid urban expansion and increased density threaten these forests, creating significant imbalances between the supply and demand for these services. Understanding the characteristics of ecosystem services and reasonably dividing ecological management zones are crucial for promoting sustainable urban development. This study introduces an innovative ecological management zoning framework based on the matching degree and synergies relationships of ESs. Focusing on Fuzhou’s fourth ring road area in China, data from 1038 urban forest sample plots were collected using mobile LIDAR. By integrating the i-Tree Eco model and Kriging interpolation, we assessed the spatial distribution of four key ESs—carbon sequestration, avoided runoff, air purification, and heat mitigation—and analyzed their supply–demand relationships and synergies. Based on these ecological characteristics, we employed unsupervised machine learning classification to identify eight distinct ecological management zones, each accompanied by targeted recommendations. Key findings include the following: (1) ecosystem services of urban forests in Fuzhou exhibit pronounced spatial heterogeneity, with clearly identifiable high-value and low-value areas of significant statistical relevance; (2) heat mitigation, avoided runoff, and air purification services all exhibit synergistic effects, while carbon sequestration shows trade-offs with the other three services in high-value areas, necessitating targeted optimization; (3) eight ecological management zones were identified, each with unique ecological characteristics. This study offers precise spatial insights into Fuzhou’s urban forests, providing a foundation for sustainable ecological management strategies. Full article

Street trees are a representative form of urban green space that play an important role in mitigating the environmental impact of urbanization. Planting the right tree in the right place in urban streetscapes can improve tree health and ecosystem services. Here, we propose a novel approach to selecting appropriate street trees using street type classifications. In the highly urbanized area of Uijeongbu City, South Korea, 221.9 km of streets with 19,717 street trees were classified into 12 types based on road width, aspect ratio, land use, and the presence of power lines. Appropriate tree species were selected for each street type, taking into account tree traits and functions as well as street environments. Then, we analyzed the structure and ecosystem-regulating services of street trees by type, also comparing the services of appropriate and non-appropriate trees. As a result, all 12 street types were identified, but their distribution was uneven. Tree dimension was the key factor in determining appropriate species, and, for the second most common street type, characterized by narrow roads, low aspect ratios, and power lines, only four appropriate species were identified, indicating an urgent need for more options. Additionally, the most dominant species accounted for over 20%, averaging 44% across the 12 street types, further highlighting the necessity of introducing more diverse tree species. Overall, appropriate street trees generally provided higher service efficiency compared to non-appropriate trees across four ecosystem regulating services. These findings emphasize the need for policies and guidelines that promote street tree diversity and enhance the ecological benefits of street trees. This study provides a foundation for developing sustainable street tree management strategies that contribute to healthier and more resilient urban streetscapes. Full article

Urbanization has significantly altered urban landscape patterns, leading to a continuous reduction in the proportion of green spaces. As critical carbon sinks in urban carbon cycles, urban green spaces play an indispensable role in mitigating climate change. This study aims to evaluate the carbon capture and storage potential of urban green spaces in Luohe, China, and identify the landscape factors influencing carbon sequestration. The research combines on-site data collection with high-resolution remote sensing, utilizing the i-Tree Eco model to estimate carbon sequestration rates across areas with varying levels of greenery. The study reveals that the carbon sequestration capacity of urban green spaces in Luohe City is 1.30 t·C·ha⁻¹·yr⁻¹. Among various vegetation indices, the Enhanced Vegetation Index (EVI) explains urban green space carbon sequestration most effectively through an exponential model (R² = 0.65, AIC = 136.5). At the city-wide scale, areas with higher greening rates, better connectivity, and more complex edge morphology exhibit superior carbon sequestration efficiency. The explanatory power of key landscape indices on carbon sequestration is 78% across the study area, with variations of 71.5%, 62%, and 84.9% for low, medium, and high greening rate areas, respectively. Moreover, when greening rates reach a certain threshold, maintaining and optimizing the quality of existing green spaces becomes more critical than simply expanding the green area. These insights provide valuable guidance for urban planners and policymakers on enhancing the ecological functions of urban green spaces during urban development. Full article

Urban green spaces (UGSs) are critical in providing essential ecosystem services (ESs) that enhance the quality of life of urban communities. This study investigated the synergies and trade-offs between structural characteristics of urban trees and their ecosystem services and their implications for urban park management within Yurim Park, Daejeon, South Korea, using the i-Tree Eco tool. The study specifically focused on regulating and supporting services, assessing diversity, air pollution removal, carbon sequestration, and avoiding runoff. A systematic review of urban park management practices complemented the empirical analysis to provide comprehensive management recommendations. The findings of a total of 305 trees from 23 species were assessed, revealing moderate species diversity and significant variations in structural attributes, such as diameter at breast height (DBH), leaf area index (LAI), and crown width (CW). These attributes were found to be strongly correlated with ES outcomes, indicating that healthier and larger trees with extensive canopies are more effective in providing benefits such as pollution removal, runoff reduction, and carbon sequestration. However, the study also identified trade-offs, particularly regarding volatile organic compound (VOC) emissions, which can contribute to ground-level ozone formation despite the trees’ pollution removal capabilities, sensitivity to water stress, requirements for shade and cooling effects, and impacts on water yield. The results highlight the importance of strategic management practices to balance these trade-offs, such as selecting low-emitting species and employing incremental pruning to enhance pollutant removal while minimizing VOC emissions. Additionally, the findings underscore the significance of tree placement and landscape patterns in optimizing year-round benefits, particularly in reducing urban heat island effects and enhancing energy efficiency in adjacent buildings. The study concludes that while urban parks like Yurim Park offer substantial ecological and environmental benefits, continuous monitoring and adaptive management are essential to maximize synergies and mitigate trade-offs. The insights provided on species selection, tree placement, and landscape design offer valuable guidance for urban planners and landscape architects aiming at enhancing the effectiveness of urban parks as nature-based solutions for sustainable urban development. Full article

Cities play a critical role in anthropogenic CO₂ emissions, which exacerbate climate change and impact urban populations. Urban green infrastructure, such as urban trees, provides essential ecosystem services, including reducing atmospheric CO₂ levels. However, there is a significant knowledge gap regarding the impact of urban trees on climate change in semiarid, polluted cities like Tehran, the capital and largest metropolis of the Middle East. This study assesses the carbon sequestration and storage potential of Tehran’s urban infrastructure using the i-Tree Eco model. A randomized cluster sampling method was employed, collecting data on species composition, diameter at breast height (DBH), and total tree height. The results indicate that Tehran’s urban trees sequester approximately 60,102 tons of carbon per year, equivalent to 220,393 tons of CO₂. The net carbon storage in urban trees is about 254,579 tons, equivalent to 933,455 tons of CO₂. Parks and urban green spaces demonstrate the highest rate of carbon sequestration per hectare, followed by urban services land use. Prioritizing the planting of species with high sequestration rates like Cupressus arizonica (Arizona cypress) and Cupressus sempervirens L. var. horizontalis (Mediterranean cypress) could enhance carbon sequestration efforts in Tehran. These data provide valuable insights into the carbon sequestration potential and environmental impact of different land use types, and may aid in the development of effective environmental policies and land management strategies in semiarid urban areas and other cities in similar settings. Full article