i-Tree Eco Model Research Articles

Relationship between Park Composition, Vegetation Characteristics and Cool Island Effect

The Land Surface Temperature (LST) of a park is lower than the surrounding environment, and thus the parkland forms a Park Cool Island (PCI). However, more case studies are needed to reveal the relationship between park composition, vegetation characteristic and PCI development. The LST and Land Use/Land Cover (LULC) of 18 different sized parks in Changzhou, China were obtained from Landsat-8 and Mapworld Changzhou data. Then, a sample investigation method was used to calculate vegetation characteristics of these parks by an i-Tree Eco model. In order to reduce the impact from the external environment on PCI, the Temperature Drop Amplitude (TDA) and Temperature Drop Range (TR) inside the parks were analyzed by ArcGIS 9.3. Impact factors were tested by Pearson correlation analysis and curve fit to reveal the relationship between these factors and PCI formation. The result shows that a park area threshold of 1.34 to 17 hectares provides the best PCI effect, that park shape (perimeter/area), Leaf Area Index (LAI), density, tree cover, water cover, and impervious surface cover have significant correlation with PCI development, vegetation health and global climate change affect the PCI development. Advice is proposed to improve and maintain PCI effects.

Modeling Ecosystem Services for Park Trees: Sensitivity of i-Tree Eco Simulations to Light Exposure and Tree Species Classification

Ecosystem modeling can help decision making regarding planting of urban trees for climate change mitigation and air pollution reduction. Algorithms and models that link the properties of plant functional types, species groups, or single species to their impact on specific ecosystem services have been developed. However, these models require a considerable effort for initialization that is inherently related to uncertainties originating from the high diversity of plant species in urban areas. We therefore suggest a new automated method to be used with the i-Tree Eco model to derive light competition for individual trees and investigate the importance of this property. Since competition depends also on the species, which is difficult to determine from increasingly used remote sensing methodologies, we also investigate the impact of uncertain tree species classification on the ecosystem services by comparing a species-specific inventory determined by field observation with a genus-specific categorization and a model initialization for the dominant deciduous and evergreen species only. Our results show how the simulation of competition affects the determination of carbon sequestration, leaf area, and related ecosystem services and that the proposed method provides a tool for improving estimations. Misclassifications of tree species can lead to large deviations in estimates of ecosystem impacts, particularly concerning biogenic volatile compound emissions. In our test case, monoterpene emissions almost doubled and isoprene emissions decreased to less than 10% when species were estimated to belong only to either two groups instead of being determined by species or genus. It is discussed that this uncertainty of emission estimates propagates further uncertainty in the estimation of potential ozone formation. Overall, we show the importance of using an individual light competition approach and explicitly parameterizing all ecosystem functions at the species-specific level.

A comparison of local and general models of leaf area and biomass of urban trees in USA

Ecosystem service estimation is a very popular topic. Many urban studies use the i-Tree Eco model developed by US Forest Service to estimate ecosystem services. Several ecosystem service estimation studies have been conducted acting upon the assumption that relationships developed elsewhere are applicable to sites that vary in species, site, climate, and environmental conditions. This study tested the accuracy of highly used existing leaf area and biomass models when used outside the region in which it was developed. To do this, we measured 74 urban trees from five species in Stevens Point, Wisconsin collecting data such as diameter at breast height (Dbh), tree height, height to the base of live crown, crown width, crown volume, leaf area, and leaf dry weight biomass. Using the data, we developed two models each to predict leaf area and biomass. Using ten independent samples, we compared our predictions with predictions from the existing models which are also used in i-Tree. Our results indicated that the local models developed in the current study predicted leaf area and biomass better than existing models which had higher prediction error. The difference in prediction will ultimately affect ecosystem services estimation when. using i-Tree, and future studies should acknowledge the difference.

An evaluation of the ecosystem services provided by urban trees: The role of Krasiński Gardens in air quality and human health in Warsaw (Poland)

Abstract Trees remove air pollution by the interception of particulate matter on plant surfaces and the absorption of gaseous pollutants through leaf stomata. However, to date, we have rather few empirical studies on the magnitude and value of the effects of trees on air quality and human health, especially especially within the climatic conditions of Central Europe. To investigate the significance of urban trees from the point of view of air pollution removal, an i-Tree Eco model was implemented. The results indicate that the 932 trees in Krasiński Gardens (Warsaw, Poland) absorb 267.12 kg of pollutants per year: 149.9 kg of O3, 94.4 kg of NO2, 11.8 kg of SO2 and 10.9 kg of PM2.5. That makes an average removal per tree (calculated by summarizing the values of all of the pollutants) of 0.287 kg/year. Furthermore, health values were used to estimate their pollution removal services in monetary terms. The total benefit of air purification by trees in Krasiński Gardens is estimated at 26250 PLN/year with an average value per tree of: 28 PLN. Although PM2.5 removal is the lowest among the four air pollutants analysed, accounting for only 4% of the total mass reduction, it provides 69% of the total economic value. The benefit associated with absorption of O3 provided 28% of the value, with the absorption of NO2 and SO2 at just 3%. The results also show that large tree species (with a crown diameter of 14-15m) can provide around 10 times higher benefits, than small ones (5-6m).

Air pollution removal by trees in public green spaces in Strasbourg city, France

This study integrates i-Tree Eco model in order to estimate air pollution removal by urban trees in Strasbourg city, France. Applied for the first time in a French city, the model shows that public trees, i.e., trees managed by the city, removed about 88t of pollutants during one year period (from July 2012 to June 2013): about 1 ton for CO; 14 tons for NO2; 56 tons for O3; 12 tons for PM10coarse (particles with diameter ranging from 2.5 to 10μm); 5 tons for PM2.5 and 1 ton for SO2. Air pollution removal varied mainly with the tree cover and the level of air pollutants concentrations. Comparison between simulated pollution removal rates and local emissions shows that public trees of Strasbourg reduce about 7% of the emitted PM10coarse in the city’s atmosphere; however, effect on other air pollutants is small. Thus, our study reveals that urban trees are a significant element to reduce air pollution but are not the only solution to this problem. It’s then recommended to associate planting and managing urban forest resources to other strategies that take into account the urban environment characteristics: built structures, street design, location of local sources; etc.

Mapping urban forest structure and function using hyperspectral imagery and lidar data

Cities measure the structure and function of their urban forest resource to optimize forest management and the provision of ecosystem services. Measurements made using plot sampling methods yield useful results including citywide or land-use level estimates of species counts, leaf area, biomass, and air pollution reduction. However, these quantities are statistical estimates made over large areas and thus are not spatially explicit. Maps of forest structure and function at the individual tree crown scale can enhance management decision-making and improve understanding of the spatial distribution of ecosystem services relative to humans and infrastructure. In this research we used hyperspectral imagery and waveform lidar data to directly map urban forest species, leaf area index (LAI), and carbon storage in downtown Santa Barbara, California. We compared these results to estimates produced using field-plot sampling and the i-Tree Eco model. Remote sensing methods generally reduced uncertainty in species-level canopy cover estimates compared to field-plot methods. This was due to high classification accuracy for species with large canopies (e.g., Platanus racemosa with ∼90% average accuracy, Pinus pinea at ∼93%, Quercus agrifolia at ∼83%) and high standard error of the plot-based estimates due to the uneven distribution of canopy throughout the city. Average LAI in canopy, based on lidar measurements was 4.47 while field measurements and allometry resulted in an LAI of 5.57. Citywide carbon storage, based on lidar measurements and allometry was estimated at 50,991 metric tons (t) and 55,900t from plot-sampling. As others have noted, carbon density varied substantially by development intensity based largely on differences in fractional cover but less so when only evaluating canopy biomass. Using separate biomass equations for each leaf type (broadleaf, needleleaf, palm) resulted in a more accurate carbon map but a less accurate citywide estimate.

Isoprene Emission Factors for Subtropical Street Trees for Regional Air Quality Modeling.

Evaluating the environmental benefits and consequences of urban trees supports their sustainable management in cities. Models such as i-Tree Eco enable decision-making by quantifying effects associated with particular tree species. Of specific concern are emissions of biogenic volatile organic compounds, particularly isoprene, that contribute to the formation of photochemical smog and ground level ozone. Few studies have quantified these potential disservices of urban trees, and current models predominantly use emissions data from trees that differ from those in our target region of subtropical Australia. The present study aimed (i) to quantify isoprene emission rates of three tree species that together represent 16% of the inventoried street trees in the target region; (ii) to evaluate outputs of the i-Tree Eco model using species-specific versus currently used, generic isoprene emission rates; and (iii) to evaluate the findings in the context of regional air quality. Isoprene emission rates of (Myrtaceae) and (Proteaceae) were 2.61 and 2.06 µg g dry leaf weight h, respectively, whereas (Sapindaceae) was a nonisoprene emitter. We substituted the generic isoprene emission rates with these three empirical values in i-Tree Eco, resulting in a 182 kg yr (97%) reduction in isoprene emissions, totaling 6284 kg yr when extrapolated to the target region. From these results we conclude that care has to be taken when using generic isoprene emission factors for urban tree models. We recommend that emissions be quantified for commonly planted trees, allowing decision-makers to select tree species with the greatest overall benefit for the urban environment.

The influence of subdivision design and conservation of open space on carbon storage and sequestration

Cities are increasingly trying to offset carbon dioxide emissions and existing and new residential developments, or urban subdivisions, are a major source of such emissions. Compact or clustered subdivision designs have the potential to improve carbon storage and sequestration through the conservation of open space and the preservation of existing trees found on built lots. However, very few empirical studies assess how different subdivision designs and tree preservation strategies affect the carbon footprint of proposed residential developments. Using a 705ha pine plantation that has been approved for the development of 1835 residential units near Gainesville, Florida, our objectives were to determine which site designs and tree preservation strategies could maximize carbon sequestration and storage. From 80 stratified random plots, we measured and analyzed tree and plot characteristics according to forest type and tree stand age categories. Tree data collected from these plots were analyzed with the i-Tree ECO model to estimate baseline predevelopment carbon stores and sequestration rates. Using ArcMap, we then assessed the impact, on baseline carbon sequestration and storage capacity, of several different site designs and tree conservation scenarios for the proposed development. Up to 91% of carbon storage and up to 82% of carbon sequestration could be maintained through a cluster urban development design and by preserving older tree stands. Results indicate that a subdivision's carbon footprint can significantly improve when forest types and tree preservation are incorporated into the design of a development.

Contribution of ecosystem services to air quality and climate change mitigation policies: the case of urban forests in Barcelona, Spain.

Mounting research highlights the contribution of ecosystem services provided by urban forests to quality of life in cities, yet these services are rarely explicitly considered in environmental policy targets. We quantify regulating services provided by urban forests and evaluate their contribution to comply with policy targets of air quality and climate change mitigation in the municipality of Barcelona, Spain. We apply the i-Tree Eco model to quantify in biophysical and monetary terms the ecosystem services “air purification,” “global climate regulation,” and the ecosystem disservice “air pollution” associated with biogenic emissions. Our results show that the contribution of urban forests regulating services to abate pollution is substantial in absolute terms, yet modest when compared to overall city levels of air pollution and GHG emissions. We conclude that in order to be effective, green infrastructure-based efforts to offset urban pollution at the municipal level have to be coordinated with territorial policies at broader spatial scales.

Urban forest structure, ecosystem services and change in Syracuse, NY

The tree population within the City of Syracuse was assessed using a random sampling of plots in 1999, 2001 and 2009 to determine how the population and the ecosystem services these trees provide have changed over time. Ecosystem services and values for carbon sequestration, air pollution removal and changes in building energy use were derived using the i-Tree Eco model. In addition, photo interpretation of aerial images was used to determine changes in tree cover between the mid-1990s and 2009. Between the mid-1990s and 2003, tree cover in Syracuse exhibited a decline from 27.5 to 25.9 %, but subsequently increased to 26.9 % by 2009. The total tree population exhibited a similar pattern, dropping from 881,000 trees in 1999 to 862,000 in 2001, and then increasing to 1,087,000 trees in 2009. Most of this increase in the urban tree population is due to invasive or pioneer trees species, particularly Rhamnus cathartica, which has more than tripled in population between 2001 and 2009. Insects such as gypsy moth and emerald ash borer pose a substantial risk to altering future urban forest composition. The annual ecosystem services provided by the urban forest in relation to carbon sequestration, air pollution removal and reduction in building energy use are estimated at about $2.4 million per year. An improved understanding of urban forests and how they are changing can facilitate better management plans to sustain ecosystem services and desired forest structure for future generations.