Exploring the Spatial Pattern of Urban Forest Ecosystem Services based on i-Tree Eco and Spatial Interpolation: A Case Study of Kyoto City, Japan.

Urban forest, as an essential urban green infrastructure, is critical in providing ecosystem services to cities. To enhance the mainstreaming of ecosystem services in urban planning, it is necessary to explore the spatial pattern of urban forest ecosystem services in cities. This study provides a workflow for urban forest planning based on field investigation, i-Tree Eco, and geostatistical interpolation. Firstly, trees across an array of land use types were investigated using a sampling method. Then i-Tree Eco was applied to quantify ecosystem services and ecosystem service value in each plot. Based on the ecosystem services estimates for plots, four interpolation methods were applied and compared by cross-validation. The Empirical Bayesian Kriging was determined as the best interpolation method with higher prediction accuracy. With the results of Empirical Bayesian Kriging, this study compared urban forest ecosystem services and ecosystem service value across land use types. The spatial correlations between ecosystem service value and four types of point of interest in urban places were explored using the bivariate Moran's I statistic and the bivariate local indicators of spatial association. Our results show that the residential area in the built-up area of Kyoto city had higher species richness, tree density, ecosystem services, and total ecosystem service value. Positive spatial correlations were found between ecosystem service value and the distribution of urban space types including the tourist attraction distribution, urban park distribution, and school distribution. This study provides a specific ecosystem service-oriented reference for urban forest planning based on land use and urban space types.

Variation in estimates of heat-related mortality reduction due to tree cover in U.S. cities.

Heat-related mortality is one of the leading causes of weather-related deaths in the United States. With changing climates and an aging population, effective adaptive strategies to address public health and environmental justice issues associated with extreme heat will be increasingly important. One effective adaptive strategy for reducing heat-related mortality is increasing tree cover. Designing such a strategy requires decision-support tools that provide spatial and temporal information about impacts. We apply such a tool to estimate spatially and temporally explicit reductions in temperature and mortality associated with a 10% increase in tree cover in 10 U.S. cities with varying climatic, demographic, and land cover conditions. Two heat metrics were applied to represent tree impacts on moderately and extremely hot days (relative to historical conditions). Increasing tree cover by 10% reduced estimated heat-related mortality in cities significantly, with total impacts generally greatest in the most populated cities. Mortality reductions vary widely across cities, ranging from approximately 50 fewer deaths in Salt Lake City to about 3800 fewer deaths in New York City. This variation is due to differences in demographics, land cover, and local climatic conditions. In terms of per capita estimated impacts, hotter and drier cities experience higher percentage reductions in mortality due to increased tree cover across the season. Phoenix potentially benefits the most from increased tree cover, with an estimated 22% reduction in mortality from baseline levels. In cooler cities such as Minneapolis, trees can reduce mortality significantly on days that are extremely hot relative to historical conditions and therefore help mitigate impacts during heat wave conditions. Recent studies project highest increases in heat-related mortality in the cooler cities, so our findings have important implications for adaptation planning. Our estimated spatial and temporal distributions of mortality reductions for each city provide crucial information needed for promoting environmental justice and equity. More broadly, the methods and model can be applied by both urban planners and the public health community for designing targeted, effective policies to reduce heat-related mortality. Additionally, land use managers can use this information to optimize tree plantings. Public stakeholders can also use these impact estimates for advocacy.

The effectiveness of urban trees in reducing airborne particulate matter by dry deposition in Tehran, Iran.

Deposition of atmospheric pollution as particulate matter (PM) has become a serious issue in many urban areas. This study measured and estimated the amount of atmospheric PM deposition onto oriental plane (Platanus orientalis L.) trees located in Tehran Megapolis, Iran. PM deposited on the leaves of urban trees during spring and summer was estimated using leaf wash measurements. In addition to direct measurements, the dry deposition velocity and the yearly whole-tree PM deposition were estimated using both field measurements and a theoretical model of deposition flux. We estimated air quality improvement as a result of the trees at respiratory height (1.5 m), tree height (10 m), and boundary layer height (1719 m). Foliar PM deposition during spring and summer was estimated to average 0.05 g/leaf and 41.39 g/tree using direct measurements. The annual PM deposited on the leaves, trunk, and branches of an average urban tree was calculated to be 78.60 g/tree. Trees were estimated to improve air quality at 1.5 m, 10 m, and 1719 m from ground level by 25.8%, 5.8%, and 0.1%, respectively. Hence, oriental plane trees substantially reduce PM at respiratory height.

Nature-Based Solutions Can Compete with Technology for Mitigating Air Emissions Across the United States.

Despite the proliferation of control technologies, air pollution remains a major concern across the United States, suggesting the need for a paradigm shift in methods for mitigating emissions. Based on data about annual emissions in U.S. counties and current land cover, we show that existing forest, grassland, and shrubland vegetation take up a significant portion of current U.S. emissions. Restoring land cover, where possible, to county-level average canopy cover can further remove pollution of SO2, PM10, PM2.5, and NO2 by an average of 27% through interception of particulate matter and absorption of gaseous pollutants. We find such nature-based solutions to be cheaper than technology for several National Emission Inventory sectors. Our results with and without monetary valuation of ecological cobenefits identify sectors and counties that are most economically attractive for nature-based solutions as compared to the use of pollution control technologies. We also estimate the sizes of urban and rural populations that would benefit from this novel ecosystem-based approach. This suggests that even though vegetation cannot fully negate the impact of emissions at all times, policies encouraging ecosystems as control measures in addition to technological solutions may promote large investments in ecological restoration and provide several societal benefits.

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.

Testing ecosystem accounting in the United States: A case study for the Southeast.

Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S. We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a ten-state region in the Southeast. The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015. Results illustrate how information from ecosystem accounts can contribute to policy and decision-making. Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area's environmental-economic trends. The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries. Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.

Comprehensive national database of tree effects on air quality and human health in the United States.

Trees remove air pollutants through dry deposition processes depending upon forest structure, meteorology, and air quality that vary across space and time. Employing nationally available forest, weather, air pollution and human population data for 2010, computer simulations were performed for deciduous and evergreen trees with varying leaf area index for rural and urban areas in every county in the conterminous United States. The results populated a national database of annual air pollutant removal, concentration changes, and reductions in adverse health incidences and costs for NO2, O3, PM2.5 and SO2. The developed database enabled a first order approximation of air quality and associated human health benefits provided by trees with any forest configurations anywhere in the conterminous United States over time. Comprehensive national database of tree effects on air quality and human health in the United States was developed.

Tree and forest effects on air quality and human health in the United States.

Trees remove air pollution by the interception of particulate matter on plant surfaces and the absorption of gaseous pollutants through the leaf stomata. However, the magnitude and value of the effects of trees and forests on air quality and human health across the United States remains unknown. Computer simulations with local environmental data reveal that trees and forests in the conterminous United States removed 17.4 million tonnes (t) of air pollution in 2010 (range: 9.0-23.2 million t), with human health effects valued at 6.8 billion U.S. dollars (range: $1.5-13.0 billion). This pollution removal equated to an average air quality improvement of less than one percent. Most of the pollution removal occurred in rural areas, while most of the health impacts and values were within urban areas. Health impacts included the avoidance of more than 850 incidences of human mortality and 670,000 incidences of acute respiratory symptoms.

Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects.

Urban particulate air pollution is a serious health issue. Trees within cities can remove fine particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM2.5 removed annually by trees varied from 4.7 tonnes in Syracuse to 64.5 tonnes in Atlanta, with annual values varying from $1.1 million in Syracuse to $60.1 million in New York City. Most of these values were from the effects of reducing human mortality. Mortality reductions were typically around 1 person yr(-1) per city, but were as high as 7.6 people yr(-1) in New York City. Average annual percent air quality improvement ranged between 0.05% in San Francisco and 0.24% in Atlanta. Understanding the impact of urban trees on air quality can lead to improved urban forest management strategies to sustain human health in cities.

Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system.

A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature and LAI fields, and CMAQ provided NO2 concentrations. A base case simulation was conducted using built-in distributed i-Tree Eco tools, and simulations using different inputs were compared against this base case. Differences in land cover classification and tree cover between the distributed i-Tree Eco and WRF resulted in changes in estimated LAI, which in turn resulted in variations in simulated NO2 dry deposition. Estimated NO2 removal decreased when CMAQ-derived concentration was applied to the distributed i-Tree Eco simulation. Discrepancies in temperature inputs did little to affect estimates of NO2 removal by dry deposition to trees in Baltimore.

Development of a distributed air pollutant dry deposition modeling framework.

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD.

How to select the best tree planting locations to enhance air pollution removal in the MillionTreesNYC initiative.

Highest priority zones for tree planting within New York City were selected by using a planting priority index developed combining three main indicators: pollution concentration, population density and low canopy cover. This new tree population was projected through time to estimate potential air quality and carbon benefits. Those trees will likely remove more than 10,000 tons of air pollutants and a maximum of 1500 tons of carbon over the next 100 years given a 4% annual mortality rate. Cumulative carbon storage will be reduced through time as carbon loss through tree mortality outweighs carbon accumulation through tree growth. Model projections are strongly affected by mortality rate whose uncertainties limit estimations accuracy. Increasing mortality rate from 4 to 8% per year produce a significant decrease in the total pollution removal over a 100 year period from 11 000 tons to 3000 tons.

Long-term results of endopyeloureterotomy using the transpelvic extraureteral approach.

OBJECTIVES: To review our clinical results to confirm the long-term efficacy of the operative technique of endopyeloureterotomy using the transpelvic extraureteral approach that we developed. METHODS: We treated 123 patients with ureteropelvic junction obstruction or upper ureteral stenosis by percutaneous endopyeloureterotomy using the transpelvic extraureteral approach between 1988 and 1999. All were followed up for at least 1 year (mean 58 months). Sixty-eight patients were male and 55 female between the ages of 3 and 78 years (mean 36). We evaluated the efficacy of our procedure preoperatively and then regularly every 6 to 12 months postoperatively using excretory urography and technetium-99m DTPA renography. RESULTS: Our results showed that 115 (90.6%) of 127 procedures relieved the obstruction without any severe complications. In the 107 cases of ureteropelvic junction obstruction, we alleviated the stricture in 96 (90%). In the 20 cases of upper ureteral stenosis, our procedure alleviated the stricture in 19 (95%). In the 47 cases of a stenotic segment of 2 cm or more in length, 43 of our procedures led to a significant improvement (91.5%). Long-term follow-up of the 123 patients revealed late recurrence in 5 patients, despite the initial success. CONCLUSIONS: Percutaneous endopyeloureterotomy using the transpelvic extraureteral approach should be considered the first choice of treatment for ureteropelvic junction obstruction and upper third ureteral stenosis, even if the stenotic segment is 2 or more cm long.