354 Nowak et al.: Assessing Urban Forest Structure and Ecosystem Services factors from local ISA chapters and somewhat outdated values (from late 1990s to early 2000s). In addition, the condition and location factors used are not directly from the methods in the last CTLA guidelines, but rather the model uses dieback as a proxy for condition and land use as a proxy for location. Thus, the actual individual tree estimates can be unreliable, because the model uses average land use values; but across the population, the model should produce accurate estimates of total structural value. With regard to pest potentials, only a few pests currently exist in the model, but the model has the capability to add other pests as host-preference data are obtained. The model only estimates potential maximum pest damage. Actual damage is likely to be much less than the potential for some pests or maximum damage may not be reached for several years or at all depending on local management activities and random factors. Biogenic Emissions Biogenic VOC emissions follow the protocols developed within the Biogenic Emissions Inventory System of the National Oce- anic and Atmospheric Administration/U.S. Environmental Pro- tection Agency (2008). The model produces results that are within range of biogenic VOC emission studies (e.g., Kinnee et al. 1997) and has the advantage of using local urban tree leaf biomass and weather data. The biogenic VOC model was devel- oped in the early 2000s and may need to be updated based on the latest biogenic VOC modeling procedures (e.g., National Center for Atmospheric Research 2008). Carbon Storage and Sequestration The main advantage of the carbon estimation in UFORE is that it is based on a statistical sample of trees within an urban area and statistically estimates diameter distribution by species. The modeled carbon values are estimates based on forest-derived allometric equations. The carbon estimates yield a standard error of the estimate based on sampling error rather than error of estimation. Estimation error is unknown and likely larger than the reported sampling error. Estimation error includes the uncer- tainty of using biomass equations and conversion factors, which may be large, as well as measurement error, which is typically very small. The standardized carbon values (e.g., kg C/ha or lbs C/ac of tree cover) produced by UFORE fall within the range of other field studies of forest carbon (Nowak and Crane 2002). However, there are various means to help improve the carbon storage and sequestration estimates for urban trees. Carbon es- timates for open-grown urban trees are adjusted downward based on field measurements of trees in the Chicago area (Nowak 1994c). This adjustment may lead to conservative estimates of carbon. More research is needed on the applicability of forest- derived equations to urban trees. In addition, more urban tree growth data are needed to better understand regional variability of urban tree growth under differing site conditions (e.g., tree competition) for better annual sequestration estimates. Average regional growth estimates are used based on limited measured urban tree growth data standardized to length of growing season and crown competition. Street tree growth data collected as part of i-Tree’s STRATUM model will provide for better growth modeling in the near future. There are currently limited biomass equations for palm trees or tropical trees in UFORE. The model needs to be updated with ©2008 International Society of Arboriculture tropical tree biomass equations for more accurate estimates in tropical cities. Also, future research is needed to obtain biomass equations for urban or ornamental tree species. Tree decay is not accounted for in the carbon estimates, which may lead to an overestimate of carbon storage. A better understanding of the magnitude of decay in urban trees is needed. Air Pollution Removal The pollution removal module is designed to use standardized local weather and air pollution data in conjunction with field data measures to estimate pollution removal. The weather data are available across the globe in a standardized format from the National Climatic Data Center (2008). The pollution data are also readily available for the United States in a standardized format from the U.S. Environmental Protection Agency (2008). For analyses outside of the United States, local hourly pollution data need to be attained from local agencies and formatted to fit the UFORE input data structure. For analyses within the United States, users only need to supply local field data to operate the model. The model uses a gas-exchange dry deposition model initially developed by the Oak Ridge National Laboratory (Baldocchi et al. 1987; Baldocchi 1988) to estimate hourly removal of NO2, SO2, and O3. For CO or PM10 removal, the model uses average deposition velocities from the literature in conjunction with local hourly pollution concentration and field data. The UFORE mod- el’s hourly pollution removal estimates are within bounds of field measurements of dry deposition velocities and follow daily gas exchange patterns (e.g., Lovett 1994). Methods to estimate the effects on PM2.5 are currently being developed for UFORE, but pollution removal of PM2.5 by trees is small in terms of magnitude of removal (T. Whitlow Cornell University, pers. comm., 2008). Building Energy Effects The base energy effect tables used are based on computer models of building energy use across the United States for various tree configurations (McPherson and Simpson 1999). The model pro- duces estimates of tree effects at the local municipal scale based on state averages. Improved estimates of energy use could be made by modeling actual building types found in the field samples, but the cost and practicality of this type of local analy- sis limits this approach in energy modeling. Updated energy tables of types of energy use in buildings (e.g., electricity versus gas or oil) and possibly more locally based tables (e.g., county scale) would aid in improving estimates of energy effects by trees. Unfortunately, this type of local data is not currently avail- able in a national database. Cost estimates are based on average 2002 state average costs but are currently being updated to 2007 values (latest costs avail- able nationally). Because the model is geared toward U.S. cli- mate and building types, this module is not appropriate for use outside of the United States, except for possibly in southern Canada. The model is currently being rewritten in C++ to allow for seamless integration within i-Tree. Currently, users collect and enter data, which are sent to the Forest Service for processing and results typically returned to the user within 3 to 4 weeks. Once the user receives the results file, they can produce numer- ous standard tables and graphs, print an automated report, and/or
November 2008
Title Name |
Pages |
Delete |
Url |
Empty |
Search Text Block
Page #page_num
#doc_title
Hi $receivername|$receiveremail,
$sendername|$senderemail wrote these comments for you:
$message
$sendername|$senderemail would like for you to view the following digital edition.
Please click on the page below to be directed to the digital edition:
$thumbnail$pagenum
$link$pagenum
Your form submission was a success. You will be contacted by Washington Gas with follow-up information regarding your request.
This process might take longer please wait