Grantee Research Project Results
2006 Progress Report: Investigation of the Interactions between Climate Change, Biomass, Forest Fires, and Air Quality with an Integrated Modeling Approach
EPA Grant Number: R832277Title: Investigation of the Interactions between Climate Change, Biomass, Forest Fires, and Air Quality with an Integrated Modeling Approach
Investigators: Shankar, Uma , Fox, Douglas G. , Baek, Bok Haeng , Binkowski, Francis S. , Xiu, Aijun , McKenzie, Donald , Prestemon, Jeff , Ran, Limei , Arunachalam, Sarav , McNulty, Steve
Current Investigators: Shankar, Uma , Hanna, Adel , Fox, Douglas G. , Binkowski, Francis S. , Xiu, Aijun , Holland, Andy , Seppanen, Catherine , Vukovich, Jeff , McNulty, Steve
Institution: University of North Carolina at Chapel Hill , Texas Agricultural Experiment Station , USDA , Colorado State University
Current Institution: University of North Carolina at Chapel Hill , USDA
EPA Project Officer: Chung, Serena
Project Period: March 13, 2005 through March 12, 2008 (Extended to March 12, 2009)
Project Period Covered by this Report: March 13, 2006 through March 12, 2007
Project Amount: $726,566
RFA: Fire, Climate, and Air Quality (2004) RFA Text | Recipients Lists
Research Category: Climate Change , Air Quality and Air Toxics , Air
Objective:
Forest fires not only change landscapes and destroy property, but also emit trace gases and aerosols (e.g., CO, CH4, NOx, and black carbon) that affect regional and global air quality, with consequences for human health and climate through their interactions with solar radiation. These impacts can be felt over long distances due to the long-range transport of these pollutants, both as primarily emitted species and as precursors for other pollutants formed in the atmosphere through photochemical reactions. Recently, the increased frequency of large fires in the United States has been thought to be associated with short-term changes in climate variables, such as precipitation and temperature, that have exacerbated the conditions for fire occurrence. Thus, the overall goal of this research is to assess the impact of climate change and variability on biomass and forest fires, the impact of the evolving emissions from forest fires on ozone and particulate matter (PM) air quality, and the regional climate response to air quality changes in the Southern United States using an integrated modeling system. Integration of some of these feedbacks in the model simulations will allow a more realistic representation of future-year emissions, from both biogenic and fire sources, and their impact on air quality. This will facilitate assessment of the air quality and ecosystem benefits of various fire management scenarios that are currently not included in most emissions control evaluations.
The primary objectives in support of the overall goal are to:
- investigate the impacts of climate change on vegetative cover and fuel characteristics, the consequences for fire frequency and intensity, and feedbacks to biomass load and biogenic emissions under managed and wildfire scenarios;
- examine changes in regional air quality due to the evolution of anthropogenic and biogenic emissions in response to various fire scenarios; and
- investigate the feedback of air quality changes to regional climate variables.
Progress Summary:
This project is a collaboration among researchers at the University of North Carolina (UNC); Dr. Douglas Fox, a private consultant and fire modeling expert; and researchers at the U.S. Forest Service (USFS) Southern Global Change Program (SGCP), led by Dr.Steven McNulty. Within the last year, Dr. Donald McKenzie from the USFS Pacific Wildland Fire Sciences Laboratory and Dr. Jeffrey Prestemon from the USFS Southern Research Station have been active consultants on the project, providing guidance and assisting in the modeling of future-year fires and accounting for fire ignitions that are human-induced, as frequently occurs in the Southeastern United States (Mercer and Prestemon, 2005). The modeling system for the studies listed in the project objectives is shown in Figure 1. Research in the second year of the project focused on three key areas of development and implementation within this system: the forest growth model, PnET (Aber, et al., 1997); the fire emissions model, BlueSky emissions model (BlueSky-EM) (Sestak, et al., 2002); and development of data linkages to the Fire Scenario Builder (FSB), a stochastic model for predicting fire area burned, developed by Dr. McKenzie and co-workers (McKenzie, et al., 2006).
Figure 1. Schematic of the Current Modeling System. Modifications to the original concept include replacement of the BEIS3 biogenic emissions model with the Model of the Emissions of Gases and Aerosols from Nature (MEGAN), developed by the National Center for Atmospheric Research (NCAR).
Forest Process Modeling
In the second year of the project, there was a thorough reevaluation of the daily PnET version investigated in the first year for application to a large region such as the Southeast. Several vegetation and site-specific inputs are required to simulate plot-level forest growth besides climate parameters (monthly mean minimum and maximum temperature, monthly precipitation, and photosynthetically active radiation). Plot-level data are then expanded to the county level using expansion factors compiled by the USFS for the various vegetation types. The input data requirements to model daily forest growth over the regional domain made it unfeasible to use the daily version, despite the computational efficiency, and the switch was made to the original Visual Basic version of the model. Input data were collected for the base year for the 13 states shown in Figure 2 from the Forest Inventory Analysis (FIA) databases in Knoxville, Tennessee, with assistance from FIA personnel. In initial testing of PnET, the remainder of the climate data required for the historic period of simulation (1990–2000) posed a challenge due to errors in key climate inputs (monthly mean precipitation) in the National Centers for Environmental Prediction Reanalysis data used for this purpose. It was thus decided that the historic data used in previous model applications by SGCP would be used along with the Hadley climate system model output to drive PnET in these tests, as it would also facilitate QA of the output against SGCP’s archived outputs for reasonable performance.
Figure 2. Modeling Domain for the PnET Forest Growth Model Application
Fire Emissions Modeling
In this project period, work began on the data linkages from the forest growth model to the BlueSky-EM smoke emissions model to provide future-year fuel loads. This was the main topic of discussion during a symposium and workshop, organized by UNC on September 7–8, 2006, involving presentations and discussions led by consultants from the USFS. Presentations from the symposium are available on the project Web site cited in Section 3.4. Dr. McKenzie provided an approach for developing correlations between the live biomass predicted by PnET and the downed dead wood (fire fuel) required by BlueSky. The correlation is based upon a multivariate regression analysis of the FIA plot data of live biomass versus dead wood in the 13 states shown in Figure 2, and include temperature, precipitation, and total mean solar radiation reaching the ground as variables for the regression. The current-year fire inventory developed for the Regional Planning organizations would permit an evaluation of this approach. The FSB has been directly linked to the Fuel Characteristic Classification System (FCCS) and BlueSky, and tested over the Northwest for the 2003 season. A schematic of the FSB and its inputs is shown in Figure 3.
Figure 3. Schematic of the FSB using Lightning or Human Ignition. Base GIS layers provide mean fire frequency and fire area burned for each cell. Flammability is based on fuel moisture calculations from the National Fire Danger Rating System (NFDRS) and output from the mesoscale model (MM5).
The development of output from the FSB for providing fire activity data to BlueSky-EM for the base and future years is underway; it uses lightning as the ignition mechanism to stochastically model future fires in the Western United States. Data for area burned per day for the period 2045–2050 were obtained from Dr. McKenzie and tested in BlueSky-EM for the years 2045 and 2050. The FSB is currently being enhanced to incorporate both lightning and human ignition probabilities for the nested domain over the eastern United States, shown in Figure 3. The human ignition probabilities in future years will be based upon gridded projection factors developed by Drs. Prestemon and Mercer from the population and economics growth database provided by Woods & Poole Economics, Inc. for future years, and from fire activity statistics obtained for the base year (2002) from the National Fire and Aviation Management Web Applications database (see http://fam.nwcg.gov/fam-web/ Exit ).
Air Quality Modeling Activities
Under a previous STAR grant, UNC investigators have developed an air quality modeling system with integrated meteorology and chemistry (METCHEM) as a modular, physically and numerically consistent, fully integrated regional-scale atmospheric dynamics and chemistry modeling system. It is based on further development and refinement of three existing models: the MM5, the Multiscale Air Quality Simulation Platform (MAQSIP) (Mathur, et al., 2005), and the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. The integrated modeling framework enables investigation of the feedbacks of radiatively important trace species to the atmospheric dynamics. METCHEM applications over the eastern United States have been able to capture the increase in optical depth due to the presence of aerosols, resulting in a reduction in the shortwave radiation reaching the ground, and consequently, in the surface temperature and the planetary boundary layer (PBL) height.
Two 6-week simulation periods in summer and fall, respectively representing the seasons for catastrophic wild fires and prescribed burns in 2002, 2015, 2030, and 2050, were identified in Year 1 of the project. In Year 2, we have completed the emissions processing for a 6-week summer period in the outer modeling domain at a 36-km grid resolution over the continental United States (CONUS) shown in Figure 4, using emissions processed by SMOKE for wildfires, along with other inventoried emissions for 2002 (the base year). Work is underway for processing emissions from nonfire sources for the southeastern United States At a 12-km resolution; these will be merged with fire emissions for input to METCHEM. The 36-km resolution data for emissions were processed from the fire inventory currently used for CONUS simulations by the Regional Planning Organizations, rather than using the full suite of models in our system. This step was necessitated by the following factors: (1) The resource requirements to prepare meteorological inputs for all the ecoprovinces in the CONUS to calculate the lightning ignition probability for the FSB are prohibitive. (2) Fuel data for Canada and Mexico are highly uncertain. (3) Forest inventory inputs, currently obtained from the FIA system database for the southern United States, are not yet available with comparable quality for the rest of the country; therefore, the CONUS simulation would also not include PnET output. Thus, the CONUS simulation is a best estimate simulation in each of the selected years that would provide boundary conditions, including the effects of large western U.S. fires, to a nested southern U.S. domain, shown in Figure 4, over which PnET has been extensively evaluated, and which would include PnET results. Future-year simulations will consider the Intergovernmental Panel on Climate Change (IPCC) scenarios (Business-as-Usual and CO2 mitigation policy) in the Community Climate System Model (CCSM) initial and boundary inputs to METCHEM.
Figure 4. METCHEM Simulation Domains; Domain D02 Will Include the Impacts of PnET-Predicted Biomass Changes on the Fire Emissions Inputs.
References:
Aber JD, Ollinger SV, Driscoll CT. Modeling nitrogen deposition in forest ecosystems in response to land use and atmospheric deposition. Ecological Modelling 1997;101:61-78. http://www.pnet.sr.unh.edu/onlinepubs/EcoMod-v101-p61.html Exit .
Mathur R, Shankar U, Hanna AF, Odman MT, et al. Multiscale air quality simulation platform (MAQSIP): Initial applications and performance for tropospheric ozone and particulate matter, Journal of Geophysical Research 2005;110:D13308, doi:10.1029/2004JD004918.
McKenzie DM, O’Neill SM, Larkin NK, Norheim RA. Integrating models to predict regional haze from wildland fire. Ecological Modelling 2006;199, doi:10.1016/j.ecolmodel.2006.05.029.
Mercer DE, Prestemon JP. Comparing production function models for wildfire risk analysis in the wildland–urban interface. Forest Policy Economics 2005;7:782-795.
Sestak M, O’Neill S, Ferguson S, Ching J, Fox D. Integration of wildfire emissions into models-3/CMAQ with the prototypes community smoke emissions modeling system (CSEM) and BlueSky. In: Proceedings of the Second Annual CMAS Workshop,October 21-23, 2002, Research Triangle Park, NC. http://www.cmascenter.org/conference/2002/session5/fox_abstract.pdf Exit .
Future Activities:
In the 3rd year of the project period, the main objective will be completion of the remaining modeling tasks to examine the fire emissions impacts on air quality under various fire scenarios (wild fires only vs. National Fire Management Plan). The project tasks will focus on the following areas:
- Link PnET model output to MEGAN to reflect changes in biogenic emissions resulting from biomass changes.
- Reflect changes due to fires in the MEGAN land cover data.
- Complete the FSB linkages to population-growth and economics-based projection factors for human-induced ignitions.
- Perform simulations for the continental United States at 36-km, nesting down to the Southeastern United States at 12-km for two seasonally representative 6-week periods in 2002.
- Evaluate the 2002 simulations against available observations.
- Complete future-year (2015, 2030, and 2050) METCHEM simulations for the wild fire season and examine trends of aerosol properties.
- Compare 2015 METCHEM simulations between wild fires only and the full implementation of the National Fire Management Plan.
- Prepare annual project report.
Journal Articles:
No journal articles submitted with this report: View all 21 publications for this projectSupplemental Keywords:
forest biomass, fire emissions, land cover changes, air quality climate feedbacks,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, Chemistry, climate change, Air Pollution Effects, Monitoring/Modeling, Environmental Monitoring, Ecological Risk Assessment, Atmosphere, Community Smoke Emissions Model, anthropogenic stress, environmental measurement, meteorology, climatic influence, global ciruclation model, global change, ozone depletion, air quality model, biomass, climate models, terrestial ecosystem model, environmental stress, coastal ecosystems, ecological models, climate model, forest resources, Global Climate Change, atmospheric chemistry, climate variabilityRelevant Websites:
http://www.ie.unc.edu/cempd/projects/FIRE/ Exit
http://www.ie.unc.edu/cempd/projects/FIRE/documents.cfm Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.