Grantee Research Project Results
2006 Progress Report: Impacts of Climate Change and Land Cover Change on Biogenic Volatile Organic Compounds (BVOCs) Emissions in Texas
EPA Grant Number: R831452Title: Impacts of Climate Change and Land Cover Change on Biogenic Volatile Organic Compounds (BVOCs) Emissions in Texas
Investigators: Yang, Zong-Liang , Parmenter, Barbara , Allen, David T.
Institution: The University of Texas at Austin
EPA Project Officer: Chung, Serena
Project Period: November 1, 2003 through October 31, 2006 (Extended to October 31, 2007)
Project Period Covered by this Report: November 1, 2005 through October 31, 2006
Project Amount: $750,000
RFA: Consequences of Global Change for Air Quality: Spatial Patterns in Air Pollution Emissions (2003) RFA Text | Recipients Lists
Research Category: Air , Air Quality and Air Toxics , Climate Change
Objective:
The overall goal of the project is to couple climate models, biogenic emission estimation models, air quality models, and anthropogenic land use models to predict future air quality trends.
Progress Summary:
Our work during 2006 focused on the following three issues.
- Using a land-surface modeling (CLM) augmented with a short-term dynamic phenology scheme to estimate the interannual variation in the emission of biogenic volatile organic compounds (BVOCs) on a regional scale.
- Using a regional air quality model (CAMx) to evaluate the impact of climate-induced changes in land cover on air quality (specifically, ozone concentrations).
- Assessing different approaches of dynamical regional climate downscaling using an advanced Weather Research and Forecasting (WRF) model.
The aims of the project have not changed from the original application.
Detailed descriptions of results so far follow.
1. Using a Land-Surface Modeling (CLM) Augmented With a Short-Term Dynamic Phenology Scheme to Estimate the Interannual Variation in the Emission of Biogenic Volatile Organic Compounds (BVOCs) on a Regional Scale
We use North American Regional Reanalysis data to drive two versions of the National Center for Atmospheric Research Community Land Model (CLM) on a 0.1° grid over eastern Texas. The first version is the standard CLM with prescribed leaf area index (LAI) (i.e., LAI varies seasonally but not interannually); the second version is the standard CLM augmented with a dynamic phenology scheme (CLM-DP) that allows LAI to respond to environmental variation. We calibrate CLM-DP using satellite-derived LAI as our visual constraint.
When phenology is prescribed, the domain-mean (domain-maximum) average absolute departure from the monthly mean BVOC flux is 11.7% (70.6%); when phenology is allowed to vary with environmental conditions, it is 22.4% (137.7%). The domain-mean (domain-maximum) average absolute departure from the monthly mean flux is lower during summer: using CLM-DP, it is 15.7% (35.3%); using the standard CLM, it is 7.0% (23.0%). The domain-average, mean-normalized standard deviation of the JJA mean BVOC flux is 0.0619 when LAI is prescribed and 0.183 when LAI varies with environmental conditions.
Our results imply that interannual variation of leaf-biomass density, which is primarily driven by interannual variability of precipitation, is a significant contributor to year-to-year differences in BVOC flux on a regional scale, of at least equal importance to interannual variation of temperature and shortwave radiation. Phenology-driven biogenic emission variability is most pronounced in regions with relatively low emissions: as a grid cell’s mean BVOC flux decreases, the mean-normalized standard deviation of BVOC flux tends to increase. BVOC flux is most variable between years in sub-humid, sparsely wooded regions where interannual variability of precipitation is relatively large.
What This Means for the EPA. On a regional scale, interannual variation in BVOC flux is considerable and likely overwhelms any differences in BVOC flux due to longer-term climate change. The assumption that BVOC flux is constant year-to-year should be re-examined.
2. Using a Regional Air Quality Model (CAMx) To Evaluate the Impact of Climate-Induced Changes in Land Cover on Air Quality (Specifically, Ozone Concentrations)
We have completed an evaluation of the impacts of climate-induced changes in land cover and urbanization on air quality, using Texas as a case study. Building on initial work done in 2005, monthly biogenic emissions were determined for the twenty year period, 1985–2004. Concentrations of air pollutants were predicted using the Comprehensive Air Quality Model (CAMx). Modeling episodes were chosen to focus on two specific areas, Austin and Houston.
Results show that the changes in biogenic emissions due to interannual variability in climate led to changes in maximum ozone concentrations. Maximum changes in daily ozone concentrations, due to increases in biogenic emissions associated with interannual variability, ranged from +40 to -6 ppb for the East Texas area and +31 to -1 ppb for the Houston area. With other factors remaining unchanged, changes in biomass due to changes in climate resulted in impacts of +22 to -20 ppb relative to 1999 levels, +40 to -6 ppb relative to 2000 levels on ozone concentrations in Texas. These changes are much greater in magnitude to changes due to urbanization.
What This Means for the EPA. These results are comparable to many commonly employed control strategies.
3. Assessing Different Approaches of Dynamical Regional Climate Downscaling Using an Advanced Weather Research and Forecasting (WRF) Model
To evaluate the capability of dynamical climate downscaling for future climate projection, the Weather Research and Forecasting model (WRF) has been used to simulate the regional climate over North America during 2000–2004 with fine resolution (36 km). The initial conditions and boundary conditions of WRF are provided by the NCAR Community Climate System Model version 3 (CCSM3) at T85 resolution. Two integration approaches are studied: (1) A long-term 5-year continuous integration. (2) Consecutive short-term weekly reinitialized integrations whose total integration time spans 5 years. The WRF regional climate downscaling significantly improves the CCSM3 simulation of 2-m temperature and precipitation, especially over mountainous and coastal regions, capturing both the regional variations and seasonal evolutions. The result points out the potential drawback of the long term integration. The accumulation of the internal errors in the WRF model causes the domain-wide cooling trend over the integration period and causes systematic underprediction of the 2-m air temperature. The short-term reinitialized integration should be considered as an alternative method to the long-term integration in regional climate modeling studies.
What This Means for the EPA. These results would be important for quantifying the uncertainty in the future climate projection on a regional scale.
Future Activities:
Future activities will be focused on quantifying the contributions to future near-ground ozone changes (2051-2053 compared with 2001-2003) in Texas from 1) climate change, 2) biogenic emissions associated with vegetation phenology change, and 3) biogenic emissions associated with land cover change.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 22 publications | 5 publications in selected types | All 5 journal articles |
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Type | Citation | ||
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Gulden LE, Yang Z-L. Development of species-based, regional emission capacities for simulation of biogenic volatile organic compound emissions in land-surface models: an example from Texas, USA. Atmospheric Environment 2006;40(8):1464-1479. |
R831452 (2005) R831452 (2006) R831452 (Final) |
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Supplemental Keywords:
volatile organic compounds (VOCs), nitrogen oxides, general circulation models, precipitation, scaling, tropospheric ozone, south central, Texas, air, Ecosystem Protection/Environmental Exposure & Risk, RFA, Scientific Discipline, Atmospheric Sciences, Chemistry, Environmental Engineering, Monitoring/Modeling, climate change, particulate matter, Global Climate Change, aerosol formation, aerosols, air quality, air quality models, airborne aerosols, ambient aerosol, ambient air pollution, anthropogenic stress, atmospheric aerosol particles, atmospheric chemistry, atmospheric dispersion models, atmospheric models, atmospheric particulate matter, atmospheric transport, climate, climate model, climate models, climate variability, climatic influence, ecological models, environmental measurement, environmental stress, global change, greenhouse gas, greenhouse gases, meteorology. Air, Ecosystem Protection/Environmental Exposure & Risk, Geographic Area, RFA, Scientific Discipline, Atmospheric Sciences, Chemistry, Ecology and Ecosystems, Environmental Engineering, Environmental Monitoring, Monitoring/Modeling, State, climate change, particulate matter, Global Climate Change, Texas (TX), aerosol formation, aerosols, air quality, air quality models, airborne aerosols, ambient aerosol, ambient air pollution, anthropogenic stress, atmospheric aerosol particles, atmospheric chemistry, atmospheric dispersion models, atmospheric models, atmospheric particulate matter, atmospheric transport, climate, climate model, climate models, climate variability, climatic influence, ecological models, ecosystem models, emissions monitoring, environmental measurement, environmental stress, global change, greenhouse gas, greenhouse gases, meteorology, modeling,, RFA, Scientific Discipline, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, climate change, Chemistry, State, Monitoring/Modeling, Atmospheric Sciences, Ecological Risk Assessment, Environmental Engineering, anthropogenic stress, aerosol formation, ambient aerosol, atmospheric particulate matter, atmospheric dispersion models, ecosystem models, environmental monitoring, environmental measurement, meteorology, climatic influence, emissions monitoring, global change, ozone, air quality models, climate, modeling, climate models, greenhouse gases, airborne aerosols, atmospheric aerosol particles, atmospheric transport, Texas (TX), environmental stress, ecological models, climate model, greenhouse gas, monitoring organics, aerosols, atmospheric models, Global Climate Change, atmospheric chemistry, air quality, ambient air pollutionRelevant Websites:
http://www.geo.utexas.edu/climate/AQ/index.htm Exit
http://www.geo.utexas.edu/climate/ Exit
http://www.engr.utexas.edu/che/directories/faculty/dallen.cfm Exit
http://wnt.utexas.edu/architecture/people/faculty/parmenterf.html 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.