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Climate Change and Air Pollution Modeling

Climate Change and Air Pollution Modeling. NCAR Summer Colloquium on Climate and Health July 27, 2004. Michelle L. Bell Yale University, School of Forestry and Environmental Studies Quansong Tong Princeton University, Woodrow Wilson School. Air Quality Modeling and Climate Change.

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Climate Change and Air Pollution Modeling

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  1. Climate Change and Air Pollution Modeling NCAR Summer Colloquium on Climate and Health July 27, 2004 Michelle L. Bell Yale University, School of Forestry and Environmental Studies Quansong Tong Princeton University,Woodrow Wilson School

  2. Air Quality Modeling and Climate Change • Purposes of air quality modeling • Overview of air quality models • Relationship to climate change research • Examples

  3. ? Emissions Land-use Meteorology Air Pollutant Concentrations

  4. Emissions Land-use Meteorology Air Pollutant Concentrations Air Quality Model

  5. Why not use monitors? • Measurements • Only available at certain times and locations • Typically geared to measuring compliance with regulatory standards • Hard to explore some research questions • Other places and time periods • Other scenarios for emissions, meteorology, etc.

  6. x Comparison of Maximum O3 Concentrations 24 Monitor Measurements 2880 Model Estimates

  7. models Uses for Air Quality Modeling • Regulatory purposes • Generate concentration estimates in places without monitors • Estimate public health impacts from air pollution policies • Explore “what-if” scenarios, such as climatic changes

  8. Cout Cin dC/dt Gridded Atmosphere (Box Model) • Incorporates: chemical reactions, decay, physical transformation • Requires initial and boundary conditions • Assumptions include: homogeneous mixing within the box

  9. Domain 1: 108-km grid cell resolution Domain 2: 36-km grid cells Domain 3: 12-km grid cells Domain 4: 4-km grid cells Domain 1 Domain 2 Domain 3 Domain 4 Domains and Nests Domain 1 Domain 2 Domain 3 Domain 4 Domain 1: 108-km grid cell resolution Domain 3: 36-km grid cells Domain 2: 12-km grid cells Domain 4: 4-km grid cells

  10. Gridded Results Can Be Connected to Other Data Example: Population in areas that exceed the O3 NAAQS (using Census) Bell and Ellis (2003), Journal of the Air & Waste Management Association 53:1531-40

  11. Meteorology-Chemistry Interface Processor (MCIP))a Emission Processing System (SMOKE) Chemistry Transport Model (CMAQ) Results/Analysis Visualization Models-3 Framework Meteorology (MM5)

  12. Features of Models-3 • Multi-scale: can be run at different resolutions • Multi-pollutants: 95 species including O3, PM (including PM2.5), SO2, CO, NOx, and VOCs • Modular • Active development (“state of the science”)

  13. Models-3 Framework MM5 (Meteorological Modeling System) CMAQ (Community Multi-scale Air Quality) LUPROC (Land-Use Processor) MEPPS (Models-3 Emissions Processing and Projection System) MCIP (Meteorology-Chemistry Interface Processor) INPRO (Input Processor) EMPRO (Emission Processor) ECIP (Emissions-Chemistry Interface Processor) CCTM (CMAQ Chemical Transport Model) OUTPRO (Output Processor) JPROC (Photolysis Rate Processor) SAS MEPRO (Models-3 Emissions Projections Processor) ICON (Initial Conditions Processor) Arc/Info BCON (Boundary Conditions Processor) IDA (Inventory Data Processor)

  14. PSU/NCAR Mesoscale Model Version 5 (MM5) • Generates gridded estimates of meteorological variables (e.g., temperature) to be used as input in the air pollution model

  15. Landuse Data Hourly Emissions Biogenic Processing Mobile Processing Meteorology Data Matrices Model Ready Emissions Area Processing Emissions Inventory Hourly Layer Fractions Point Processing Air Quality Modeling Component I: Emission Model (SMOKE) (SMOKE: Sparse Matrix Operator Kernel Emissions modeling system)

  16. Model Output • Estimates for each gridcell for every time period (e.g., hour) for each pollutant • Ozone, particulate matter (including PM2.5), sulfur dioxide, others

  17. Example Modeling Application All VOC and NOx emissions increased 25% Increase in 1-hour max O3 All anthropogenic VOC and NOx emissions increased 25%

  18. Model Evaluation • How good are the concentration estimates? • What do we care about? • Several graphical and numerical techniques available • Model developers, policy-makers, and EPA generally do not promote rigid criteria for accepting or rejecting modeling results

  19. Some Statistical Measures Mean Bias Normalized Bias Gross error Unpaired highest-prediction accuracy

  20. = observed (monitor) concentration at location i and time j = predicted (model) concentration at location i and time j = number of hourly prediction-observation pairs for location i = number of monitoring stations = number of total hours for all prediction-observation pairs across all monitors = peak observed concentration = peak predicted concentration

  21. little high good very good Evaluation of Models-3 for O3 Bell and Ellis (2004), Atmospheric Environment 38:1879-89

  22. Comparison of Model Estimates and Measurements (O3)

  23. Model-Estimates and Measurements (O3 8-hr average) Location: Millington, Maryland 8-hr Average O3 (ppb) Local Time

  24. PM10: Model-Estimates and Measurements (24-hr avg. July 14, 1995)

  25. More Information on Air Quality Modeling • Models-3 (Air quality model) • http://www.epa.gov/asmdnerl/models3/index.html • Community Modeling & Analysis System (CMAS) • http://www.cmascenter.org/html/models.html • MM5 (Meteorological model) • http://www.mmm.ucar.edu/mm5/

  26. Connecting Air Quality Modeling to Climate Change and Human Health • Can explore the impacts of future climatic conditions (or other future conditions) on ambient air quality • Can use model results to relate changes in air quality to human health (e.g., epidemiological concentration-response functions)

  27. Emissions Land-use Meteorology Health Climate Change Air Quality Air Quality Model

  28. Example: Ozone and Climate • Elevated mortality and hospital admissions from climate change induced increases in ambient ozone concentrations • M.L. Bell, C. Hogrefe, C. Rosenzweig, P. Kinney, J. Rosenthal, K. Knowlton, B. Lynn, J. Patz • Builds on research of the New York Climate & Health Project (Columbia University, P. Kinney) http://eiwall.ei.columbia.edu/directory/displayproject.php?projectid=150 • Related project for New York City region (Kim Knowlton)

  29. How could climate change affect O3 and thereby health? • Hourly ambient concentrations of ground-level ozone • Current climate: summers of 1995 to 1997 • Future climate: summers of 2053 to 2057 • Connect changes in concentration to health using epidemiological studies • Only examines a piece of how climate change could affect (ozone air quality only) • Only examines a piece of how elevated ozone could affect health (a subset of the adverse impacts)

  30. Changes in Daily O3

  31. Changes in Daily Ozone (ppb)

  32. Red (1.2%) Red (2.5%) Purple (0.3%) Purple (0.1%) Orange (8%) Orange (13%) Yellow (27%) Green (54%) Yellow (31%) Green (63%) Changes in O3 Air Quality Index Category Future Climate Current Climate

  33. Human Health Impacts • Percent Increase in Total Mortality (Stieb et al. 2003) • Overall: 0.28% (0.17, 0.39) • Largest: 0.43% (0.12, 0.73) • Percent Increase in asthma-related hospital admissions for those < 64 (Sheppard et al. 2003) • Overall: 2.1% (0.6, 3.6) • Largest: 4.7% (1.4, 8.1)

  34. Current Research on Climate Change Using Air Quality Modeling • Pacific Northwest Regional Climate Modeling Project • Focuses on the Pacific Northwest and the Northern Midwest • Univ. of Washington (Jack Chen, et al.) • www.atmos.washington.edu/~salathe/reg_climate_mod/STARCCAQ/

  35. Recent Research on Climate Change Using Air Quality Modeling • Carnegie Mellon University • Peter Adams, Spyros Pandis • Development of an integrated modeling framework and sensitivity assessment for the effects of climate change and global emissions on U.S. air quality • http://cfpub2.epa.gov/ncer_abstracts//index.cfm/fuseaction/display.abstractDetail/abstract/6238/report/0

  36. Recent Research on Climate Change Using Air Quality Modeling • Georgia Institute of Technology, MIT, Northeast States for Coordinated Air Use Management • Russell Armistead, M. Talat Odman, Ronald Miller, et al. • EPA-funded project for sensitivity and uncertainty assessment of climate change on ozone and particulate matter • http://cfpub2.epa.gov/ncer_abstracts//index.cfm/fuseaction/display.abstractDetail/abstract/6238/report/0

  37. Recent Research on Climate Change Using Air Quality Modeling • New York Climate & Health Project • Patrick Kinney, Christian Hogrefe et al., Columbia University • Focuses on NY metropolitan region • Estimating health impacts associated with climate change • http://eiwall.ei.columbia.edu/directory/displayproject.php?projectid=150 • http://www.earth.columbia.edu/events/2004/nycch.htm

  38. Concluding Thoughts on Air Quality Modeling and Climate Change + Useful way to link changes in emissions, land-use, and meteorology to ambient air quality and then to health + Highly resolved estimates, temporally and spatially + Generally reflects “state of the science” knowledge regarding the physical and chemical transformation of pollutants

  39. Concluding Thoughts on Air Quality Modeling and Climate Change –Requires time, money, and expertise –Data input requirements –Uncertainties • Model evaluation • Modeling system under different conditions • Input of climate change scenarios into the air quality modeling system

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