137 E. Franklin Street, 6th floor ● Campus Box 6116 ● Chapel Hill, NC 27599-6116.

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Presentation transcript:

137 E. Franklin Street, 6th floor ● Campus Box 6116 ● Chapel Hill, NC

The UNC Institute for the Environment focuses its research and engagement on four critical issues that lie at the heart of global environmental challenges... Environmental Modeling Landscape Change & Health Energy & the Environment Sustainable Community Design

The UNC Institute for the Environment conducts its environmental modeling work within the Center for Environmental Modeling for Policy Development (CEMPD) – a group of 20 scientists and engineers with a long history working with EPA To learn more about CEMPD, visit us on the web at: CEMPD Expertise Air Quality Modeling Modeling Tool Development Meteorological Modeling Regulatory Support Emissions Modeling Data Analysis

Ambient, Met, and AQ Data Analysis Atmospheric Model Evaluation Tool (AMET) Integrating AMET-AQ and AMET-Met to create a unified approach for evaluating met and AQ model results Creating installation package, user interface, and documentation Air Quality and Emissions Model Performance Evaluation Developing tools to process and create netCDF files of aerometric and emissions data Create an extensive set of model evaluation tools for annual model evaluation of CMAQ with O 3, PM and Air Toxics, against various observed networks Create tools to visualize AERMOD outputs with PAVE National Urban Database and Access Portal Tools (NUDAPT) Hosting an emerging collection of high-resolution 3-d building and land use data for urban modeling Sponsors EPA, FAA and Others

Overview An observational and modeling study to examine the interrelationships among: Changes in climate Air pollution Heat and cold morbidity Classification of weather patterns Figure shows percentage rise in asthma-related hospital admissions Sponsor EPA Ambient, Met, and AQ Data Analysis Effects of Climate Change on Human Health

Air Quality Modeling CEMPD investigates the scientific issues involved with simulating air quality through the development, evaluation, and application of air quality modeling systems at urban, regional and global scales. Projects related to air quality modeling include: Air Quality Impacts of Aviation Emissions Radiative Feedback of Aerosols CMAQ Coarse-mode Chemistry Algorithms Effects of Climate Change on Human Health Integrated Meteorology-Chemistry Modeling

Air Quality Impacts of Aviation Emissions Overview Multiscale annual CMAQ simulations to assess incremental effects of aviation emissions on O 3, PM and Air Toxics near airports Comparative evaluation of AERMOD driven by MM5 and NWS meteorology Compare CMAQ and AERMOD outputs Explore alternate hybrid modeling techniques Develop PM Response Surface Model (PM-RSM) for aviation emissions Data transfer to multiple institutions Sponsors Federal Aviation Administration (FAA) NASA FAA/NASA/TC Center of Excellence Air Quality Modeling

CMAQ Photolysis Module Overview New on-line photolysis module includes effect of primary and secondary aerosols predicted by CMAQ Cloud effects on photolysis calculated on-line Calculates single scattering albedo for vertical column to compare with satellite data Overview Direct radiative aerosol feedbacks in WRF/CMAQ Develop a software module to estimate the optical and radiative properties of CMAQ simulated aerosol fields Develop a scheme to facilitate the direct aerosol feedback to the WRF shortwave radiation module Sponsor EPA Coupled Met/Chem WRF/CMAQ

Variable Grid Modeling Overview Natural transport of plumes across multiple grid resolutions Avoids nesting Single domain can cover many resolutions One model run Figure shows partial modeling domain over North Carolina Sponsor DOE Air Quality Modeling

Intercontinental Transport and Climatic Effects of Air Pollutants Overview Examine processes associated with cross-Pacific and cross-Atlantic pollutant transport Annual simulations and analyses of meteorology and emissions Figure shows an ozone episode during April 1998 Sponsor EPA Air Quality Modeling

NO 3 - NH 4 + SO 4 = Na + Cl - H 2 O POA SOA a SOA b EC Other SVOCs HNO 3 NH 3 H2OH2O NO 3 - NH 4 + SO 4 2- Na + Cl - H 2 O Soil, Other COARSE MODE2 FINE MODES H 2 SO 4 HCl Developed algorithms to be included in next CMAQ release for chemistry of coarse particles New species and interactions shown in RED Sponsor EPA Air Quality Modeling

Overview We developed and applied a coupled meteorology-chemistry model to study air quality impacts on climate; evaluating with long-term aerosol measurements over North America Impacts of A1B and B1 IPCC emissions scenarios for 2030 are being examined over South Asia The model is being linked to a forest growth model and fire simulator to examine climate change, forest biomass loads, fire emissions and aerosol carbon over the southeastern U.S. Sponsors NSF, EPA Integrated Modeling Air Quality and Climate Interactions Modeled Aerosol Optical Depths

Meteorological Modeling Prognostic snow model in WRF Overview Develop a prognostic snow model in the Pleim/Xiu Land Surface Model within WRF The snow model has only one layer of snow cover and simulates the snow accumulation, sublimation, melting, and heat exchange at snow– atmosphere and snow–soil interfaces Sponsor EPA Air Quality Forecast Support Overview Review/optimize AQ forecast system using MM5 and WRF over Korea - Reduced MM5 runtimes by 50% using appropriate MPI settings Sponsor Korea Institute of Science and Technology

CEMPD is a leader in emissions data preparation for air quality modeling. As the primary developer of the Sparse Matrix Operator Kernel Emissions (SMOKE) model, CEMPD has been advancing emissions software and modeling concepts for over a decade. Emissions Inventory Modeling Projects related to emissions inventory modeling include Determining the causes of regional haze and acid deposition Air quality impacts of aviation emissions

Determining the Causes of Regional Haze and Acid Deposition Emissions Inventory Modeling Overview Regional haze modeling of the western U.S. Conducting multiple annual base-and future- year emissions simulations Regional haze SIP development 2006 base year modeling for the Rocky Mountain Atmospheric Nitrogen and Sulfur (RoMANS) study Sponsors Western Governors’ Association National Park Service

Air Quality Impacts of Aviation Emissions Overview Develop new SMOKE interface to process high-resolution airport-level emissions estimates from FAA’s EDMS, that vary in 4-D Develop custom temporal profiles from a few airports to 325 U.S. airports Process integrated CAP+HAP annual inventories Compare NEI and EDMS-based estimates Development of in-flight aircraft emissions inventories for SMOKE/CMAQ modeling Sponsors Federal Aviation Administration (FAA) NASA Emissions Inventory Modeling

UNC Computing Resources Compute Servers Topsail – 4, GHz EM64T CPUs 28.7 Teraflops capacity, ranks 34 th in Top 500 Emerald – 320 mixed CPUs (Xeon and Athlon) Gigaflops capacity Cedar/Cypress – 136 Itanium2 CPUs Data Storage 39 Tb of shared scratch space Mass Storage – IBMTS3500 tape library, scalable Petabyte long-term storage, with dual backup Provides data access in near real-time

Documentation and Tech Transfer Overview Developing and providing documentation, support, and distribution for several modeling, decision support, and analysis tools Globally renowned training program for emissions and air quality modeling Host of the CMAS Center Supported Tools SMOKE CMAQ/MCIP BenMAP VERDI

Training and Conferences SMOKE, CMAQ, EMF, and WRF hands-on trainings New Process Analyses Training Classes offered at UNC and on-site at any location, worldwide Annual conference highlighting developments and applications of atmospheric modeling Visiting scientist program for collaborative training with the CMAS Center August ‘07 CMAS-NATO Workshop Bulgarian Academy of Sciences Sofia, Bulgaria Community Modeling and Analysis System (CMAS) Outreach July ‘06 SMOKE training for INE Mexico City, Mexico

CEMPD software engineers have developed many models and software tools that support environmental modeling. Using a team approach to software design and engineering, we focus on improving the modeling process by facilitating the automation of modeling studies and by developing tools for the generation and use of metadata during model application studies. Projects related to software design include: Emissions Modeling Framework Control Strategy Tool (CoST) Spatial Allocator Surrogate Tool Modeling Tool Development

Overview A system to better manage emissions modeling data Changes to datasets are tracked and versioned in a database; any version can be retrieved at any time Quality assurance steps can be run and tracked “Case manager” provides a graphical user interface to run SMOKE and other models Embedded Control Strategy Tool (CoST) develops controlled inventories using available control measures Sponsor EPA Emissions Modeling Framework Modeling Tool Development

Spatial Allocator Overview Converts BELD3 land use data to SMOKE inputs Changes data on one grid to another grid Point-to-grid, projection, and datum conversion Spatial data overlay and Shapefile filtering Surrogate Tool Overview Part of the Emissions Modeling Framework Creates SMOKE surrogates from Shapefile attributes (e.g., population) Merges precomputed surrogates Gapfills surrogates to prevent dropping of emissions Sponsor EPA 1km data converted to 4km data Sample Surrogate Tool output Modeling Tool Development

Overview Real-time storm-surge prediction system created for the State of North Carolina Uses WRF numerical weather prediction model + ADCIRC coastal ocean prediction model Assists with evacuation planning, decision- making and resource deployment Sponsors FEMA State of North Carolina RENCI Storm-surge simulation of Tropical Storm Ernesto Decision Support Hurricane Storm-Surge Prediction

137 E. Franklin Street, 6th floor ● Campus Box 6116 ● Chapel Hill, NC Center for Environmental Modeling for Policy Development Contact Information: Adel HannaDirector of Alison EythContract Program Sarav ArunachalamSenior Air Quality Zac AdelmanSenior Emissions Additional contact information: