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This document discusses the EPA's strategic approach to emissions and meteorological modeling, focusing on improving efficiency, quality assurance, and automation of methodologies. It highlights the importance of accurate emissions calculations, the implementation of advanced modeling frameworks like SMOKE, and incorporating meteorological data for more precise air quality predictions. The presentation also addresses ongoing projects related to climate change impacts, multi-pollutant control strategies, and technical challenges faced in the field. Efforts to enhance data management and develop new models are emphasized as essential steps for future success.
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Contract Technical Kickoff EMISSIONS, METEOROLOGICAL, AND AIR QUALITY MODELING SUPPORT
EPA’s Perspective - Emissions Issues Marc Houyoux US EPA, OAQPS Air Quality Assessment Division Emission Inventory and Analysis Group
Emissions Guiding Principles • Improve timeliness • Emissions calculations • Quality assurance and summaries • Automate what can be • Prevent mistakes • Document as we go • Be able to find what we did, whether it was in-house or by a contractor; reproducibility • Improve emissions calculations, where get an impact
Improving efficiency (1) • Using the Emissions Modeling Framework for managing emissions modeling work. Example of SMOKE Case setup in the EMF…
Improving efficiency (2) • Improved automation of methods for quality assurance of SMOKE inputs and outputs • Log analysis • Automatic generation of PAVE plots • Interested in moving to VERDI • Interested in linkages to Google Earth, AirQuest, DataFed • Improvements in techniques and data for control strategy development and multi-pollutant impacts of these (ongoing work on the Control Strategy Tool), but need data.
Improving emissions calculations • Recent emissions modeling experiences for criteria and one-atmosphere (criteria, PM, Hg, and other HAPs) modeling • 2002-based platform developed by EPA • First limited use planned for this year • May need improvements in future, but none planned now • SMOKE automated test suite development • Main thrust of limited SMOKE “development” this year • Expected upcoming work assignment: Improvements in temporal profiles, speciation profiles and spatial allocation factors. New available data and new techniques for calculating improved factors. • Explore met-based techniques for met-dependent temporal allocation, such as residential wood combustion, some nonroad, and ag NH3. • Changes to emissions modeling needed to support upcoming CMAQ updates, with many emissions calculations internal… • Biogenics, plume rise, windblown dust, sea salt, ocean chlorine
Other topics of interestSMOKE-specific • Using SMOKE to support AERMOD, other dispersion models, and/or fine-scale Eulerian model applications • Inventory and ancillary data approaches for California, and using these data in modeling applications • Optimization of SMOKE processing, scripts, and quality assurance • Improvements and updates to SMOKE not previously submitted to EPA or CMAS, or not being used by EPA • Applications of SMOKE using WRF as the meteorological driver
Other topics of interest Miscellaneous • Emissions modeling and projections to support ambient air quality modeling tied to impacts of climate change • The status of the CONCEPT system and experiences using it • Experience and applications with the MEGAN biogenics model • Experience and applications with the Process-Based NH3 model • Spatial allocation approaches for resolutions below 4km • Emissions modeling applications in Alaska, Hawaii, and/or extra-continental US territories • Impacts and significance of tribal emissions data on regional and local modeling applications
The safety seagull EPA’s Perspective - Meteorology Issues Pat Dolwick US EPA, OAQPS Air Quality Assessment Division Air Quality Modeling Group
EPA Discussion of Upcoming Issues Related to Meteorological Modeling and Analyses • Primary Expectations: • Development of AQ model input meteorological files • WRF / MM5 • MCIP • Evaluation of AQ model input meteorological files • Determination of meteorological sensitivity w/in meteorological and air quality models • Meteorological elements of OAQPS climate-related activities • (e.g., downscaling global climate model outputs to drive WRF / MM5)
EPA Discussion of Upcoming Issues Related to Meteorological Modeling and Analyses • Secondary Expectations • Assist in development of meteorologically-adjusted air quality trends • Development and maintenance of ambient meteorological data bases • Develop capacity for data transfer to other groups • Applications involving meteorological preprocessors for dispersion models • (e.g., AERMET) • Incorporation of prognostic model meteorological output into short-range dispersion models • Analysis of specific years / episodic meteorology • Assistance with exceptional events, EIS reviews, & other miscellany • Initial applications of WRF-Chem, WRF-CMAQ
EPA’s PerspectiveAir Quality Modeling Issues Norm Possiel US EPA, OAQPS Air Quality Assessment Division Air Quality Modeling Group
Air Quality Modeling Issues of Interest • Model Applications • CMAQ, CAMx, and AERMOD applications for various emissions control scenarios involving criteria and criteria plus toxic pollutants • Intercontinental/national/regional/local scale applications • Impacts of climate change on (1) future pollutant concentrations and deposition and (2) the effectiveness of emissions controls • Model Evaluation • Performance evaluation for CMAQ and CAMx using measurements at the surface and aloft and satellite data
Air Quality Modeling Issues of Interest • Model Sensitivities/Improvements/ Analyses • Horizontal and vertical resolution • Plume-in-grid treatment for point sources • Improvements and updates to the scientific approaches in CMAQ and /or CAMx (e.g. deposition, mixing) • Comparison of CMAQ predictions with WRF vs MM-5 • Characterization of model-predicted and observed inter-annual variability in pollutant concentrations and deposition
Air Quality Modeling Issues of Interest • Model Response • Compare the response of CMAQ and CAMx predictions to changes in input emissions • Process Analysis to understand and interpret CMAQ and CAMx results • Source Apportionment • Apply/compare CMAQ PPTM, CAMx OSAT/PSAT, and DDM • Develop source tagging for toxic pollutants • Peer review CMAQ source tagging and CAMx source apportionment techniques
Air Quality Modeling Issues of Interest • Model Applications Framework • Develop framework for managing CMAQ and CAMx model applications and output files • Visualization tools for analysis of model inputs and outputs • Sharing model input/output data with other groups