Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Data Needs for Evaluation of Radical and.

Slides:

Advertisements

Similar presentations

Detailed chemical modelling based on the Master Chemical Mechanism (MCM) Mike Jenkin EMMA Group Department of Environmental Science and Technology

Advertisements

Simulating isoprene oxidation in GFDL AM3 model Jingqiu Mao (NOAA GFDL), Larry Horowitz (GFDL), Vaishali Naik (GFDL), Meiyun Lin (GFDL), Arlene Fiore (Columbia.

OThree Chemistry MM5/CAMx Model Diagnostic and Sensitivity Analysis Results: Base B and Emissions Sensitivities Central California Ozone Study: Bi-Weekly.

Measurement of NO y During SCOS97-NARSTO Dennis R. Fitz University of California, Riverside College of Engineering Center for Environmental Research and.

Preliminary Results CMAQ and CMAQ-AIM with SAPRC99 Gail Tonnesen, Chao-Jung Chien, Bo Wang, UC Riverside Max Zhang, Tony Wexler, UC Davis Ralph Morris,

Sensitivity to changes in HONO emissions from mobile sources simulated for Houston area Beata Czader, Yunsoo Choi, Lijun Diao University of Houston Department.

Evaluating the impact of recent changes in

Chemical regimes over Europe – long term, seasonal and day to day variability Matthias Beekmann LISA University Paris 7 and 12, CNRS Créteil, France Thanks.

Improving the Representation of Atmospheric Chemistry in WRF William R. Stockwell Department of Chemistry Howard University.

Christian Seigneur AER San Ramon, CA

The Framework of Modeling SOA Formation from Toluene Oxidation Di Hu and Richard Kamens Department of Environmental Sciences and Engineering, University.

Developing Secondary Organic Aerosol (SOA) Code for the MCM David Johnson (Mike Jenkin and Steve Utembe) Department of Environmental Science and Technology,

Modification of the chemical environment during long-range transport M. Auvray & I. Bey GEOS-CHEM Meeting – April 2005 Swiss Federal Institute of Technology,

Evaluation of MCM v3, using environmental chamber data P. G. Pinho 1, C.A. Pio 1 and M.E. Jenkin 2 1 Departamento de Ambiente e Ordenamento, Universidade.

This Week—Tropospheric Chemistry READING: Chapter 11 of text Tropospheric Chemistry Data Set Analysis.

Ozone Production Efficiency in the Baltimore/Washington Urban Plume Presentation by Linda Hembeck Co-Authors: Christopher Loughner, Timothy Vinziguerra,

Sensitivity of U.S. Surface Ozone to Isoprene Emissions & Chemistry: An Application of the 1°x1 ° North American Nested GEOS-CHEM Model GEOS-CHEM Model.

Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Modeling Source Apportionment Gail Tonnesen,

Atmospheric chemistry Day 4 Air pollution Regional ozone formation.

Simulation of Houston-Galveston Airshed Ozone Episode with EPA’s CMAQ Daewon Byun: PI Soontae Kim, Beata Czader, Seungbum Kim Emissions input Chemical.

Simple Chemical modeling of ozone sensitivity

QUESTIONS 1.If CO emission to the atmosphere were to double, would you expect CO concentrations to (a) double, (b) less than double, (c) more than double?

Xuexi Tie Xu Tang,Fuhai Geng, and Chunsheng Zhao Shanghai Meteorological Bureau Atmospheric Chemistry Division/NCAR Peking University Understand.

Krish Vijayaraghavan, Prakash Karamchandani Christian Seigneur AER San Ramon, CA 3rd Annual CMAS Models-3 Conference October 18-20, 2004 Chapel Hill, NC.

University of California Riverside, ENVIRON Corporation, MCNC WRAP Regional Modeling Center WRAP Regional Haze CMAQ 1996 Model Performance and for Section.

Center for Environmental Research and Technology University of California, Riverside Bourns College of Engineering A Process Analysis for Analyzing and.

Examination of the impact of recent laboratory evidence of photoexcited NO 2 chemistry on simulated summer-time regional air quality Golam Sarwar, Robert.

Yuzhi Chen 13th CMAS Assessment of SAPRC07 with Updated Isoprene Chemistry against Outdoor Chamber Experiments Yuzhi Chen a, Roger Jerry a, Kenneth Sexton.

Comparison of three photochemical mechanisms (CB4, CB05, SAPRC99) for the Eta-CMAQ air quality forecast model for O 3 during the 2004 ICARTT study Shaocai.

O UTLINE Why are we interested in linking GEOS- CHEM with regional air quality model (CMAQ)? Technical issues to consider when linking GEOS-CHEM & CMAQ.

Center for Environmental Research and Technology University of California, Riverside Bourns College of Engineering Evaluation and Intercomparison of N.

PM2.5 Model Performance Evaluation- Purpose and Goals PM Model Evaluation Workshop February 10, 2004 Chapel Hill, NC Brian Timin EPA/OAQPS.

WRAP Update. Projects Updated 1996 emissions QA procedures New evaluation tools Model updates CB-IV km MM5 Fugitive dust NH 3 emissions Model.

Ozone MPE, TAF Meeting, July 30, 2008 Review of Ozone Performance in WRAP Modeling and Relevance to Future Regional Ozone Planning Gail Tonnesen, Zion.

Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CMAQ Tagged Species Source Apportionment (TSSA)

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Fire Plume Rise WRAP (FEJF) Method vs. SMOKE.

Deguillaume L., Beekmann M., Menut L., Derognat C.

Model & Chemistry Intercomparison CMAQ with CB4, CB4-2002, SAPRC99 Ralph Morris, Steven Lau, Bongyoung Koo ENVIRON International Corporation Gail Tonnesen,

Methods for Incorporating Lightning NO x Emissions in CMAQ Ken Pickering – NASA GSFC, Greenbelt, MD Dale Allen – University of Maryland, College Park,

Evaluation of the VISTAS 2002 CMAQ/CAMx Annual Simulations T. W. Tesche & Dennis McNally -- Alpine Geophysics, LLC Ralph Morris -- ENVIRON Gail Tonnesen.

Statewide Protocol: Regional Application August 27, 2003 Air Resources Board California Environmental Protection Agency Luis F. Woodhouse.

Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CMAQ Model Performance Evaluation with the.

Hemispheric transport of ozone pollution and the nonlinearities GMI meeting UC Irvine March 17, 2008 Shiliang Wu, Harvard Bryan Duncan, NASA / GSFC Arlene.

1. How is model predicted O3 sensitive to day type emission variability and morning Planetary Boundary Layer rise? Hypothesis 2.

Weekend/Weekday Ozone Observations in the South Coast Air Basin Phase 1 Report Sponsored by National Renewable Energy Laboratory and Coordinating Research.

May 22, UNDERSTANDING THE EFFECTIVENESS OF PRECURSOR REDUCTIONS IN LOWERING 8-HOUR OZONE CONCENTRATIONS Steve Reynolds Charles Blanchard Envair 12.

Status of MOZART-2 Larry W. Horowitz GFDL/NOAA MOZART Workshop November 29, 2001.

HYMN Hydrogen, Methane and Nitrous oxide: Trend variability, budgets and interactions with the biosphere GOCE-CT Status of TM model Michiel.

1 Prakash Karamchandani 1, David Parrish 2, Lynsey Parker 1, Thomas Ryerson 3, Paul O. Wennberg 4, Alex Teng 4, John D. Crounse 4, Greg Yarwood 1 1 Ramboll.

Georgia Institute of Technology SUPPORTING INTEX THROUGH INTEGRATED ANALYSIS OF SATELLITE AND SUB-ORBITAL MEASUREMENTS WITH GLOBAL AND REGIONAL 3-D MODELS:

June 29, 2011NASA/ARB Data Analyses Discussion1 What can We Learn from ARCTAS-CARB Data? Modeling and Meteorology Branch Planning and Technical Support.

W. T. Hutzell 1, G. Pouliot 2, and D. J. Luecken 1 1 Atmospheric Modeling Division, U. S. Environmental Protection Agency 2 Atmospheric Sciences Modeling.

U.S. Environmental Protection Agency Office of Research and Development Implementation of an Online Photolysis Module in CMAQ 4.7 Christopher G. Nolte.

Visualizing Winter Nitrate Formation Using CMAQ Process Analysis Charles Stanier – University of Iowa CENTER FOR.

SciDAC Fast Chemical Mechanism LLNL Philip Cameron-Smith Peter Connell Cathy Chuang (John Taylor) Keith Grant (Doug Rotman) NCARJean-Francois Lamarque.

Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CCOS 2000 Model Intercomparison: Summary of.

Comparisons of the Response of Simulated Ozone Concentrations to Changes in Emissions Using the Carbon Bond IV and SAPRC99 Chemical Mechanisms Bruce Jackson,

University of California, Los Angeles Nocturnal Vertical Gradients of O 3, NO 2, NO 3, HONO, HCHO, and SO 2 during CalNex 2010 Tsai Catalina, Kam Weng.

Uncertainties in isoprene-NO x -O 3 chemistry: Implications for surface ozone over the eastern United States TEMP PAR Leaf Area ISOPRENE + NO x  O 3 Arlene.

Understanding the impact of isoprene nitrates and OH reformation on regional air quality using recent advances in isoprene photooxidation chemistry Ying.

Ozone Budget From: Jacob. Ozone in the Atmosphere Lifetime: –~1 month –Highly variable – dependent on season, latitude, altitude, etc. Background concentrations:

Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division Office of Research and Development.

Andrea Fraser DIAC PhD student Supervised by Prof. H ApSimon

Workshop on Air Quality Data Analysis and Interpretation

Characteristics of Urban Ozone Formation During CAREBEIJING-2007 Experiment Zhen Liu 04/21/09.

INTERCONTINENTAL TRANSPORT EXPERIMENT – NORTH AMERICA (INTEX-NA)

OZONE PRODUCTION IN TROPOSPHERE

Asian outflow and chemical evolution of ozone and nitrogen oxides over the Pacific Mathew Evans, Daniel Jacob, Harvard Group, TRACE-P Science Team et al.

UNCERTAINTY ANALYSIS IN OZONE MODELS

Improving Regional PM2.5 Modeling along Utah’s Wasatch Front

Presentation transcript:

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Data Needs for Evaluation of Radical and NOy Budgets in SCOS97-NARSTO Air Quality Model Simulations February 14, 2001, SCOS97-NARSTO DataWorkshop Gail S. Tonnesen University of California, Riverside Bourns College of Engineering Center for Environmental Research and Technology

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Acknowledgments Funding for related projects –U.S. EPA –American Chemistry Council Datasets – Draft prerelease datasets provided by ARB

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Trace Gas Governing Equations j=1,N Coupled PDEs  C j  t   v.  C j + D  2 C j + P(C)  L(C)C j + E j  D j Operator Splitting:  C j  t =  v.  C j  C j  t = D  2 C j + E j  D j dC j  dt = P(C)  L(C)C j Gear solver is the gold standard for stiff ODEs

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Model Evaluation Verification, Validation or Evaluation? –Oreskes et al., Comparisons with ambient data. Validation of component processes. Indicators for testing O3 sensitivity. Sensitivity and uncertainty analysis.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Family Definitions NO x = NO + NO 2 + (NO N 2 O 5 + HONO + HNO 4 ) NO z = HNO 3 + RNO 3 + NO 3 – + PAN NO y = NO x + NO z = total oxidized nitrogen. HC = VOC (or ROG) + CH4 + CO O x = O 3 + O + NO 2 + NO z + 2 NO N 2 O 5 + HNO 4 HO x = OH + HO 2 + RO 2

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Fundamental Photochemistry Tropospheric gas phase chemistry is driven by the OH radical: Radical Initiation Radical Propagation Radical Termination NO x termination

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside PSS Equilibrium NO 2 + h   NO + O O + O 2  O 3 O 3 + NO  O 2 + NO 2 NO 2 + O 3  NO 3 + O 2 NO 3 + h   NO 2 + O P(O x ): RO 2 + NO  RO + NO 2 HO 2 + NO  OH + NO 2

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Radical Initiation O 3 + h   O( 1 D) O( 1 D) + H 2 O  2 OH HCHO + h   2 HO 2 + CO HO 2 + NO  OH + NO 2 HONO + h   OH + NO PAN  RO 3 + NO 2

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Radical Propagation OH + CH 4 + O 2  CH 3 O 2 + H 2 O CH 3 O 2 + NO  NO 2 + CH 3 O CH 3 O + O 2  HO 2 + HCHO HO 2 + NO  NO 2 + OH 2x( NO 2 + h  + O 2  O 3 + NO ) Net Reaction: CH O 2  2 O 3 + HCHO + H 2 O

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Radical and NO x termination OH + NO 2  HNO 3 HO 2 + HO 2  H 2 O 2 HO 2 + RO 2  ROOH RO 2 + NO  RNO 3 RO 3 + NO 2  PAN N 2 O 5 + H 2 O  2 HNO 3

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Local Diagnostics – Instantaneous reaction rates at a given site. –Examples: P(OH), P(O x ), P(O x )/P(NO z ) –Cannot get production rates from time-series! Cumulative Trajectory Diagnostics –cumulative history of reaction rates and other loss processes in an air parcel integrated over hours or days. –Examples: [H 2 O 2 ], [HNO 3 ], [O 3 ], [O 3 ]/[NO z ] Model Evaluation

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Radical Initiation J-values & HCHO, O 3, H 2 O, HONO, H 2 O 2, PAN OH Chain Length  k OH HC i /(  k OH HC i + k OH NO 2 ) k HO2 NO /(k HO2 NO + k HO2 (RO HO 2 ) ) Radical Termination NO 2 & OH, HO 2 & RO 2, NO & RO 2, O 3 NO x Termination, P(NO z ): NO 2 & OH, NO & RO 2, NO 2 & RCO 3, NO 3, N 2 O 5 & H 2 O P g (O x ) NO, HO 2, RO 2. Data Needs for Local Diagnostics

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Radical Initiation & Termination (approximate):Radical Initiation & Termination (approximate): (2 peroxides + NO z ) (2 peroxides + NO z ) OH Chain Length (approximate):OH Chain Length (approximate): O x / (2 peroxides + NO z ) 2 peroxides/NO z 2 peroxides/NO z NO x Termination, P(NO z ):NO x Termination, P(NO z ): HNO 3, speciated RNO 3, NO 3 -, PAN HNO 3, speciated RNO 3, NO 3 -, PAN P(O 3 ), P(O x ):P(O 3 ), P(O x ): O 3, & O 3 +NO 2 + NO z Data Needs for Cumulative Diagnostics

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Model Domain and Parameters 1997 Southern California Ozone Study (SCOS97). Aug 3 to 5, 1997 CMAQ and CAMx MM5 16 layers CB4 chemical mechanism Gear CMAQ, CMC CAMx Bott Advection Scheme No Aerosols Includes process analysis diagnostic outputs.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Uncertainties In CMAQ vs CAMx Comparison Timing in CAMx - are emissions calculated as PST or PDT? Vertical mixing - CAMx has less vertical dispersion in early morning? Emissions - CMAQ may be missing large point sources. Problem with isoprene in CAMx

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Peak Model Ozone on Aug 5 (3rd day) Difficult to analyze effects accumulated over 3 days, so...

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Start Evaluation with spinup (1st day) Comparison of O3 at 15:00 PDT:

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Comparison of O3 aloft before start of 2d day Errata: all units are ppbV

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Pg(Ox) 7:00-8:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Pg(Ox) 8:00-9:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Pg(Ox) 9:00-10:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Pg(Ox) 10:00-11:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Pg(Ox) 11:00-12:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Cumulative Pg(Ox) 7:00-19:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside CO conc. at 9:00 PDT in LA: inversion breaks up 2 hours later in CAMx…is timing of emissions wrong?

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Cumulative P(OH) 7:00-19:00 PDT, Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside H2O at 12:00 PDT

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside % contribution of O1D to OH initiation, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside HO2 initiation, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside RO2 radical initiation, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Reactions of NO3 & O3 with isoprene, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Reactions of OH with isoprene, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Total new radical initiation, Layer 1, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Total OH Production, Layer 1, cumulative for Aug 3.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside HNO3 mixing ratio, 24:00 PDT, Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside HNO3 produced by OH+NO2, Layer 1, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside HNO3 produced by OH+NO2, Later 3, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside HNO3 produced by N2O5+H2O, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside E-W Slice through LA, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Fraction HNO3 of total NOz, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Net Production of PAN, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Production of organic nitrates, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Total Production of NOz, cumulative for Aug 5.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Ox production efficiency per NOx, cumulative for Aug 5. (Note: regions of gray within red are areas in which P(NOz) is negative).

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Indicators to Evaluate O3 Sensitivity Indicators based on HNO 3 or NO z may fail in CAMx simulations due to large contribution of N 2 O 5 +H 2 O to P(HNO 3 ). Alternative: Use indicators based on radical propagation efficiency, O 3 is VOC sensitive for: %HO 2 +NO > 93% %OH+HC < 80%

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Indicator of O3 sensitivity: %HO2+NO (cumulative for Aug 5).

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Indicator of O3 sensitivity: %OH+HC (cumulative for Aug 5). (Note colormap is inverted)

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Conclusions Minor problems with emissions, vertical dispersion and time zone need to be corrected before full evaluation. More serious issue w.r.t. N 2 O 5 chemistry. Uncertainty in fate of NO x is a critical issue for O 3 sensitivity and weekend effects. Validation of HO x budgets is equally important.

Center for Environmental Research and Technology/Environmental Modeling University of California at Riverside Recommendations Should adopt an up-to-date mechanism –SAPRC99, CB4-99, RACM2. Use NO y data to better characterize N 2 O 5 chemistry and NO x fate. Use sensitivity studies to evaluate effects of uncertainty in N 2 O 5 chemistry.