Photochemical grid model estimates of lateral boundary contributions to ozone and particulate matter across the continental United States Kirk Baker U.S. Environmental Protection Agency Research Triangle Park, NC January 6, 2016 Outline Regulatory modeling
Source attribution: apportionment & sensitivity Lateral boundary inflow attribution project References Regulatory Modeling Use regional to local scale photochemicaltransport models (CMAQ & CAMx) Typically use 12 km grid res., sometimes 4 km,not coarser than 12 km for a regulatoryassessment 2011 NEI based emissions O3 & PM2.5 NAAQS review cycle Interstate transport rules: NOX SIP Call, CAIR,CSASPR, etc. NESHAP sector rules such as Mercury & AirToxics (MATS) New Source Review/Prevention of SignificantDeterioration: single source permit modelingfor O3 & secondary PM State/local agencies: NAAQS attainment,Regional Haze rule progress Mobile source sector rules Other types of assessments usingregulatory quality modeling but notnecessarily for rulemakings: National Air Toxics Assessment 2011 Source Sensitivity & Apportionment Modeling Approaches
How will the modeled concentrations change based on changes to emissions? Source sensitivity approaches Brute force zero out or emissions perturbations Decoupled Direct Method (DDM) What are the various contributors to modeled concentrations? Source apportionment approaches Ozone and PM source apportionment (OSAT, PSAT, ISAM) (Kwok et al 2013; Kwok et al, 2015; ENVRION,2015) Tracers: inert or reactive *All techniques have strengths and limitations Source Sensitivity & Apportionment Examples
Source groups may be single sources, groups of sources (e.g. sector, biogenics, lateralboundary inflow), entire Counties, entire States, entire Countries Baker and Kelly, 2014 Lateral boundary attribution: motivation
Increasing interest in characterizing the contribution from chemicallateral boundary inflow (Dolwick et al, 2015) Compare chemically reactive and non-reactive tracer approaches forestimating lateral boundary inflow contribution to O3 and PM2.5 Illustrate the strengths and weaknesses of the various approaches Are any techniques efficient enough to be part of routine modelapplication More project details available in Baker et al, 2015 Background All assessments 12km annual 2011 CAMx platform
CB6r2 gas chemistry; ISORROPIA inorganic chemistry GEOS-CHEM chemical inflow Surface to 50 mb with 25 layers O3 boundary contribution estimated using multiple techniques Reactive tracers: Ozone Source Apportionment Technology (OSAT) withstratified boundaries (west, north, east, south, top) uses reactive tracersthrough all chemical and physical processes in the model Reactive tracers: RTRAC with stratified boundaries (west, north, east,south) with the west and north boundaries further stratified by layers: 1 to14, 15 to 22, and 23 to 25 Non-reactive tracers: boundary condition only run (no chemistry) 7/8/2015 Background All assessments 12km annual 2011 CAMx platform
CB6r2 gas chemistry; ISORROPIA inorganic chemistry GEOS-CHEM chemical inflow Surface to 50 mb with 25 layers PM2.5 boundary contribution to PM2.5 sulfate, nitrate, ammonium, EC, primarycomponent of OC, and other primarily emitted PM2.5 Reactive tracers: Particulate Source Apportionment Technology (PSAT) withstratified boundaries (west, north, east, south, top) Non-reactive tracers: boundary condition only run (no emissions orchemistry) 7/8/2015 Reactive Tracers: OSAT, RTRAC/RTCMC
The CAMx reactive tracer (RTRAC) probing tool providesa flexible approach for introducing gas and particulatematter tracers within CAMx simulations; can not be runat the same time as OSAT/PSAT Each RTRAC tracer is influenced by boundary conditions,advection, diffusion, emissions and dry deposition. Gas-phase tracers can also undergo chemical destructionand/or production using either a simpler (RTRAC) ormore complex (RTCMC) chemistry interface. The RTRAC Chemical Mechanism Compiler (RTCMC)allows the user to externally define a full chemistrymechanism with no limits on complexity (withinavailable computer resources). 7/8/2015 RTCMC Template for CB6r2 provided by ENVIRON
Example input chemistry control file for 2 sets ofextra O3 destruction reactions for the boundarytracking simulation The configuration for this project does not accountfor NO titration A total of 8 additional sets of tracers were used totrack 3 separate vertical layers on the west andnorth boundaries and full faces east and south Additional RTCMC input is a second ICON andBCON file that only contains tracer concentrations(e.g. O3A, O3B, etc.) Fortran program to manipulate ICBC input files forRTCMC provided by ENVIRON No attempt to apply RTCMC for PM boundarycontributions 7/8/2015 O3 Contribution Monthly average O3contribution fromthe west lateralboundary using theOSAT approach. Surface level. O3 Contribution Monthly average O3contribution fromthe north lateralboundary using theOSAT approach. Surface level. Method Comparison Monthly average O3 contributionfrom all lateral boundaries usingOSAT (left panels), the difference inmonthly average O3 contributionusing inert tracers (middle panels)and the RTRAC approach (rightpanels). Surface level. Cool colors in the difference plotsindicate OSAT estimates are higherand warm colors indicate thealternative approach estimates arehigher. Inert and RTRAC tend to have largerlateral boundary O3 contributionthan OSAT reactive tracer approach Method Comparison Scatter density plots showing hourlymodel estimated lateral boundarycontribution methods compared atCASTNET monitor locations: OSATand inert tracers (top left), OSAT andRTRAC (top right). Hourly model estimated bulk O3compared with estimated lateralboundary contribution from theinert tracers (bottom left) and OSAT(bottom right) approaches atCASTNET locations. Colors represent the percentage ofpoints falling at each location on theplot so warm colors indicate areaswith a large amount of values. Western boundary inflow (RTRAC) Northern boundary inflow (RTRAC)
Layers 1-14 (left); (mid); (right) Northern boundary inflow (RTRAC) Layers 1-14 (left); (mid); (right) *results shown above are surface level PM2.5 Contribution Monthly average PM2.5contribution from all lateralboundaries and the modeltop using the PSATapproach. Surface level. Contribution tracked fromeach lateral face, justshown in aggregate herefor brevity. IMPROVE PM2.5 Bias (model estimate measured estimate) paired in time and space with modeled contribution from lateral boundary inflow using the PSAT approach. Only IMPROVE sites shown. CASTNET O3 Hourly bias (model estimate measuredestimate) paired in time and space withmodeled contribution from lateral boundaryinflow using the OSAT approach. Only model estimates of ozone where thelateral boundary contribution is greater than90% of the bulk modeled O3 are shown. Bias greater than zero indicates a model over- prediction of baseline ozone and below zeroindicates a model under-prediction ofbaseline ozone. Colors represent the percentage of pointsfalling at each location on the plot so warmcolors indicate areas with a large amount ofvalues. No obvious spatial patterns in bias Concluding Remarks Inert tracers do not provide aphysically realistic contributionestimate for ozone Better ways of evaluating theboundary inflow? This type ofassessment misses the situationswhere observed BCONinfluence is not captured due tomischaracterized meteorology OSAT more computationallyefficient than RTRAC approach Not clear any approach efficientenough for routine application References Baker, K.R., Emery, C., Dolwick, P., Yarwood, G., Photochemical grid model estimates oflateral boundary contributions to ozone and particulate matter across the continental UnitedStates. Atmospheric Environment 123, Dolwick, P., Akhtar, F., Baker, K.R., Possiel, N., Simon, H., Tonnesen, G., Comparison ofbackground ozone estimates over the western United States based on two separate modelmethodologies. Atmospheric Environment 109, Kwok, R., Baker, K.R., Napelenok, S., Tonnesen, G., Photochemical grid modelimplementation of VOC, NO x, and O 3 source apportionment. Geoscientific Model Development8, Baker, K.R., Kelly, J.T., Single source impacts estimated with photochemical model sourcesensitivity and apportionment approaches. Atmospheric Environment 96, Kwok, R., Napelenok, S., Baker, K.R., Implementation and evaluation of PM2.5 sourcecontribution analysis in a photochemical model. Atmospheric Environment 80, ENVIRON, CAMx Users Manual.