Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Forecast and Hindcast Modeling in the Grand Bay Mercury Intensive Mark Cohen, Fantine Ngan, Roland Draxler, Winston Luke, Paul Kelley, and Richard Artz NOAA Air Resources Lab, Silver Spring, Maryland _____________________ Grand Bay Mercury Intensive Data and Planning Meeting, Jan 24, 2011 Georgia Tech University Atlanta, GA 1

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Outline emissions of Hg(0), Hg(II), Hg(p) Hg from other sources: local, regional & more distant wet and dry deposition to the water surface  Enhanced oxidation of Hg(0) to RGM?  Enhanced deposition? Reactive halogens in marine boundary layer Measurement of wet deposition Measurement of ambient air concentrations wet and dry deposition to the watershed 1. Forecasting for mission planning 2. High-resolution hindcast meteorological modeling (Fantine Ngan) 3. Atmospheric Mercury and Other Hindcast Modeling 2

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Forecasting for Mission Planning During the Summer 2010 Intensive  Based on the NOAA NCEP NAM 12km weather forecast model product  This forecast starts at UTC 00 for the given date, which is 7 PM the night before in Grand Bay time (GBT).  The hours displayed in the product – 9 AM to 8 PM GBT – thus represented hours in the 48 hr t00z forecast.  The file became available to NOAA ARL at ~2:00 AM GBT, and the processing of the data to make this product was generally done by 5:00 – 6 00 GBT.  Goal was to have product ready each day by 7:00 GBT 3

HYSPLIT-based forecast product for the Grand Bay Intensive Trajectories (pages 2-13)  One page for each local hour from 9 AM to 8 PM  Image in upper left corner is mixing height (m)  The other five images are back-trajectory maps, each map representing a starting point at a different elevation (meters) above mean-sea-level (250, 500, 1000, 2000, and 3000)  There are nine trajectories shown on each map: one starting at the Grand Bay NERR and on a +/- 1 deg lat/long grid around the NERR  The trajectories each go back 96 hours; but the trajectories may not stay on the map for all 96 hours.  On each trajectory there is a little dot showing the location at six-hour intervals; and a larger symbol at 00 UTC each day.  In the panel below the trajectories, the height above the surface is shown for each trajectory as it goes back in time  Note that elevations in trajectory maps are shown as being “above ground level”, and the starting heights labels in the panels below each trajectory are shown for the first trajectory run. This happened to started over land where the elevation was ~80m, so, the labels happen to refer to that trajectory, so the labels say ~170, 420, 920, 1920, and Wind Direction at Different Elevations (pages 14-25)  One page for each local hour from 9 AM to 8 PM  Each image shows a map of wind direction, at each grid point in the NAMSF 12-km forecast at a particular vertical level in the met data set  There are 6 maps, corresponding approximately to the elevations 10, 250, 500, 1000, 2000,  The met data is on “terrain following sigma levels”; so, the heights above the ground at any given location are influenced by the terrain height. Meteorological Data Contours (pages 26-37)  One page for each local hour from 9 AM to 8 PM  Image in upper left corner and upper middle are the mixing height (same map as shown on Trajectory pages). The two maps are slightly different due do differing interpolation procedures  The map in the upper right corner is forecast precipitation, shown as a 3- hr accumulation, ending at that hour; that is the amounts shown are the total forecast precipitation over the previous 3 hrs.  Other maps shown are for the following three surface parameters: pressure, downward shortwave radiation flux, and friction velocity Meteorological Data for Grand Bay NERR (pages 38-50)  Page 38 is description of data that are shown  Then, one page for each local hour from 9 AM to 8 PM  Each page shows the meteorological data at the surface and at each level of the gridded, forecast meteorological data set.  Note that on these pages and throughout, times are expressed in UTC (Universal Time Coordinate). These are currently 5 hrs ahead of Grand Bay, e.g., 9 AM Grand Bay is 2 PM UTC (or UTC 14) RGM Plumes from Large Regional Sources (pages 51-63)  Page 51 shows a map of some of the large sources in the region; as stated on map, some of the sources are no longer emitting. These sources were not included in these simulations.  One page for each local hour from 9 AM to 8 PM; each page shows model-estimated RGM concentrations for six different vertical layers n the atmosphere.  These maps do not represent the total RGM in the atmosphere, but only the fraction contributed by large regional sources.  The maps show average concentrations for the hour leading up to the stated hour, e.g., the map for UTC 14 represents average concentrations between UTC 13 and 14 (8 – 9 AM Grand Bay) Based on the t00z NAM-12km forecast generated by the National Weather Service This forecast starts at UTC 00 for the given date, which is 7 PM the night before in Grand Bay time (GBT). The hours displayed in this product – 9 AM to 8 PM GBT – thus represent hours in the 48 hr t00z forecast. The file becomes available to NOAA ARL at ~2:00 AM GBT, and the processing of the data to make this product is generally done by 5:00 – 6 00 GBT. 4

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University The first set of pages were hourly maps of mixing heights and back trajectories 5

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University The second set of pages were hourly maps of wind vectors at different heights 9

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University The third set of pages were hourly maps of mixing height, PBL-height, 3-hr precipitation, surface pressure, downward shortwave radiation flux and friction velocity 13

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University The fourth set of pages were hourly tables of surface variables and meteorological parameters in a vertical column above the site 26

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University The fifth set of pages were hourly maps of modeled RGM concentrations in the region, arising from anthropogenic sources in the region 31

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Forecasting for next intensive?  What format would be most helpful?  Maybe just have one page per hour, and then one could look at one part of the page as one scrolled through…  This would mean far less information, though, as we are limited to about six images per page…  If we did it this way, what would the six images be?  Or maybe this is too limited?  Another issue was bandwidth for downloading – I had to degrade the quality of the images significantly in order to keep file size as small as it was (~12 MB), and even this was perhaps too large 44

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University 2. High Resolution Hindcast Meteorological Modeling A 4-km meteorological data modeling analysis (with data assimilation) has been produced by Dr. Fantine Ngan, a post-doc at NOAA ARL, for the Summer 2010 Intensive Unfortunately, Fantine couldn’t be at this meeting as she is at the AMS meeting in Seattle this week, but she prepared the slides in this section for presentation here 10 m wind fields 18 UTC August 06 46

South-west corner (km) Number of cellsResolution (km) Starting point relative to mother domain X-originY-originEastingNorthingX-direction Y-direction D D D Projection center: 40N, 100W Standard latitude: 30N, 60N Layers: 43, with model top at 50 mb (1 st layer thickness is 33 m and 15 layers are below 850 mb) Domain configuration D01 D02 D03 Grand Bay – , , 5 m 47

Simulation period: 210/07/31 00 UTC – 08/13 12 UTC IC/BC for D01 is from GFS data + objectively analysis (OBS2GRID) Others are nestdown from coarse domain. 3D grid nudging, SFC nudging and OBS nudging are on for all domains The model was run in 5.5 day segments and re-initialized every 5 days. There were 12 hours overlapping between each run segment. The soil moisture and temperature in the input files were replaced with the WRF output in the previous run segment run segmentperiod p17/30 00 UTC – 8/4 12 UTC p28/4 00 UTC – 8/9 12 UTC p38/9 00 UTC – 8/13 12 UTC Physical options microphysics: WSM 3-class scheme radiation scheme: RRTM scheme for longwave radiation Dudhia scheme for shortwave radiation land surface model: PX LSM PBL scheme: ACM2 scheme cumulus scheme: Grell-Devenyi Ensemble scheme Model Setup 48

Temperature time series at Grand Bay Black *: observation, Red line: WRF model Relative humidity time series at Grand Bay Measurements are provided by Winston Luke 49

Wind speed time series at Grand Bay Black *: observation, Red line: WRF model Wind direction time series at Grand Bay 50

Soundings at Grand Bay at 2010/08/06 16 UTC Wind speed Potential temperature Measurements are provided by Winston Luke 51

2 m temperature 09 UTC August 062 m temperature 19 UTC August 06 PBL height 09 UTC August 06 PBL height 19 UTC August 06 Shaded background: model Color circles: MADIS OBS 52

10 m wind fields 12 UTC August 0610 m wind fields 15 UTC August m wind fields 18 UTC August m wind fields 21 UTC August 06 Shaded : model wind speed Vector: model wind vectors Color circles: MADIS OBS 53

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Questions for the group  We are going to be using this dataset for modeling, but would this met data set be useful for anybody’s else’s data analysis?  Fantine (and/or Mark) might be able to help extract needed data for any particular use… 54

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University 3. Atmospheric Mercury and Other Hindcast Modeling A. Back-trajectory modeling using HYSPLIT B. Comprehensive Fate and Transport Modeling using HYSPLIT-Hg Note – both kinds of modeling will utilize high-resolution met data developed by Fantine to the greatest extent possible 55

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University 3. Atmospheric Mercury and Other Hindcast Modeling A. Back-Trajectory Modeling Using HYSPLIT  Can model back-trajectories arriving at the Grand Bay site and try to correlate with observations at the site  Can model back-trajectories associated with any given air-craft measurement and try to correlate with these measurements  The idea is that maybe having information regarding where air masses were coming from will help with data interpretation 56

Time series of Reactive Gaseous Mercury (RGM), Fine Particulate Mercury (FPM) and Gaseous Elemental Mercury (GEM) from two co-located instruments (D1 and D2) (top graph) and of SO2, O3, NO, NOy, and CO (bottom graph) measured at the Grand Bay NERR from May 3-8,

Time series of Reactive Gaseous Mercury (RGM), Fine Particulate Mercury (FPM) and Gaseous Elemental Mercury (GEM) from two co-located instruments (D1 and D2) at the Grand Bay NERR from May 3-8,

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University 3. Atmospheric Mercury and Other Hindcast Modeling B. Comprehensive Fate and Transport Modeling Using HYSPLIT-Hg  Model mercury from regional and global sources for the time period of the Intensive  Compare model predictions against surface measurements at the Grand Bay NERR site as well as measurements aloft during flights  One goal is help with data interpretation, i.e., help explain why we saw what we saw  Another goal of this analysis will be model sensitivity and model evaluation, i.e.,  Can model reproduce measurements?  If not, why?  Sensitivity to key uncertainties? 68

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University  Emissions from sources during intensive, especially local/regional sources that particularly impacted our observations? Some issues with mercury fate/transport modeling 69

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Emissions data: a critical model input  In model evaluation, want to diagnose weaknesses in model without large influence of emissions errors  Need accurate, speciated emissions estimates for all sources impacting the site – for the time period of the episode Pascagoula MSW Incinerator shut down in Jan 2001, but still in 2002 NEI CRIST: New scrubber installed Dec 2009 will dramatically reduce RGM emissions Lowman reported dramatic drop in mercury emissions in 2008 TRI Brewton paper mill : Hg emissions in 2002 NEI, but do not appear in TRI IPSCO Steel: significant Hg emissions in 2002 NEI, but negligible emissions in 2008 TRI Large mercury emissions point sources from USEPA 2002 National Emissions Inventory (NEI) Grand Bay NERR site 70

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University  Emissions from sources during intensive, especially local/regional sources that particularly impacted our observations? Some issues with mercury fate/transport modeling  How to incorporate bromine and other chemical measurements into the modeling? What kind of collaboration makes sense?  Model configuration for prediction and subsequent comparison at a fixed site – e.g., the Grand Bay NERR site -- is “routine”, but prediction & comparison for a moving platform will be a little more challenging 71

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Summary of modeling questions for the group discussed in this presentation  FORECASTING: What kind of forecast product would be most useful for the next intensive?  HIGH-RES MET DATA: Does anybody need/want extracts from the high- resolution met data set, or can think of any other way that this data set might be useful for their analysis?  BACK-TRAJECTORY MODELING: We will most likely carry out some kind of back-trajectory analysis, using the high-resolution met data, but does anybody have any particular requests? The goal is to help with data interpretation.  FATE/TRANSPORT MODELING: We will definitely carry out this kind of modeling and would like to collaborate in any way that makes sense…  For both the BACK-TRAJECTORY and FATE/TRANSPORT modeling, do we have the complete set of flight locations (lat/long/elevation) and times associated with each measurement? 72

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Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University color of symbol denotes type of mercury source coal-fired power plants other fuel combustion waste incineration metallurgical manufacturing & other size/shape of symbol denotes amount of RGM) emitted during 2002 (kg/yr) – urban areas Grand Bay NERR monitoring site Watson Daniel Barry Lowman Crist Mobile Pensacola Mississippi Alabama Florida Louisiana Pascagoula MSW incinerator ** Brewton paper mill* * Hg emissions included in 2002 NEI, but do not appear to be in TRI ** Hg emissions included in 2002 NEI but incineration ceased in January 2001 *** Significant Hg emissions in 2002 NEI, but negligible emissions reported in 2008 TRI Eaton Gaylord Container Bogalusa IPSCO Steel *** Biloxi- Gulfport New Orleans Hattiesburg Slidell Pascagoula Location of the Grand Bay NERR sampling site, along with large point sources of RGM in the region, based on the EPA’s 2002 National Emissions Inventory 74

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Mercury Air Emissions from Charles R. Lowman Power Plant as reported to the Toxic Release Inventory For some sources, there have been big changes since 2002, the date of the last comprehensive mercury inventory 75

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Current Atmospheric Measurements of Ambient Air Concentrations and Meteorological Data Elemental mercury (two instruments) Fine particulate mercury (two instruments) Reactive gaseous mercury (two instruments) Sulfur dioxide Ozone Carbon Monoxide Nitrogen Oxides (NO, NOy) Aerosol Black Carbon Wind speed, Wind Direction Temperature, Relative Humidity Precipitation Amount “Speciated” Atmospheric Mercury Concentrations Trace gases and other measurements to help understand and interpret mercury data Meteorological Data 76

Grand Bay Mercury Intensive, Data and Planning Meeting, Jan 24, 2011, Georgia Tech University Wet Deposition Measurements added in 2010 by the Mississippi Department of Environmental Protection (Henry Folmar, Becky Comyns, others), with funding from the USEPA Precipitation Continuous digital measurement of precipitation amount Major Ions pH, SO 4 -2, NO 3 -, PO 4 -3, Cl -, NH 4 +, Ca +2, Mg +2, K +, Na + Weekly measurements of concentrations in precipitation (NADP-NTN) Total Mercury Weekly measurements of concentration in precipitation (NADP-MDN) Methyl Mercury Monthly measurements of concentration in precipitation (composite) Selected Trace Metals As, Cd, Cr, Cu, Pb, Ni, Se, Zn Weekly measurements of concentrations in precipitation (MDN Heavy Metal Protocol) 77