Aerosol Data (IMPROVE network speciated aerosol samplers)

Archived data products created from analyses of IMPROVE aerosol data used for RHR SIP analyses are described below. Identification of the 20% best and worst days used in these analyses have been made based on the calculation of total extinction (or deciview) for each day, not on mass concentration. This is true even for data products summarizing mass concentrations for best and worst days. It is important to note that identification of days used in these analyses assumed an equal number of best and worst days. This differs from the method used on the VIEWS web site, where the number of 20% worst days may includes an additional day. (For example, if a given site collected 101 complete samples for a year, the analyses archived here would have identified the cleanest and dirtiest 20 days; analyses on the VIEWS web site would have identified the cleanest 20 and the dirtiest 21 days.) This difference in methodology is not expected to substantively change the interpretation of VISTAS analyses.

VISTAS states elected to use the revised IMPROVE algorithm (December 2006) for calculating aerosol extinction rather than the original algorithm, developed in the early 1990s. A few data analyses were performed to investigate the differences between these algorithms, and those are specifically identified below. The revised IMPROVE algorithm is identified by “NIA”, the original algorithm by “OIA”.

Results for all VISTAS IMPROVE monitoring sites and selected surrounding sites outside of VISTAS are included. A full description of analysis products is provided in the ARS final report, VISTAS Conceptual Description Support Document (2007). All of these data summary products were produced by ARS, with the exception of the Glidepath products. These were created by Scott Reynolds, with the South Carolina Department of Health and Environmental Control.

Glidepaths

The RHR guidance requires reasonable progress to be tracked using the Haze Index (deciviews), which is determined as a logarithmic transformation of the sum of all light extinction terms in the IMPROVE light extinction algorithm. The rate of visibility improvement between baseline conditions in 2000-2004 and natural background conditions in 2064 is defined as the glidepath for the uniform rate of progress toward visibility goals.

Back Trajectory Analysis

Meteorological back trajectory analyses use interpolated measured or modeled meteorological fields to estimate the most likely central path over geographical areas that provide air to a receptor. Back trajectories account for the impact of wind direction and wind speed on delivery of emissions to the receptor, but do not account for chemical transformation, dispersion and deposition of emissions. VISTAS used back trajectories to investigate typical wind pattern throughout the baseline period and to assist with area of influence analyses.

Trends

10-year extinction trends for the period 1995-2004 were computed for each site that had at least 5 years of complete data. Emissions reductions were implemented in the eastern U.S. during this period under the Acid Rain provisions of the 1990 Clean Air Act Amendments and under the NOx SIP call for ozone. Theil slopes were calculated to determine the trend, and p-values were calculated using Mann-Kendall trend analysis to determine the significance of each slope. Lower p-values indicate higher confidence levels in the computed slopes.

International Attribution

To account for contribution to mass measured at VISTAS sites from international emissions, VISTAS generated model results with zeroed out Mexican and Canadian emissions, and boundary conditions (as defined by the GEOS-CHEM global model). The difference between the model run with and without the international emissions was used to represent species mass attributable to international sources.

WinHaze

Data

Emission inventory data used in regional haze state implementation plans are presented below. The Base G2 inventory is considered Best and Final for 2002. The Base G4 (BaF) inventory is Best and Final for 2009 and 2018. States would have used Base G2 or Base G4 depending on which inventory was available and complete at the time of the SIP preparation and submittal.

Base G2

Inventory data summary in NIF format for VISTAS states, annual average, organized at county and SCC tier level for 2002 actual, 2002 typical, 2009 projected and 2018 projected for the following sectors:

Base G2 Emission Summaries

Base G4 - Best and Final (BaF)

Best and final inventories for 2009 projected and 2018 projected were updated to reflect BART controls, consent decrees, corrections to Base G2 and source specific controls. Only EGU and non-EGU point source records were changed. Area, on-road mobile and non-road mobile inventories did not change from Base G2 scenarios.

Best and Final Emission Summaries

Emissions and Air Quality Modeling

Meteorological Modeling

Meteorological Model Performance Documents

Please contact your state modeling representative to obtain the 2001-2003 CALMET data for either the 12km or 4km data sets. Please note: these are very large data files (~135 GB for the 12km dataset, and up to ~280 GB for a single domain of 4km data).

VISTAS states are responsible for determining if a source may use the new IMPROVE equation in the BART exemption modeling. VISTAS contracted with Dr. Ivar Tombach to develop a post processor to allow CALPOST outputs to be used with the new IMPROVE equation. Dr. Tombach also provided instructions on how to apply the post processor. VISTAS is providing access to the post processor and instructions for its application on this archive web site, but VISTAS does not have a policy position on the application of the post processor for the new IMPROVE equation. A BART source in a VISTAS state needs to obtain permission from the state to use this post processor. A BART source in a non-VISTAS state needs to contact their state to determine if the state would consider the new IMPROVE equation for BART.