Data Day Summary


DATA DAY – May 4, 2009

Meeting Summary:

Purpose:

The purpose of “Data Day” was to provide a focused forum for review and discussion of paired sets of site-specific indoor air, subslab soil gas, and groundwater sampling data, followed by an evaluation of the efficacy, reliability and predictability of modeling efforts  based on that data. (Need to say something along these lines)

Agenda:

  • Overview (Paul Locke/MassDEP)
  • Presentation of EPA study data (Andy Friedman/MassDEP – MassDEP Data Day Presentation)
  • Discussion of MassDEP data (Andy Friedman/MassDEP – MassDEP-data-day-data-05042009)
  • Presentation of Two Case Studies (Robbie Ettinger/GeoSyntec – slides will be posted upon receipt)
  • Presentation of other data received (none received)
  • Discussion

Attendees: See below

Meeting Notes:

  • MassDEP requested but did not receive any site-specific data from external workgroup participants.
  • MassDEP provided 75 paired sample results from 35 Massachusetts sites, but with minimal site- or sample-specific information.
  • MassDEP provided links to the USEPA Vapor Intrusion database, which formed the basis of most of the Data Day discussion.
  • Andy Friedmann provided an overview of the EPA and MassDEP data.
  • Discussion noted potential circumstances in which modeling “can be valuable.”  Various model applications mentioned by some participants included:
    • For current exposures
      • Where actual data cannot be obtained
      • Condition is confounded by inside source
      • Where you can’t gain access
      • To direct/target/prioritize sampling (and control sampling costs) at a large site
      • To help document that you’ve sampled enough – that you know what’s going on
      • To help make sense of measured indoor air data
    • For estimating potential future exposures
    • For determining remedial goals or levels for corrective action
  • Robbie Ettinger discussed lessons learned from studies at two sites
    • At the Raymark site (CT), a slide of sampling results from one residence was displayed, highlighting background effects and the uncertainty in the values
      • described the importance of showing the variability/uncertainty of values using box-and-whisker plots
      • described the importance of showing results for all chemicals, including radon (even not site-related) as they are part of the story
      • If ratio (alpha) is different for chemicals that should migrate similarly, then something is amiss: there may be an indoor air background source, lab error, vadose zone biodegradation, etc…
      • Focus on calculating empirical alphas at higher concentrations:  C-empirical  = alpha-VI + ((background conc.)/(soil gas conc.)).  At higher concentrations, background levels are low relative to VI concentrations and C-empirical approximates Alpha-VI. At lower concentrations, background levels contribute proportionately more and C-empirical overestimated alpha-VI.
      • Noted that there was no correlation between modeling results and measured results at individual houses.
    • Based on R. Ettinger experience and appropriate use of models, generic attenuation values generally fall:
      • Alpha-sub slab = 4E-03
      • Alpha-soil gas = 7E-04 to 2E-03
      • Alpha-groundwater = 1E-05 to 1E-03
    • At CO DOT site, R. Ettinger participated in a study correlating measured & modeled values
      • Although more than 1,000 data points had been collected, only 150 were found to be usable in the modeling effort,
      • Data points were screened in or out based on data correlation (TCE, 1,1,1-TCA, 1,1-DCA, 1,2-DCA)  with 1,1-DCE
      • Even after eliminating 85% of the data points and using only the most reliable data, a 10x or 100x difference in attenuation factors was seen, even within the same home (similar to Raymark data).
      • To minimize influence of outliers, use percentile values, not mean
  • Participants noted that there is substantial variability in [fill in the blank]. Temporal variability. Spatial variability. Analytical variability. Variability across sites. Variability within a site. Variability within a single building. Given this context, it is not surprising that model results do not “predict” measured values when such correlation studies are conducted using limited site data. (One could even say that indoor air sampling is not very predictive of indoor air concentrations.)

MassDEP Comments/Conclusions:

  • Models have a role in the site assessment process. Model results are a line of evidence that can be used to develop and support a Conceptual Site Model. The weight given to model results will depend upon site-specific circumstances.
  • Models should help explain analytical results, not over-rule (or discount) measured values.
  • Models should not be used to replace sampling unless and until a comprehensive understanding of the site and the vapor intrusion pathway is achieved.
  • While not “predictive”, models can be used appropriately and conservatively to provide results that are unlikely to underestimate VI impacts and potential inhalation exposures.
  • MassDEP is looking into acquiring an intern to pull site files and compile data, including site characteristics. Combined with the USEPA data, this information may be useful in developing guidance on the appropriate role of modeling in the site assessment and remediation process in Massachusetts.
  • MassDEP repeats its request to the Workgroup members to provide site data directly (Excel template is still available on the website) or the RTN for sites that the intern may review.

Data Day Sign-In Sheet

Monday, May 4, 2009 – MassDEP Boston Office

(note that all attendees may not have signed-in)

Name Affiliation
Ileen Gladstone GEI
Brian Magee AMEC
Gerard Martin MassDEP SERO BWSC
Robert Ettinger GeoSyntec
Todd Creamer GeoSyntec
Andy Friedmann MassDEP NERO BWSC
Steve Johnson MassDEP NERO BWSC
Irene Dale MassDEP NERO BWSC
Larry Feldman GZA
Denise Kmetzo Roux Associates
Peter Zeeb GeoSyntec
Julianna Connolly GeoSyntec
Rebecca Woolley MassDEP WERO BWSC
Rich Lester Cambridge Environmental
Christie LeBlanc Harvard University
Janine Commerford MassDEP Boston BWSC
Tom Angus MassDEP Boston ORS
Greg Braun MassDEP Boston ORS
Nancy Fitzpatrick MassDEP NERO BWSC
Maureen Vallatini MassDEP NERO OGC
Catherine Wanat MassDEP WERO BWSC
Gina Plantz Haley & Aldrich
Rose mcCafferty Haley & Aldrich
Tod Kopyseirski Con-Test Analytical Lab
Chris Ayers MassDEP Boston OGC
Liz Callahan MassDEP Boston BWSC
Tim Condon Lightship Engineering
Kathleen Nolan self
Paul Locke MassDEP Boston BWSC
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