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Similar to Lund Using Climate Zones, Architectural Knowledge, and Low-cost Indicators to Build Efficient Vapor Intrusion (VI) Sampling Strategies
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Lund Using Climate Zones, Architectural Knowledge, and Low-cost Indicators to Build Efficient Vapor Intrusion (VI) Sampling Strategies
- 1. www.jacobs.com | worldwide Innovation that provides sustainable solutions to complex challenges worldwide Using Climate Zones, Architectural Knowledge, and Low-cost Indicators to Build Efficient Vapor Intrusion (VI) Sampling Strategies AWMA Annual Conference June 2019 CH2M is now Jacobs Chris Lutes (Jacobs), Chase Holton (Jacobs, Geosyntec), Elsy Escobar Ph.D. (Jacobs), Shirley Steinmacher (Jacobs) and Loren Lund Ph.D. (Jacobs)
- 2. Current VI Site Evaluation Practice • Many jurisdictions assume that a one-time, very short exposure to TCE (24 hours or less) at trace concentrations could cause birth defects in developing fetuses. But for other pollutants longer-term average exposure is key. • The degree of “temporal variability” is generally assumed, based primarily on studies of only two houses, to be about 100x. • The number of sampling rounds required is unclear. EPA guidance states “multiple rounds”. Some states require four rounds (i.e., MI), while others (e.g., NJ) allow one winter round • Studies suggest that even four random air samples might not provide adequate confidence in a determination of concentration below screening levels • At some sites as many as 10 rounds of samples have been collected
- 3. How VI Sampling is Currently Scheduled • “Convenience sampling” – based on when funding is approved, when the technician is available, or soon after a particular stakeholder first requests sampling to be done. • US practice based primarily on data from a limited number of climate zones • Rough national rules of thumb – “winter is worst so sample then” and “don’t sample for a few days after heavy rain”. • Little consideration is given to the particular construction of the building or climate characteristics of the locality in scheduling sampling.
- 4. Developing a New, Improved Approach • Conducted review capturing knowledge from these key fields: ‾ Building Science: i.e., ventilation, heating/cooling, comfort; ‾ Architecture: i.e., passive solar strategies; earth-sheltered strategies ‾ Climatology ‾ Multiple long-term VOC and Radon VI studies This information helps us understand more specifically how particular buildings behave in particular climates. • Both historical/vernacular buildings and architect-designed buildings are designed to work with the particular circumstances of climate to maintain comfort. • Comfortable conditions – controlled temperature and adequate ventilation are related to vapor intrusion vulnerability
- 5. Climate Zone Systems: USDA • USDA system familiar to ordinary citizen gardeners Based on extreme temperatures • Correlation of stack effect with short-term maximum exposure possible • Where “Winter is worst” VI can rise exponentially as temperature gets colder. Reprinted from: https://planthardiness.ars.usda.gov/PHZMWeb/ http://planthardiness.gc.ca/images/PHZ_2014_USDA_ Map_30M.pdf
- 6. Climate Zone Systems: IECC • International Energy Conservation Code (IECC) • Used in building codes and by architects • Temperature aspect based on degree-days – so a measure of full winter stack effect – and thus exposure • Also includes moisture considerations Figure reprinted from https://www.greenbuildingadvisor.com/article/climate- zone-map-including-canada
- 7. Climate Zone Systems: AWS Truepower Wind Resource Map • Wind speed and direction can be important to VI variability • Wind not considered in standard climate zones • US map looks very different than temperature based zones!
- 9. Interpreting Local Wind Information In buildings without heating systems VI driving forces more influenced by wind loads then temperature. Thus temporal variability may have a complex pattern governed by wind shifts and how they interact with the openings in the building. Example of Monthly Wind Roses - Wilmington NC from Iowa State University http://mesonet.agron.iastate.edu/sites/windrose.phtml?network=NC_ASOS&station=ILM Figures from: Modeled Wind Effect on Building from Shirazi and Pennell, Environ Sci: Process Impacts, 2017, 19, 1594- 1607.
- 10. Examples of Climate Adapted Vernacular Houses Historic house well adapted to New England • Compact design, minimizes surface/volume ratio. • Long sloping roofs deflects wind over building • Small window area on all sides Historic house adapted to Coastal California Mediterranean climate – near Santa Barbara • Encourages natural ventilation • Uses thermal mass for cooling • Protected from summer sun. Photo from http://thechoatenews.choate.edu/wp-content/uploads/2018/05/Screen-Shot-2018-05-11-at-11.33.56-PM.png Phtoo from https://scholarworks.gvsu.edu/reagans_rancho_del_cielo/14/
- 11. Understanding Air Exchange Rates (AER) • AERs, which protect buildings from vapor intrusion, highest in summer in many houses that use natural ventilation • This is especially true in northern residences without air conditioning. Opening windows and activating attic fans can have dramatic effects. • Thus temporal variability would be expected to be high in these structures. • Given the same soil gas concentrations, newer energy efficient residences would be expected to have the highest indoor concentrations. While older houses may have more leaky slabs they also have the protective effect of wall and ceiling leakage.
- 12. What Have We Learned From Climate Zones? • Several different systems of climate zones can each provide insight for VI • Temperature is not always the controlling variable for temporal variability • Buildings can be classified as: ‾ “envelope dominated” – generally small, such as residences and small office buildings that would be more controlled by weather vs. ‾ “internally dominated” large, tight buildings where the HVAC must operate year around to provide adequate ventilation (regardless of VI) and cooling (because of heat given off by people and electrical equipment) ‾ “Internally dominated” buildings are less effected by climate and thus would be expected to be less temporally variable.
- 13. Vapor Intrusion Conceptual Site Model – Single Structure Graphic Reprinted from Quirouette “Air Pressure and The Building Envelope”, 2004 WELL-MIXED DIFFUSION SOURCE (Soil or GW) ADVECTION + DIFFUSION v v v v v Air Exchange Qsoil Csoil Cracks EBldg = QBldg.CBldg Qsoil Csoil Rain Infiltration Intrusion through pipes and joints Smear Zone Air Mixing Stack Effect Air Mixing Air
- 14. Indicators, Tracers and Surrogates (ITS): Measurable Physical Features: • Relatively low cost, continuous measurements • Can be statistically compared to indoor CVOC conc. for possible associations Temperature Pressure Radon • Measurements revealing factors/forces driving VI at a particular site and building • Provides insight into VI driving forces & building-factors operating at the time of cVOC sampling (i.e., concurrent non-static measurements) Improves interpretation (meaning/value) of contemporaneous cVOC samples Focus sampling on times & places having exposures of concern Reducing # of indoor CVOC samples needed; i.e., to make decisions with quantified/doc. percentile (%ile) of exposure represented & confidence levels 14
- 15. Heating Degree Days in USEPA Indianapolis Duplex Study As Indicator 15 0 2 4 6 8 10 12 14 16 18 20 0 50 100 150 200 250 300 350 PCEconcentration(µg/m3) Heating Degree Days) Weekly Total Heating Degree Days vs. PCE Concentration 422 Base South; Mitigation Off or Not Installed Data Only ColdestWarmest
- 16. Is Winter Always Worst? • Underlying assumption - stack effect caused increase in soil gas entry rate will dominate temporal variability • Air exchange rates can also be high in cold weather in older structures. • Several exceptions noted – sites with strong shallow subslab sources, in far northern climate, where temperature effects on volatility dominate • “Winter is worst” is not always true; but very often true – we can better identify cases that are likely to be exceptions now. Barnes, David L., and Mary F. McRae. Atmospheric environment 150 (2017): 15-23.
- 17. Sites Providing Large/Long Term Data Sets across the IECC Climate Zones IECC zones Reprinted form https://basc.pnnl.gov/images/iecc-climate-zone- map Sun Devil Manor UT Indianapolis Duplex San Antonio MEW and Moffett Field CA Redfield and Colorado DOT San Diego Yorktown VA Wendell and Gaffney AK CRREL (NH) Bradford VT 17
- 18. Cases With Large Temporal Data Sets We are Comparing – Part 1 Case Building Type IECC Climate Zone Conceptual Site Model ΔP or BP ΔT1 Rn Sun Devil Manor, Layton UT Single family residential, modern 5B TCE in groundwater plume intersecting with neighborhood scale preferential pathway EPA duplex, Indianapolis IN Duplex, historic 5A PCE, TCE, CF in groundwater plume from multiple dry cleaners intersecting with neighborhood scale preferential pathways (CSO) San Antonio, Bexar County, TX Single family residence (multiple) 2A Groundwater plume, (non-”winter worst”), PCE Middlefield-Ellis- Whisman and Moffett Superfund Sites, CA Commercial steam heated with AC, occupied 24x7; contains office space 3C Groundwater plume, TCE, cis-1,2-DCE Orion Park Moffett field, CA Two-story connected townhouses 3C Groundwater plume, TCE; sub-slab spatial variability 1 measured (can also be estimated retrospectively from Tout from weather records with Tin assumption) 18
- 19. Cases With Large Temporal Data Sets We are Comparing – Part 2Page 2 Case Building Type IECC Climate Zone Conceptual Site Model (primary contaminants, source) ΔP or BP ΔT1 Rn Yorktown VA Large commercial, unheated 3A Soil and groundwater source beneath building, TCE; solvents in degreasers San Diego North Island CA Large Commercial Office 3B TCE, soil and groundwater; building has history of carpentry, machining, Tidal Cold Regions Research Laboratory, NH Large commercial office and laboratory 6A TCE in soil, DNAPL and groundwater plumes; process leaks, spills Redfield CO Single family homes (hundreds) 5B TCE, 11-DCE in groundwater plume; metalworking spills CDOT MTL CO Mainly large apartment buildings, few single family 5B TCE, 11-DCE in groundwater plume; metalworking spills * Wendell and Gaffney Sites in Fairbanks, AK Small commercial buildings 8 Soil sources from dry cleaners, also shallow groundwater impacts, non- winter worst Vermont sites (2), Bradford VT 1) 6,000 sq ft Office and 45,000 sq ft manufacturing and storage; 2) 2,800 sq ft railroad depot (now restaurant) 6A PCE in soil and groundwater plume from former dry cleaners * is not long-term data but pre- and post mitigation for brief periods 1 outdoor-indoor measured (can also be estimated retrospectively from Tout from weather records and Tin assumption) 19
- 20. 0.01 0.1 1 10 100 1000 SDM (Layton, UT), TCE , 24- hour avg. Indy, 422 Base. South, Before Mitigation, Chloroform Indy, 422 Base. South, Before Mitigation PCE Indy, 422 First Floor, Before Mitigation Chloroform Indy, 422 First Floor, Before Mitigation PCE MEW Location 15-1 TCE MEW Location 15-1 Cis-1,2-DCE Yorktown Shed 3 Midway TCE Yorktown Shed 3 Front Office TCE Yorktown Shed 6 Lunch Room TCE Yorktown Shed 6 Big Room TCE Gaffney Alaska PCE Wendell Alaska PCE VOCIndoorAirConcentration(ug/m3) Temporal Variability: Box and Whisker Chart of Multiple Sites Sixteen Hour to One Week Durations; VI Dominated; Four Season Data Sets N=723 N= 61 N=155 N=80 N=83 N=27 N=32
- 21. 0 20 40 60 80 100 120 140 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Multiple of Mean Sun Devil Manor 24 Hr TCE 0 5 10 15 20 25 30 35 Frequency Multiple of Mean Indianapolis 422 Basement PCE 0 5 10 15 20 25 30 35 Frequency Multiple of Mean Indianapolis 422 FirstFloor PCE 0 5 10 15 20 25 Frequency Multiple of Mean Concentration Indianapolis 422 FirstFloor Chloroform 0 10 20 30 40 50 60 70 Frequency Multiples of Mean MEW Location 15-1 TCE 0 10 20 30 40 50 60 70 80 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Normalized Concentration MEW Location 15-1: 1,2-DCE 0 5 10 15 20 25 30 35 40 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Multiples of Mean Yorktown Shed 3 Midway, TCE 0 5 10 15 20 25 30 Frequency Multiples of Mean Yorktown Shed 3 Front Office TCE 0 5 10 15 20 25 30 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Multiples of Mean Yorktown Shed 6 Lunch Room TCE 0 5 10 15 20 25 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Multiples of Mean Yorktown Shed 6 Big Room TCE 0 2 4 6 8 10 12 14 16 Frequency Multiples of Mean Gafney PCE 0 1 2 3 4 5 6 7 8 9 10 <X/128 X/128toX/64 X/64toX/32 X/32toX/16 X/16toX/8 X/8toX/4 X/4toX/2 X/2toX Xto2X 2Xto4X 4Xto8X 8Xto16X 16Xto32X 32Xto64X 64Xto128X >128X Frequency Multiples of Mean Wendel PCE Comparing Multiple Site Temporal Variability Distributions Using Histograms Normalized as Multiples of the Mean 0 5 10 15 20 25 Frequency Multiple of Mean Indianapolis 422 Basement Chloroform
- 22. We Now Have a Basis to Evaluate Key Questions For Your Site • What is the most efficient sampling strategy to determine required “reasonable maximum exposure”? How many sampling rounds are enough? • Can I “hurry the process” with controlled pressure testing vs. waiting for the weather/seasons? • How large a range of temporal variability should I expect in this particular building? • From the two samples I have already taken, can I project how bad my third and fourth samples could reasonably be expected to be? • How can Indicators, Tracers and Surrogates help us better understand the controls on vapor intrusion in particular buildings? More data sets are needed to refine these concepts!
- 23. Acknowledgements • Robert Truesdale RTI, Brian Schumacher, and John Zimmerman (EPA) • Jay Clausen (US Army CRREL) • David Barnes, (University of Alaska Fairbanks) • Jeff Kurtz (Geosyntec) • Henry Schuver, Matthew Plate, Alana Lee, Ralph Dollhopf, (EPA) • Vitthal Hosangadi (NOREAS) • Blayne Hartman, Mark Kram (Groundswell Technologies) • Jill Johnston (UNC, USC) • Alan Rossner and Michelle Crimi (Clarkson University)
- 24. www.jacobs.com | worldwideJuly 19, 2020 © Copyright Jacobs Thank you! Christopher.Lutes@Jacobs.com
Editor's Notes
- Current practice is very much one site fits all, or dependent on jurisdictional judgment, not climate and building type.
- Architects go to school to learn how to make a building work well in a given climate. But societies also have centuries of experience in what building features make them comfortable and use less energy that gets passed down as traditions. The conditions that make for comfort – temperature control and ventilation
- The canonical VI sites on which policy is based (Sun Devil Manor, Endicott NY, Redfield CO, Indianapolis) are mostly groundwater sites in the blue and green zones.
- The canonical VI sites on which policy is based (Sun Devil Manor, Endicott NY, Redfield CO, Indianapolis) are mostly groundwater sites in the blue and green zones.
- If wind controls temporal variability…note importance of coasts and great lakes. Introduce the key, red is highest blue is lowest.
- A substantial percentage of commercial buildings don’t have central forced air heating and cooling systems
- Here is an example of how wind interacts with buildings
- But not all commercial buildings will be internally dominated, many commercial buildings like warehouses have lots of openings and so may be envelope dominated
- Taller buildings have stronger stack effects, and thus would be expected to have more temporal variability if all else were equal. Only about 60% of US commercial buildings are heated throughout. In a population of buildings at a given site, the strongest indoor/outdoor temperature differentials, and thus the strongest stack effects would be expected in temperature controlled buildings.
- Simple example here of an indicator
- Note how many of the key examples that guide VI policy are from zone 5 or 6 (SDM, Indianapolis, Redfield, Endicott (not shown on figure))….
- This is the first time so many sites with large datasets (n=27 to 593) have been viewed on comparable scales The interquartile range for most sites is relatively narrow – SDM the exception. Long term means are near or sometimes even above the 75th percentile. Total range of temporal variability is typically around 2 orders of magnitude. Similar degree of temporal variability for commercial buildings to Indianapolis case. Similar temporal variability across a wide range of geographies This allows us to begin to developed statistical estimates of temporal variability for more buildings in diverse climates
- Overview of format: Centered around the mean of the distribution, allows shapes of distributions to be compared. Sun Devil Manor has the widest distribution – also more truncated because it has the most nondetects. At most of these sites samples the chance of seeing a sample >4X the long term mean are quite low. These are mostly quite old buildings, but there doesn’t appear to be a radical difference industrial vs. residential.