Updated Approaches for Monitoring Strategies/Options for Long Term Protection from CVI (under RCRA Corrective Action)

Transcription

1 USEPA Work Shop, AEHS 27 th Annual International Conference on Soil, Water, Energy and Air March 21, 2017, San Diego, CA Updated Approaches for Monitoring Strategies/Options for Long Term Protection from CVI (under RCRA Corrective Action) Acknowledgement and thank you to expert team: Robert Truesdale, RTI International; Henry Schuver, U.S. EPA ORCR; Chris Lutes, CH2M; David Folkes, Geosyntec Consultants, Jeff Kurtz, Geosyntec Consultants Dr. Ian Hers, Dr. Paris Jourabchi, Golder Associates

2 Presentation Outline Summarize 2015 and 2016 presentations on long-term stewardship, protectiveness and monitoring/mitigation strategies Summarize some key findings of research on indicators and statistics Present a preliminary approach and framework for long-term monitoring for protection of chlorinated vapor intrusion (CVI) March 21,

3 Previous Analysis USEPA 2015 Work Shop Hers et al Residential Building Lifecycle Cost Evaluation for Natural and Controlled Conditions. EPA Work Shop. AEHS 25 th Annual Int l Conference, March 23-26, San Diego, CA. Assumed monitoring strategies and frequencies were developed for chronic and acute (short-term concern e.g. TCE) with estimated life-cycle costs for mitigated and non-mitigated (monitoring only) scenarios For acute concern, clear conclusion was early mitigation most effective strategy, for chronic scenario monitoring only is slightly higher cost Monitoring assumptions for frequency were hypothetical and did not consider sampling robustness, statistics, indicators, etc. unguided sampling Equal Protectiveness March 21,

4 Testing Pre-emptive Chronic Concern Acute Concern Initial Testing PVE Test Backdraft Test Physical Tests Physical tests heating season IAQ testing Physical tests PVE test Backdraft test For One Year: IAQ testing twice yearly Physical tests twice yearly Annual PFE California DTSC Guidance Commissioning Longterm Testing Hers et al Hypothetical-Generic Residential Scenario - Mitigation Monitoring IAQ testing Physical tests PVE test Backdraft test Automated pressure system monitor For Two Years: IAQ testing twice yearly Physical tests twice yearly PFE twice yearly High risk sites: semi-annual testing of air quality and SSD Backdraft heating season performance parameters for three years, 1 Backdraft heating season sampling every two 1 years thereafter None IAQ & physical tests 3 rd and 5 th year, then physical tests every 5 th year Total IA samples = 5 IAQ & physical tests testing 3 rd & 5 th year, and then IAQ & physical every 4 th yr Total IA samples = 11 in 30 yr 1 4 If commissioning was not conducted in heating season, System check-up conducted each site visit, Physical tests = pressure and flow testing, IAQ = indoor air quality, PFE = pressure field extension

5 Hers et al Hypothetical-Generic Residential Scenario Monitoring Costs * Per House Chronic Concern Acute Concern Commissioning $2,150 $2,300 Year 1 $4,300 $5,000 Year 2 0 $5,000 Year 3 $2,500 $2,500 Year Year 5 $2,500 $2,500 Year 6 on $600 every 5 yr (just physical) * Assumes 5 house program $2,500 every 4 yr (IAQ+physical) 5

6 Hypothetical-Generic LTS Lifecycle Cost Cumulative $ per Residence Chronic Concern Cumulative Cost $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 Slope curves similar - 3 & 5 yr frequency ~ O&M + physical checks IAQ 3 yr freq. IAQ 5 yr freq. No further post-mitigation IAQ monitoring Years Mitigation Chronic Lower Mitigation Chronic Higher Monitoring Only Twice Yearly Monitoring Only Quarterly Curves highly sensitive to monitoring assumptions but suggest similar costs

7 Cumulative Cost $70,000 $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 Hypothetical-Generic LTS Lifecycle Cost Cumulative $ per Residence Acute Concern IAQ 1 yr freq. Breakeven point is < 2 yrs IAQ 2 yr freq. IAQ 4 yr freq Years Mitigation Acute Lower Mitigation Acute Higher Monitoring Only Monthly Monitoring Only Bi-monthly Monitoring only costs higher there should be benefit in mitigation respecting on-going monitoring requirements

8 Previous Analysis USEPA 2016 Work Shop Hers & Jourabchi 2016 Analysis of Vapor Intrusion Mitigation and Monitoring Options for Improved Stewardship. EPA Work Shop. AEHS 26 th Annual Int l Conference, March 23-26, San Diego, CA. Develop a better understanding of performance and sustainability of different VI mitigation methods Improved framework for monitoring that is efficient and that Considers exceedance ratio concept Non chemical based diagnostic data (e.g., pressure and flow) In part based on work conducted for Ontario MOECC Mitigation effectiveness and protection needed March 21,

9 Lessons Learned and Optimization Passive Venting Pressure gradients/flow variable Convection important, wind turbines help Modeling suggests barrier provides some reduction in VI but P key Optimization Aerated floor or very high K gravel Sufficient risers (1 per m 2 ) Riser Dia > lateral Dia (depending on # of laterals connected to riser) Include wind turbines to improve efficiency Active Venting Pressure gradients can be controlled, minimal P required Barrier may not be warranted but sealing building envelope is important (conduct smoke tests) Optimization Aerated floor (added benefit dilution) Riser design depend on venting layer & foundation (grade beams) Small fan often sufficient Air entry pipes to minimize shortcircuiting and losses KEY POINTS: Both active and passive vent acceptable; active systems can be reliably engineered to achieve reductions Use civil engineering design tools for this purpose.

10 Monitoring Framework Study Building Exceedance Ratio Existing Building Active Venting - SSD Future Building Active Venting Barrier Optional Future Building Exceedance Ratio March 21, 2017 Passive Venting - Barrier Subslab Chemistry Low Biannual x 1 yr Chronic Low High Low High Low High Indoor Air Chemistry Optional High Optional Bi-annual x 1 yr; 3 rd, 5 th yr < A > A > B < B > C < C Acute Indoor Air Chemistry Bi-annual x 1 yr; 3 rd, 5 th yr Bi-annual x 1 yr; 3 rd, 5 th, 10 th yr. Note subslab monitoring also required Exceedance ratio = Predicted or measured indoor air/risk-based threshold Intensity monitoring depends on whether above or below exceedance ratio Framework assumes: Commissioning testing Initial pressure field extension testing Physical parameter monitoring each event Possible exceedance ratio thresholds A = 10, B = 200, C = 100 (see Hers et al for details)

11 Goal is Develop Updated Long-term Monitoring Strategy Goal is to develop practical, sustainable and implementable monitoring approach and framework that reflects the nature of the risk (chronic vs short-term), under natural or modified conditions (including the effectiveness/reliability of pathway modifications/controls in place), builds on monitored natural attenuation concepts for groundwater, incorporates an appropriate rigor and duration of long term/follow-up monitoring, uses surrogates and indicators where beneficial, and Is based on appropriate statistics to inform decision-making. Current scope is residential houses but concepts could apply to other building types as well. March 21,

12 Reasonable Maximum Exposure US EPA 2015 VI guide definition: reasonable maximum exposure (RME) A semi-quantitative term, referring to the lower portion of the high end of the exposure distribution; conceptually, above the 90th percentile exposure but less than the 98th percentile exposure. US EPA RAGS recommends use of 95% upper confidence limit (95% UCL) on the arithmetic average concentration be calculated to estimate exposure concentration used in risk assessments. Important to distinguish between 95% UCL and upper percentile of distribution (e.g., 95 th percentile) Key finding: Estimation of RME assuming random sampling requires a large number of samples and is impractical; guided sampling significantly reduces the number of samples required March 21, Lutes Indicators, Tracers and Surrogates, Why Use Them, Probability Analysis, Definitions and Examples, AEHS EPA 2017 Workshop, San Diego, Mar 21.

13 Analysis of ASU Sun Devil Manor TCE Data Kurtz et al (N= hr TCE points, 5000 simulations of random seasonal sampling) Probability of 1 or more indoor air sample exceeding the Target Concentration and 95UCL of Mean compared to percentile of total dataset for various sampling strategies 4 62% probability that >=1 samples>90th seasonsummer& Seasons Sampled s Winter Winter Winter Winter Winter Winter Winter Winter Total Samples or more sample>90th% 34% 27% 47% 62% 73% 81% 86% 90% 93% 1 or more sample>95th% 19% 11% 26% 36% 45% 52% 59% 65% 70% 95 UCL OF MEAN=% OF DISTRIBUTION 90TH% March 21, >95.5 % >95TH % >95TH % >94.5T H% >94TH % Key findings: A more efficient way of predicting upper percentile may be to use 95% UCLM or exceedance fraction, but depends on assumed distribution (e.g., normal, log-normal) and may be overconservative Kurtz et al New Analysis of the ASU SDM Data, AEHS EPA 2017 Workshop, San Diego, Mar 21. >94TH %

14 CVI Indicators, Tracers and Surrogates (ITS) There is significant opportunity to improve monitoring programs through use of Indicators (indicating the potential for CVI, e.g., weather, radon), Tracers (move with CVI chemicals, e.g., radon), Surrogates (semi-quantitative predictor of CVI, e.g., radon) Indicators are both a leading metric, used to identify when to sample and to limit number of samples, and lagging metric, used to interpret monitoring results Research has primarily focused on weather indicators, measured pressure indicator and radon as indicator, tracer and surrogate Important not to forget subsurface conditions as indicator could there be transient mass flux that is higher in non-heating season? March 21,

15 CVI Weather Indicators Weather indicators potentially include Outdoor temperature Indoor-outdoor temperature difference Solar stack effect? Wind speed Wind chill Wind direction Barometric pressure Snow and frost cover Snowmelt Rainfall Water level change Conceptual Site Model (regional considerations, building factors) Analysis (autocorrelation, time element, significance) Practical Indicators (e.g., T) (how robust, geographically applicable?) March 21,

16 Summary of Indicator Research (Kurtz et al. 2017) 1 Daily T vs TCE ASU Sun Devil Manor (SDM) House Clear correlation between T and CVI Indoor TCE concentrations rise steeply once T > 18 o C Radon slightly better predictor than T Daily Rn vs TCE Rn Indicator (>90 th %) approach for RME 24-hr TCE 40% True Positives 60% False Positives 95th March 21, Kurtz et al New Analysis of the ASU SDM Data, AEHS EPA 2017 Workshop, San Diego, Mar hr Rn

17 Possible Data Analysis Nomographs (Kurtz et al. 2017) Bin the data for T range, then generate curves with reference to average and percentile Avg 95 th Differential T>90 th percentile, TCE>95 th 2 percentile samples, 1 > 50 th 1 sample, 1 > 50 th 3 samples, 1 > 95 th 2 samples, 1 > 95 th 1 sample, 1 > 95 th 34% True Positives 66% False Positives Increasing true positive rate 95 th Avg March 21,

18 Summary of Indicator Research (Lutes 2017) US EPA Indianapolis House Correlation between T and CVI Increasing Rn as a predictor was statistically significant at 1% level and predicted 40-60% of the variability in indoor air VOC concentrations Increasing temperature more important than absolute T reservoir effect? Foster Wheeler Industrial Building Rn-guided sampling indicated TCE concentrations were higher when radon guided 0 Radon (pci/l) and VOCs (µg/m3) Results for Upstairs Sampling Locations RANDOM RADON GUIDED Rn R T P March 21, Lutes Indicators, Tracers and Surrogates, Why Use Them, Probability Analysis, Definitions and Examples, AEHS EPA 2017 Workshop, San Diego, Mar 21. Unit 106 (Column in Kitchen) 2nd Floor, On North Wall, East Side of Atrium Unit 134 (Column in Center of Unit) Unit 224 (TV Stand near Exterior Wall) On Papertowel Dispenser in Women s Restroom Unit 154 (Shelf Between Bed and Door) Unit 106 (Column in Kitchen) Unit 148 (Shelf in Kitchen) Sampling Locations On Coat Rack in Theater Prop Room Shelf at SE Corner of South File Storage Room On Gate to South Overhead Door in Theater Between Basement & 1 st Floor on West Stairs

19 Conceptual Long-term Monitoring Framework Framework criteria could include the following: Staged air monitoring program; conceptually 2 stages, 1 st stage more intensive sampling within relatively short time frame, make risk management decision; additional monitoring at reduced frequency Reflect risk concern - chronic, short-term Guided sampling incorporating indicators and surrogates - weather indicators ( T), Rn practically how can Rn be used? Narrow the assessment period - within reason! Develop nomographs or estimators for number of samples based on: 1. Expected variability (Higher vs Lower) 2. Indicator (e.g, T, radon) 3. Risk concern - statistical estimator (mean vs upper percentile) Incorporate appropriate statistical methods and estimators for data analysis (UCLM, exceedance fraction) March 21,

20 Conceptual Long-term Monitoring Framework Risk concern Expected Variability Indicator Establish Analysis Objectives and Desired Confidence Establish Sampling Criteria (e.g., over-sample in narrowed assessment period) 1 Data Analysis (e.g., UCLM exceedance fraction) 1 May be appropriate to collect few samples from other seasons to confirm hypothesis March 21,

21 Conceptual Long-term Monitoring Framework Framework criteria for stage 2 monitoring (cont): Intensity for additional monitoring based on whether building is mitigated or not, e.g., less frequent monitoring typically supported for mitigated vs nonmitigated building, coupled with how close to threshold Mitigated Nonmitigated Factor x Threshold Threshold Factor x Threshold March 21,

22 Conclusions New concepts and research offer opportunity to design improved indoor air monitoring programs and conduct smart programs that are efficient and targeted to meet assessment objectives Monitoring should incorporate considerations relating to risk concern, variability, indicator and desired confidence Data analysis based on Sun Devil Manor incorporates a high degree of variability, in part due to sewer pathway Timescales for flux events may be important, e.g., may be correlation between indoor CVI concentrations and initial increase in T, but strength of seasonal correlations less known Further research is needed on data rich studies to support development of robust and more widely applicable framework and test assumptions

23 Extra Slide Comparison between Rn and DT as indicator of TCE