Data Quality & Implications for Risk Assessment -...
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DATA QUALITY AND IMPLICATIONS FOR RISK ASSESSMENT Jackie Wright, Environmental Risk Sciences ACLCA SA 7 April 2011
Transcript of Data Quality & Implications for Risk Assessment -...
DATA QUALITY ANDIMPLICATIONS FOR RISK ASSESSMENT
Jackie Wright, Environmental Risk Sciences
ACLCA SA
7 April 2011
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TEOverview
• Why is data quality important?
• Where does the data come from?
• Key aspects that need to be considered
Data quality is not just a QA/QC Assessment
• Examples
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TEWhy is Data Quality Important?
§ If the data is not adequate you cannot assess risk with any degree of confidence.
§ Why:
• Cannot define the nature and extent of contamination?
• Cannot identify which chemicals are important in a risk assessment?
• Cannot rely on concentrations to quantify exposure and risk?
§ So no point doing a risk assessment if the data is not OK
§ If the data is adequate the data evaluation assists in understanding the uncertainties that are being introduced in the risk assessment.
2/19/2012
Initiation of Site Investigation
Preliminary Health Risk Assessment
Data Collection
Comparison to HILs
Risk Management Decision
Communicate results to risk manager
Site-Specific Health Risk Assessment
Data Collection
Risk Characterisation
Toxicity Assessment Exposure Assessment
Risk Assessment in the ESA process
Phase 1 should be considering risk issues when designing Phase 2
Phase 2 collecting the correct data with consideration of risk issues? QA/QC?
Additional DataMay be required before a risk assessment can be completed
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TEKey Aspects of Data Quality
Data QA/QC:
§The QA/QC evaluation is important to ensure that the quantitative analytical results can be relied upon – often seen as a tedious task delegated to the most inexperienced and cheapest staff.
§This includes review of field and laboratory QA/QC as all aspects can affect the quality of the data.
§May involve combining data from a number of different investigations and consultants over a number of years.
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TEKey Aspects of Data Quality
Data QA/QC:
§Some aspects to consider:
• Have any of the data been qualified by the laboratory or in the QA/QC assessment and why?
• Consistency of laboratory methods (e.g. TPH and any new data collected when NEPM revision is issued)
• Non-detects and laboratory detection limits – are these elevated?
• Bore logs – are these available and have they been prepared using a standardised/consistent approach/terminology?
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TEKey Aspects of Data Quality
Data Quantity:
§is there enough data available to characterise the nature and extent of contamination?
• Consider the land use to be assessed in the risk assessment (current and future)
• The location of source areas and extent of contamination (including hot spots) is important for the identification of who may be exposed
• The location of contamination is important from an exposure perspective (surface soil, depth of volatile contamination etc.)
• Have enough samples been analysed for the key chemicals?
• Has enough data been collected to address temporal variability (including consideration of media that are cyclical – e.g. tidal fluctuations or wet/dry weather fluctuations)?
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TEKey Aspects of Data Quality
Has the correct data been collected for use in a risk assessment:
§Has data been collected from the correct media where exposures may occur – soil (and/or sediment), water (groundwater and surface water), air (dust or vapour), homegrown produce (fruit and vegetables, eggs, poultry etc.), biota?
§Have samples been analysed for the correct analytes in the relevant media? Phase 1 should suggest what contamination may need to be considered. The behaviour of the contamination in the environment should also be considered to ensure that the sampling plan addresses media where the contaminants may be present.
§Is it important to characterise species (e.g. Cr III or Cr VI) or bioavailability (e.g. As in soil)?
§Is it important to know what background exposures may be? Has background data from the correct media been collected?
CSM
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TESome Show-Stoppers
§ Data fails a number of key aspects of QA/QC evaluation.
§ Only soil sampled, shows significant levels of impact, shallow groundwater and no data.
§ Significant contamination in groundwater, only VI pathway important for risk assessment, soil gas data quality very poor.
§ No surface soil data in children’s playground or school and contamination is only in shallow fill (where there is insufficient data - sampled at 2 locations at depth only).
§ Incorrect field sampling methods for VOCs, which are expected to be the key contaminants of concern.
§ If uptake/accumulation into eggs needs to be quantified and only soil data is available.
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TEIt’s not all bad……
Most deficiencies can be worked around in a risk assessment.
Data gaps are often identified and are evaluated for their significance in a risk assessment – this determines if the risk assessment can proceed with the available data.
BUT in most cases this involves making conservative assumptions (results in a tiered approach)
Uncertainty in risk assessment.
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TEHow are data limitations addressed?
Data QA/QC:
§If it has not been done – we have to do it!!!
§If it is deficient – we have to re-evaluate it !!!
§Where we have a lot of data over many years – need to make a decision in relation to the most appropriate data to assess the risks of concern – past/current and/or future exposures (e.g. post remediation data only relevant to future developments).
§Qualified data – Can often be OK but maybe only the maximum should be considered
§Elevated LOR – generally consider the LOR first then…..
§Bore log inconsistencies – take more conservative soil type
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TEHow are data limitations addressed?
Data Quantity – do we have enough data:
§Only the source area sampled – assume across whole site.
§No delineation of impacts – consider that the maximum is in all areas (e.g. use onsite data for offsite areas).
§Not all the key chemicals have been analysed – if the key indicators are reported these are assessed however it places greater uncertainty on the conclusions particularly where mixture issues may need to be considered.
§Only 1 round of data – use the maximum and consider some general rule of thumb to address variability.
§No surface soil data - use data from depth (if relevant).
§The depth of volatile contamination not defined – assume it is at most shallow depth.
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TEHow are data limitations addressed?
Has the correct data been collected for use in a risk assessment:
§Not all media sampled:
• No soil gas data – model from source (can be conservative – but be careful)
• No indoor air data – model from soil gas or source
• No surface water data – assume GW quality (conservative)
• No data on produce - can estimated for fruit and vegetables (very conservative and the models have limitations) but other produce less certain
• No data on particulates (in air and as deposited dust) – can estimate (generally conservative)
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TEHow are data limitations addressed?
Has the correct data been collected for use in a risk assessment:
§Speciation/bioavailability not addressed:
• Assume most toxic species comprises100% of the concentration (conservative)
• Assume 100% relative bioavailability (except Pb and potentially As) (conservative)
§Background:
• The risk assessment may be addressing background concentrations (not representative of contaminated site issues)
• Soil and groundwater – probably of less significance but there are some areas where it is (Bendigo?)
• Indoor air – very important as there are many background sources
• Surface water and biota – very important
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TEExample 1
§ Petroleum groundwater plume from service station
§ GW (@ 5m depth) and SG data from onsite areas only
§ Data needed to address the extent of offsite GW contamination and risk issues (residential areas offsite)
§ No GW data collected offsite
§ Passive SG samples placed at 0.3 m depth offsite only
Can this data be used to address extent and risk?
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TEExamples 2 and 3
Example 2
§Petroleum hydrocarbon contamination in groundwater
§Samples collected over 2 rounds, 6 years ago, only BTEX reported
§No soil gas data
Can this data be used to quantify vapour risk?
Example 3
§Soil gas data was collected – petroleum site
§Permanent wells installed and sampled on same day
§Field QA/QC data collected 1 month after primary samples
Can this data be used to quantify vapour risk?
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TEIn Conclusion…..
• Should QA/QC be delegated to the most inexperienced staff?
• In ESAs, risk issues should be considered (development of CSM) and addressed in the development of sampling plans.
• The quality of data is important and significantly affects the reliability and level of confidence in risk assessment conclusions.
