Numbers versus What we see

Bill Duncan, ERA PanelNOAMI Workshop on Risk Assessment, November 2008

Quantitative Modeling

• Standards and modeling can rule out risks• However, conservatism greatly limits usefulness

for determining real risk at a site• As models are “improved” through the process

and risk is “whisked” away - confusing many stakeholders in the process

• Areas of biological impacts to communities are usually easy to see by seasoned biologists, First Nations and the locals. However, the cause may not always be clear.

2

Quantitative Modeling

3

LOR 1 LOR 2 LOR 3Food Ingest. Rate model model modelDiet concentrations generic measure measure% Soil in diet literature literature literatureTTFs literature measure measureBioavailability 100% literature measure/litHabitat Quality 100% 100% mapSoil Concentration model measure mapEffects literature literature literature

Bottom up – model up through the food chainMove from more conservative to more real

Quantitative ModelingIncluded In

Chemical LOR2 LOR3 CommentAntimony Ruled out risk in LOR 2ArsenicBarium Within range of background levelsBeryllium Maximum below standardsBoron Maximum below standardsCadmiumChromium Not related to smelter emissionsCobalt Maximum below standardsCopperFluoride Ruled out risk in LOR 1LeadMercuryMolybdenum Maximum below standardsNickel Maximum below standardsSelenium Maximum below standardsSilver Maximum below standardsSulphur Within range of background levelsThallium Maximum below standardsTin Not related to smelter emissionsVanadium Within range of background levelsZinc

Quantitative Modeling

5

Included InReceptor LOR1 LOR2 LOR3

Avian Species

American crow

American robin

Belted kingfisher

Black capped chickadee

Chicken

Mallard

Osprey

Red tailed hawk

Message to Public

“DEAD ROBINS”

6

Quantitative Modeling

What you see

What you see

•Highest suitability for robins in Trail Urban environment near Smelter•Lots of robins found by wildlife surveys•Public perception is lots of meaningless study – we could have told you there were plenty of robins – but look no vegetation over here•When are you going to do something about greening?

What you see

1974 2000

Plant species richness; a measure that shows how vegetation has responded to past and present metals and sulphur dioxide concentration.

High evidence of impacts

Moderate evidence of impacts

Low evidence of impacts

What you see

• 7,900 ha or 18.5% of original captured area• Plant communities have continued to develop •Effects area much smaller than “model predicted” area•Where we saw effects and would have determined needed management, surprise we need management

Other ideas

•Risk assessment can be used to help determine cause and effect but some areas are obviously impacted and can be addressed upfront•RA may be seen as a way to do nothing but is useful in defining the grey areas where remediation may not be required as risk benefit is low (more damage in cleaning up)•Modeling may be best used to evaluate and rank plausible remediation – relative risk ranking as opposed “quantitative” ranking•As a field biologist I tend to believe what the biological communities tell me - the top down approach but both have their roles