ComET™ Farfield Modelling Dr. Don Mackay Mr. Jon Arnot Canadian Environmental Modelling Centre Trent University Peterborough, ON Slides and Materials Copyright Protected

Two Sources of Human Exposure Nearfield: Nearfield: –Indoor or direct product use  e.g., cleaning agents Farfield (focus of this presentation): Farfield (focus of this presentation): –Environmentally mediated  e.g., outdoor inhalation, water ingestion, foodstuffs, etc…

Estimates of both are desirable Estimates of both are desirable Which one dominates? Which one dominates? Varies from substance to substance Varies from substance to substance Depends on how the substance is produced and used and its physical/chemical properties Depends on how the substance is produced and used and its physical/chemical properties Two Sources of Human Exposure

Overview: Objective – Develop and apply a consistent, transparent, conservative estimation method using only available input data Objective – Develop and apply a consistent, transparent, conservative estimation method using only available input data Method – Combine environmental fate model with food web model Method – Combine environmental fate model with food web model Results: Results: –Estimates of concentration in all relevant exposure media (e.g., air, water, soil, food)

Assumption (1): Steady state Steady state (not dynamic) Steady state (not dynamic) Time (years) Concentration Emission starts, then remains constant

Assumption (2): Use a single environment for all chemicals Use a single environment for all chemicals Based on a typical ChemCAN region and the EQC evaluative environment Based on a typical ChemCAN region and the EQC evaluative environment Area – 10 5 km 2 (i.e., 316 km  316 km) Area – 10 5 km 2 (i.e., 316 km  316 km) Includes: Includes: –Air, water, soil, sediment, near shore ocean

Dimensions of Evaluative Environment AirFreshwaterOceanSoilSediment Area (m 2 ) 1x x x10 8 9x x10 10 Depth (m) Volume (m 3 ) 1x x x x x10 8

Farfield Model vs. EUSES Key Similarities: Key Similarities: –Compartment based mass-balance models –Level III –Fate and exposure pathways –Generally similar, diffusive and advective inter-media transfer process Key Differences: Key Differences: –Farfield model includes regions in Canada and can be run in ‘batch mode’ –Farfield model includes media specific half-lives –Farfield model includes mechanistic bioaccumulation models –Fugacity vs. rate constant formulation

Assumption (3): Organisms selected as representative species Organisms selected as representative species –Use current “state of the science” bioaccumulation –Including reported respiration and feeding rates

‘Representative’ Food Web Vegetation Vegetation – leafy Game Vegetation – stem Terrestrial feeding bird (e.g., pheasant) Vegetation – root Aquatic feeding bird (e.g., duck) Vegetation -- fruit/nut/grain Small herbivorous mammal (e.g., rabbit) Freshwater Organisms Large herbivorous mammal (e.g., deer) Aquatic invertebrates (e.g., crayfish) Small fish (e.g., perch) Agricultural Products Large fish (e.g., lake trout) Dairy (e.g., milk & cheese) Marine Organisms Eggs Marine invertebrates (e.g., lobster, shrimp) Beef Small fish (e.g., herring) Chicken Large fish (e.g., halibut, tuna) Pork Marine mammal (e.g., seal)

Assumption (4): Input data: Input data: –Molecular weight, vapor pressure, water solubility, octanol-water partition coefficient, pKa –Environmental half-lives in air, water, soil and sediment Unit emission rate: Unit emission rate: –100 kg/h –3 modes of entry (air, water and soil)

Assumption (5): Metabolic transformation rate constant is initially set to be zero in the bioaccumulation models for organisms of the food web Metabolic transformation rate constant is initially set to be zero in the bioaccumulation models for organisms of the food web –Reasonable assumption about metabolic transformation in organisms if no data available –If reliable metabolic transformation rate data are available they can be incorporated

Model Output Excel spreadsheet – transparent and available to all Excel spreadsheet – transparent and available to all Unit emission rate – 100 kg/h to air, water and soil Unit emission rate – 100 kg/h to air, water and soil Aim is priority setting -- to set aside or prioritize for additional consideration Aim is priority setting -- to set aside or prioritize for additional consideration

Matrix Emission Approach 100 kg/h to air: 100 kg/h to air: –C AIR = 100; C WATER = 30; C FOOD = kg/h to water: 100 kg/h to water: –C AIR = 15; C WATER = 150; C FOOD = 3000 If actual emission is 200 to air: If actual emission is 200 to air: –C AIR = 200; C WATER = 60; C FOOD = 10,000 If actual emission is 200 to air & 300 to water: If actual emission is 200 to air & 300 to water: –C AIR = (200/100)  (300/100)  15 = 245 –C WATER = (200/100)  30 + (300/100)  150 = 510 No need to re-run model, just scale the results No need to re-run model, just scale the results

Emission Options Ideally, we will use current reliable and real data on emissions Ideally, we will use current reliable and real data on emissions Alternatively, there are a number of options under consideration which will be the subject of the next talk on emission estimation Alternatively, there are a number of options under consideration which will be the subject of the next talk on emission estimation To Recap: To Recap: –CEMC will provide data on “unit emissions” –LLG and HC will estimate and apply emission estimates

Summary Physical-chemical properties (CEMC) Physical-chemical properties (CEMC) Unit emissions (CEMC) Unit emissions (CEMC) Calculate all exposure concentrations from unit emissions (CEMC) Calculate all exposure concentrations from unit emissions (CEMC) Scale to desired emission rate (LLG) Scale to desired emission rate (LLG) Recalculate concentrations (LLG) Recalculate concentrations (LLG) Calculate dosages for selected age classes using exposure quantities (e.g., food intake rates) (LLG) Calculate dosages for selected age classes using exposure quantities (e.g., food intake rates) (LLG) Combine / compare with near field dosages (LLG) Combine / compare with near field dosages (LLG)