Post on 17-Mar-2021
Mercury Levels in U.S. Seafood
Tim Fitzgerald
EDF Hg database & recommendations
• Developed in 2004-2011 as a compliment to eco-recommendations
• Combine numerous data sources into one comprehensive resource
• Advice based on mean Hg levels
• Age/gender specific advisories
• 350+ gov’t & peer-reviewed sources
• Based on EPA’s National Guidance for establishing Fish Advisories
EPA/FDA Mercury Advice
DO NOT EAT (1 ppm) Shark Swordfish King Mackerel Tilefish
ONCE PER WEEK Albacore Tuna (~0.31 ppm)
Species Hg (ppm) Marlin 1.40
Cobia 0.74
Bluefin tuna 0.73
Opah/moonfish 0.62
Bigeye tuna 0.58
Escolar 0.58
Wahoo 0.49
Orange roughy 0.48
Spanish mack. 0.46
Chilean seabass 0.40
Spotted seatrout 0.40
Grouper 0.38
Lingcod 0.36
Bluefish 0.34
Sturgeon 0.34
Market factors influence exposure
1. 92% of U.S.-eaten seafood is imported
2. 60% of U.S.-eaten seafood is shrimp, canned tuna, salmon
3. 50% of U.S.-eaten seafood is farmed
4. 33% (on average) is mislabeled
5. U.S. seafood consumption -12% since 2004
Where U.S. seafood comes from
China, 19%
USA, 16%
Thailand, 14% Canada, 10%
Indonesia, 5%
Vietnam, 4%
Ecuador, 3%
Everyone else, 28%
U.S. Top 10 Seafoods
Species/Item Hg (ppm)
Shrimp 0.05
Canned Tuna 0.12-0.33
Salmon 0.05
Tilapia 0.02
Pollock 0.06
Pangasius 0.01
Crab 0.10
Cod 0.07-0.14
Catfish 0.01-0.14
Clams 0.03
1. Systematic update of EDF database (WoS)
2. Focus on Top ‘Hg Contributors’ (Groth, 2010)
3. Screened 1000+ data sources
4. Extracted mean [Hg] from 350+ sources
5. Examine trends & variability in [Hg] in domestic & imported seafood items
6. ID knowledge gaps
7. Compare findings with FDA monitoring program data
Approach, Goals & Rationale
EDF/Stony Brook Hg database
Sources Data
Points
% Domestic
Seafood
Date
Range
Geo.
Range
EDF/SB
study ~360 65,000 42%
1878-
2011 Global
FDA 1 4,500 N/A 1991-
2011
Global
(limited)
NMFS 1 7,400 100% 1971-
1978 U.S.
EPA 9 6,900 100% 1990-
2011 U.S.
EDF/Stony Brook Hg database
EDF/SB Database vs. FDA data
FDA under-estimates vs. Hg database
FDA over-estimates vs. Hg database
• Identify new funding to keep Hg database current
•Better data on farmed and imported fish
• Examine intra- and inter-species variability
• In-depth analysis of geographic differences
•Apply same methodology to other seafood contaminants
What Next?
Health risk implications of seafood fraud/mislabeling