Comparative risk assessment of dioxin and fine particles

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COMPARATIVE RISK ASSESSMENT OF DIOXINS AND FINE PARTICLES

Main message:
Question:

How large are fine particle risks from heavy-duty traffic, and dioxin risk due to fish consumption in Helsinki metropolitan area? How can the EU-legislation for these stressors promote the public health?

Answer:

Fine particle risk clearly outweigh the dioxin risk. By stricter emission standards for heavy-duty vehicles, approximately 30 annual premature deaths can be avoided in Helsinki (1000000 inhabitants). By banning fish species (salmon, herring) containing dioxin above the EU-limit concentration, the net health effect would turn out to be negative, thanks to beneficial omega-3 fatty acids found in fish.


The full model is available from http://heande.pyrkilo.fi/heande/images/1/1d/PMvsDX.ANA

Background information about the study

Dioxins and airborne fine particles both are environmental health problems that have been subject to active public debate. Knowledge on fine particles has increased substantially during the last ten years, and even the current, lowered levels in Europe and the United States appear to be a larger public health problem than previously thought. On the other hand, dioxins are ubiquitous persistent contaminants and animal carcinogens at high doses, and therefore of a great concern. Our aim was to quantitatively analyze these two health risks and compare whether there are differences in given risks scenarios. Scenarios were chosen to match current and forthcoming EU regulations and standards for these two pollutants. We performed a comparative risk assessment for both pollutants in the Helsinki metropolitan area (Finland), and estimated the health effects for several scenarios: For primary fine particles: a comparison between the present emission situation of heavy-duty vehicles (CURRENT PRACTISE) to particle emission standards set by the EU, For dioxins: an EU-directive that regulates for commercial fishing of Baltic salmon and herring that exceed the dioxin concentration limit, and a derogation from the directive for these two species. Both of these two decisions are very topical issues. We found the risk of fine particles emitted by heavy-duty vehicles clearly outweighing the risk of dioxin in Finnish fish. Substantial improvement to public health could be achieved by advancing in emission standards from present situation to stricter emission standards, about 30 avoided premature deaths annually in Helsinki. In addition, we found that benefits of fish consumption due to omega-3 exposure were hundreds of times larger than the potential dioxin cancer risk.

Dioxin risk model

Here are some key variables of the model introduced to raise some discussion and to improve the model. Please, use the discussion tab located next to tab 'article' to add a comment or an argument. The relevant outcomes of the discussions will be transferred to this page and the adjustments to the variables will be updated accordingly when needed.



Variable #1:

Dioxin concentrations of Finnish fish

Concentrations of dioxins in domestic fish. Samples include skin and ventral fat. Therefore we can consider these concentrations as worst case scenarios.

References

  • Hallikainen A. et al 2004
  • KTL. Kirjolohien pitoisuus data
  • RKTL. Kalatalous tilastoina 2002

Definition

Fish species Dioxin WHO-TEQ in fresh weight
Farmed salmon (sea+freswater) Fractiles(0.4954 0.4965 0.6628 0.6871 0.6911 0.9743 1.124 1.399)
Wild salmon (sea) Fractiles(2.32 3.21 8.77 9.11 9.27 9.7 10.8 14.6 15.7 17.4)
Herring +17 cm (sea) Fractiles(8.23 15.9 16.6)
Herring -17 cm (sea) Fractiles(2 2.52)
White fish (sea) Fractiles(1.2 1.2 1.39 1.62 3.21 3.84 7.07)
Sprat (sea) Fractiles(0.882 2.04 2.72 2.98)
Perch (sea) Fractiles(0.529 1.18 1.28 1.51 1.85 2.74 4.23 5.23)
Flounder (sea) Fractiles(1.4 2.29)
Pike-perch (sea) Fractiles(0.721 0.777 1.66 2.04)
Bream (sea) Fractiles(0.386 0.99 1.05 1.68 3.37 4.58)
Pike (sea) Fractiles(0.447 0.617 0.71 0.945 1.31 1.39)
Vendace (sea) Fractiles(0.364 0.39 0.391 0.417 0.747 0.756 1.29 1.44 2.3)
Burbot (sea) Fractiles(0.132 0.178 0.262)
Wild salmon (freshwater) Fractiles(2.32 3.21 8.77 9.11 9.27 9.7 10.8 14.6 15.7 17.4)
White fish (freshwater) Fractiles(0.164 0.168 0.552 0.615 0.877 2.63)
Perch (freshwater) Fractiles(0.077 0.116 0.219 0.324 0.324 0.441)
Pike-perch (freshwater) Fractiles(0.147 0.273 0.276 0.319 0.744 0.814)
Bream (freshwater) Fractiles(0.386 0.99 1.05 1.68 3.37 4.58)
Pike (freshwater) Fractiles(0.07 0.14 0.202 0.218 0.379 1.6)
Vendace (freshwater) Fractiles(0.364 0.39 0.391 0.417 0.747 0.756 1.29 1.44 2.3)
Burbot (freshwater) Fractiles(0.061 0.167 0.533)

Causality

List of parents: N/A (original data)

Formula

N/A

Unit

ng/kg in fresh weight

Result

Fish species Mean WHO-TEQ in fresh weight
Farmed salmon (sea+freswater) 0.7976
Wild salmon (sea) 10.11
Herring +17 cm (sea) 14.16
Herring -17 cm (sea) 2.26
White fish (sea) 2.566
Sprat (sea) 2.23
Perch (sea) 2.238
Flounder (sea) 1.845
Pike-perch (sea) 1.272
Bream (sea) 1.915
Pike (sea) 0.9001
Vendace (sea) 0.8454
Burbot (sea) 0.1875
Wild salmon (freshwater) 10.11
White fish (freshwater) 0.7218
Perch (freshwater) 0.2484
Pike-perch (freshwater) 0.4185
Bream (freshwater) 1.915
Pike (freshwater) 0.3548
Vendace (freshwater) 0.8454
Burbot (freshwater) 0.232


Variable #2:

Consumption of domestic fish species

Scope
Includes fish from sea-areas, lakes and rivers of Finland.

Consumption of domestic fish species describes

Description

In these tables are the most common domestic fish species available for consumers.

References

  • RKTL. Kalatalous tilastoina 2002.
  • Suomen ympäristö 687

Definition

Fish species Consumption
Farmed salmon (sea+freshwater) (1.3*Forfood)
Wild salmon (sea) ((((((4.440e+005+1.520e+005)/Populationoffinland)*0.59)+(((6.900e+004+5.900e+004)/Populationoffinland)*0.59))+(((9.200e+004+3.240e+005)/Populationoffinland)*0.52))*Forfood)
Herring +17 cm (sea) ((Triangular(0.9,0.9,1.1)*(1-Sum(Herring_size_distrib[Sizecat=[12-14.9,15-16.9]])))*Forfood)
Herring -17 cm (sea) ((Triangular(0.9,0.9,1.1)*Sum(Herring_size_distrib[Sizecat=[12-14.9,15-16.9]]))*Forfood)
White fish (sea) ((((8.820e+005+9.440e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Sprat (sea) ((((1.574e+007+0.000e+000)/Populationoffinland)*Filletingfactor)*Forfood)
Perch (sea) ((((8.030e+005+2.993e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Flounder (sea) ((((1.300e+005+3.740e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Pike-perch (sea) ((((4.120e+005+6.150e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Bream (sea) ((((2.110e+005+7.760e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Pike (sea) ((((2.290e+005+2.312e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Vendace (sea) ((((9.800e+004+8.900e+004)/Populationoffinland)*Filletingfactor)*Forfood)
Burbot (sea) ((((1.040e+005+2.330e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Wild salmon (freshwater) ((((((9000+5.300e+004)/Populationoffinland)*0.59)+(((0.000e+000+6.600e+005)/Populationoffinland)*0.52))+(((1.200e+004+5.980e+005)/Populationoffinland)*0.52))*Forfood)
White fish (freshwater) ((((3.670e+005+2.054e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Perch (freshwater) ((((2.590e+005+9.340e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Pike-perch (freshwater) ((((7.500e+004+6.850e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Bream (freshwater) ((((2.170e+005+1.443e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Pike (freshwater) ((((1.270e+005+7.760e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Vendace (freshwater) ((((2.815e+006+2.022e+006)/Populationoffinland)*Filletingfactor)*Forfood)
Burbot (freshwater) ((((4.300e+004+7.880e+005)/Populationoffinland)*Filletingfactor)*Forfood)
Total 5.285


Causality

List of parents:

  • fish for human food
  • herring size distribution
  • filleting factor
  • Population of Finland

Data

Formula

Analytica_id:

<anacode></anacode>

Unit

kg/person/year

Result

Fish species Consumption
Farmed salmon (sea+freshwater) 1.3
Wild salmon (sea) 0.1242
Herring +17 cm (sea) 0.6419
Herring -17 cm (sea) 0.3248
White fish (sea) 0.1814
Sprat (sea) 0.03669
Perch (sea) 0.1816
Flounder (sea) 0.01879
Pike-perch (sea) 0.09217
Bream (sea) 0.05563
Pike (sea) 0.1746
Vendace (sea) 0.02166
Burbot (sea) 0.01815
Wild salmon (freshwater) 0.1345
White fish (freshwater) 0.2406
Perch (freshwater) 0.4593
Pike-perch (freshwater) 0.0382
Bream (freshwater) 0.09356
Pike (freshwater) 0.5419
Vendace (freshwater) 0.5601
Burbot (freshwater) 0.04475
Total 5.285


Variable #3:

Consumption of exported fish

Scope
Consumption of fish exported to Finland.

Consumption of exported fish describes

Description

Amount of how much imported fish is eaten in Finland.

References

  • RKTL. Taskutilasto 2002.

Definition

Fish species Consumption
Salmon 2.1
Rainbow trout 0.6
Tuna 1.6
Herring preservatives 0.5
Saithe 0.4
Others 2.8
Total 8

Causality

List of parents:

  • original data

Data

Formula

Analytica_id:

<anacode></anacode>

Unit

kg/person/year

Result

Fish species Consumption
Salmon 2.1
Rainbow trout 0.6
Tuna 1.6
Herring preservatives 0.5
Saithe 0.4
Others 2.8
Total 8


Variable #4:

Dose-response of dioxins

Scope
The response assessment is restricted to cancer endpoints, because it is the more sensitive endpoint.

The variable describes

Description

Cancer dose-response of humans. Also called as the cancer slope factor (CSF)

References

Definition

156000

Causality

List of parents:

  • Original data

Data

Formula

Analytica_id:

<anacode></anacode>

Unit

(1/(mg/kg/day))

Result

156000


Variable #5:

Dose-response of Omega-3

Scope
Dose response of dioxins WHO-TEQ to human health The variable describes

Description

Exposure-response function where also the uncertainty about the population that benefits from omega-3 is taken into account.

References

  • Mozaffarian and Rimm. 2006.

Definition

D_r_normal*(if All_or_chd=1 then 1 else F_chd_pati)

Causality

List of parents:

  • D-R normal
  • Does omega-3 help CHD patients or everyone?
  • Fraction of CHD patients among deaths

Data

Formula

Analytica_id:

<anacode></anacode>

Unit

probability/(g/d)

Result

-0.9088


Variable #6: Selected end points:

  • for dioxins - cancer

There are also other (more sensitive) endpoints than just cancer, e.g. developmental defects related to dioxins. Cancer deaths are used in this model in order to have commensurable units for both risks and benefits due to fish consumption.


  • for omega-3 - avoided coronary heart diseases

There are also other endpoints than just acoided CHD deaths, e.g. neurodevelopmental benefits. Avoided CHD deaths are used in this model in order to have commensurable units for both risks and benefits due to fish consumption.


Comparing the numbers of deaths and numbers of avoided deaths is unambiguous.