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					WP4. Assessment of environmental impacts and resulting
 externalities from multi-media (air/water/soil) impact
            A. Rabl, T. Bachmann, R. Torfs - 26 May 2003

      Participant    ARMINES           USTUTT.         VITO
                    (WP leader)          IER
      Person-months    11,5               5,8              7

     Deliverables                                    Due
     D4.1: Inventory of emissions to water and soil June 01
     for the major fuel chains.
     D4.2: Report on soil and water pathways,        April 02
     including adaptation of EUSES multi-media
     model for calculation of site-specific damages.
     D4.3: Results for damage e stimates.            Dec 02
  Pathways taken into account for health impacts of air pollutants.


                                 deposit ion (wet & dry)

                              f resh                                agricult ur al
                              wat er                                 veget at ion
                 wat er

                           f resh wat er
                seafood                                      milk               meat
                                f ish

                                              ingest ion                               inhalat ion
                                                 dose                                     dose

  Direct emissions to soil or water are a special case where the analysis begins at the
respective “soil” and “water” boxes. In the present version seafood is not yet included.
              Linearization of the Dose-Response Functions

                                                          slope s2

                                   slope s1

          0                                   D1                     D2   dose

 DRF at two values of the background dose, D1 and D2. For small variations around the
  background the DRF can be approximated by straight lines with slopes s1 and s2. The
     slopes can be different between groups with different backgrounds or different
sensitivities. For the calculation of population-total impacts one can take the population-
weighted average of the slopes. Doses below a NOAEL are a special case with slope zero.
          Justification for Equilibrium Models

                       One can show that
since with linear dose-response functions only the collective dose
matters for the total impact (irrespective of how it is distributed in
    time or among individuals), a dynamic model consisting of
 compartments with first order processes, yields exactly the same
   result as an equilibrium model with the same compartments,
      regardless of any detail of the time history of the inflow.

   Therefore an equilibrium model is sufficient for
    calculating the total dose, even though the real
         environment is never in equilibrium.
                Uniform world model (UWM)
For inhalation
• verified by comparison with about 100 site-specific
EcoSense calculations (EU, Eastern Europe, China, Brasil,
Thailand, …);
• recommended for typical values for emissions from tall
stacks, more than about 50 m (for specific sites the agreement is
usually within a factor of two to three; for ground level emissions
damage much larger; apply correction factors).
For ingestion it is even better, because food is transported
over large distances average over all the areas where the
food is produced.

Most policy applications need typical values (people tend to use
site specific results as if they were typical  precisely wrong rather than
approximately right)
                        Results for Doses
          Collective doses for central European conditions
              in mg/yr (for emission 1 kg/yr) = intake fractions x 1E6
by exposure pathway as a percentage of the total (figure) and in mg per emitted kg (table) for
                               base case (tcut = 100 years).
 As, Cd, Cr and Ni are modeled as PM10 and Pb as PM2.5; Hg is modeled as metallic Hg for
                            inhalation, methyl Hg for ingestion.
Pathway                 Arsenic     Cadmium       Chromium         Mercury    Nickel    Lead

Inhalation                3.9          3.9            3.9           22.0       3.9       7.1

Water                     15.6         15.8          15.5            2.5       15.8     17.8

Cattle milk              153.5         0.3           37.3           10.6       26.7     10.7

Cattle meat               13.6         1.3           36.1            7.4       43.1      4.1

Freshwater fish           7.8          15.8           0.8          1261.3      15.8      4.4

Grains                    60.6        119.3          60.2           217.1      64.2     80.2

Root vegetables           12.4         24.1          12.0           16.3       13.1     15.9

Green vegetables          16.2         47.5          15.9            9.2       17.6     23.9

TOTAL                     283          228           182            1547       200       164
                                 Results for Doses, cont’d







                       Arsenic    Cadmium   Chromium   Mercury   Nickel   Lead
TOTAL (Base case)      283.5       228.0      181.6    1546.5    200.2    164.1
Green vegetables        16.2       47.5       15.9       9.2     17.6     23.9
Root vegetables         12.4       24.1       12.0      16.3     13.1     15.9
Grains                  60.6       119.3      60.2     217.1     64.2     80.2
Freshwater fish          7.8        15.8       0.8     1261.3    15.8      4.4
Cattle meat             13.6        1.3       36.1       7.4     43.1      4.1
Cattle milk            153.5        0.3       37.3      10.6     26.7     10.7
Water                   15.6       15.8       15.5       2.5     15.8     17.8
Inhalation               3.9        3.9        3.9      22.0      3.9      7.1
                     Comparison with CalTOX
                        (a model based on fugacity)
      Ratio of total doses calculated by our model (UWM) and by CalTOX,
after multiplying the CalTOX results by the ratio 80/29 of population densities in
                            central Europa and the USA.

  Ratio of doses                As         Cd         Cr        Ni        Pb

  UWM/CalTOX                   0.61       0.07       0.39     0.60       0.05
            Results for Impacts and Social Costs
CRFs, DRFs and impacts, per kg emitted, for the carcinogenic metals.
   Unit risk and slope factor from IRIS
                                   As         Cd        Cr-VI       Ni
 unit risk                       4.30E-03   1.80E-03   1.20E-02   2.40E-04
 sCR [cancers/(pers·yr·kg/m3)]   6.14E+04   2.57E+04   1.71E+05   3.43E+03
 Cancers/kg, inhalation, UWM     2.32E-05   9.73E-06   6.49E-05   1.30E-06
 slope factor                    1.50E+00
 sDR [cancers/kg]                1.07E+00
 Cancers/kg, ingestion           3.05E-04
 Total cancers/kg                3.28E-04   9.73E-06   6.49E-05   1.30E-06
 Cost/kg [€/kg] at 2 M€/cancer     656        19         130        2.6
            Damage cost of IQ decrement due to Pb
Dose-response function is quite well determined [meta-analysis by
Schwartz 1994]: 0.026 IQ points per 1 µg/l increase of Pb in blood,
linear without threshold.
Cost 3000 €/IQ point
Two calculations:
a) 1.0 g/m3 incremental exposure to Pb in ambient air increases the
blood level by 50 µg/l,  1.3 IQ points per child per g/m3
Express in terms of total population (sensitive population 1 to 3 yr)
sCR = 1.43E-2 IQ points/(pers·yr·(g/m3))
 804 €/kg, with relation blood/air
b) relation between blood level Pb and ingestion dose [WHO 1995]
sDR = 3.32E+03 IQpoints/(
1633 €/kg, with relation blood/ingestion.
Limit for unleaded gasoline after 2000 is 5mg/l [EC 1998]. At this level, and with
1633 €/kg, the associated damage cost would be 0.008 €/l.
              Vito, Rudi Torfs
             Model comparison

1. Examine Vlier-human (VH) model from Vito
   •   Define most sensitive parameters
2. Set parameters to values used in UWM
3. Calculate (total dose)/(inhalation dose)
   •   To compare with UWM results
4. Do some sensitivity analysis
                                      Example Ni                   (VITO)

We have made calculations for the following scenarios:
1 VH with the original parameters VH-original
2 VH with the UWM parameters VH+UWM
3 VH with the UWM parameters, but the BCF set to the Flemish values VH+UWM-BCF
4 VH with the UWM parameters, but the soil water distribution coefficient (Kd) set to the
   Flemish values, for different pH values VH+UWM-Kd pH =X
Table 1: results for Ni
                                                   VH+UWM-    VH+UWM-     VH+UWM-     VH+UWM-
 Ni (kg/(pers.yr))        VH-original   VH+UWM       BCF      Kd pH = 4   Kd pH = 6   Kd pH = 8
 Soil intake               4.9E-09          -          -          -           -           -
 Vegetables                1.9E-07       1.5E-08    8.0E-08    1.5E-08     1.5E-08     1.5E-08
 Meat                      9.6E-09       1.9E-07    3.4E-07    1.9E-07     1.9E-07     1.8E-07
 Milk                      1.6E-09       8.1E-08    1.4E-07    7.8E-08     7.7E-08     7.7E-08
 Water                     4.2E-08       3.4E-07    3.4E-07    1.1E-07     3.4E-08     1.1E-08
 Dose from ingestion       2.5E-07       6.3E-07    9.1E-07    3.9E-07     3.1E-07     2.9E-07

 Dose from inhalation       3.7E-09      3.7E-09    3.7E-09    3.7E-09      3.7E-09     3.7E-09
 Total dose/inhalation         68          173        248        107           86          79
          Conclusions (VITO)
• Ni : good agreement between the
  ingestion/inhalation ratio of VH and UWM.
• Cr : mismatch between the two models,
  perhaps due to the drinking water pathway.
• Pb : VH model with parameters set to the
  UWM values gives a ratio that is 3 to 4
  times higher than that of UWM
• VH-model as a local component?

•Have results for doses and impacts for cancers due to As, Cd, Cr and
Ni, and for IQ due to Pb
•Have all the major pathways, except seafood
•Have sensitivity analysis
•What time horizon? Significant contributions >100 yr for Hg and Pb.
•Ingestion dose for toxic metals about two orders of magnitude larger
than inhalation dose
•Large uncertainty for doses (order of magnitude?)
•Lack of information on DRFs (for most noncancer effects, e.g. due to
Hg, only NOAEL or LOAEL data - not sufficient for quantification of
•What is included in DRF: only inhalation or also ingestion?

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