132
6 Risk Assessment and Management of Chemical Products
with f i = m i /M being the fraction of the chemical’s total amount that is present
in compartment i and k denoting the weighted average of the first-order loss
rate constants, k i . Equation 6.23 shows that the overall persistence is the inverse
of the weighted average of the loss rate constants in all media with the mass
fractions, f i , as weighting factors. This is a useful result because it shows how the
overall persistence combines information about a chemical’s degradability (the k i )
with information about the chemical’s partitioning (the f i ). Many level III models
calculate the P ov of chemicals in this way.
However, there is also a drawback of P ov as a metric of persistence. The f i
strongly depends on the way in which the chemical is emitted to the environment.
Emission to soil, for example, generally leads to a higher fraction of chemical in
soil than emission to air. In other words, the overall persistence includes an arbitrary
element, namely the choice of the emission pathway and its influence on the f i in
Eq. 6.23.
A solution to this problem was proposed by Stroebe et al. (2004). If in a multicompartment model a chemical is released to each compartment separately (i.e.,
100% to air, 100% to water, etc.), a P ov value is obtained for each of these model
runs. The highest of all these P ov values is a good estimate of the chemical’s
persistence in the temporal remote state (TRS). The persistence in the TRS describes
how rapidly (or, rather, slowly) the most long-lived reservoir of the chemical in the
multi-compartment model degrades. If a chemical’s longest half-life is in soil, this
most long-lived reservoir is in the soil. This reservoir consists of the amount of
chemical that is still left when most of the chemical has been degraded in the other
compartments. Therefore, the speed at which this last reservoir of the chemical
disappears is a meaningful metric of the chemical’s persistence, and notably, it is
independent of the emission pathway (Stroebe et al., 2004).
This concept of calculating the greatest P ov value in a model system and using
it as an estimate of the chemical’s persistence in the temporal remote state is also
employed in the OECD P ov and LRTP Screening Tool (Wegmann et al., 2009).
Persistence and LRTP can be determined from measurement data (laboratory
measurements on degradation half-lives, measured concentrations of chemicals in
the field) as well as from model calculations such as from the OECD’s P ov and LRTP
Screening Tool. Substituting highly persistent and highly mobile substances with
shorter-lived and less mobile substances can greatly limit environmental exposure
(Scheringer, 1997, 2002).
6.5
Effect Assessment (Step 3)
In this next step of product risk assessment, the relationship between the level of
exposure to a substance (dose) and the resulting effect (response) is investigated.
This is called the dose-response relationship and can be estimated in a similar way
for both humans and the environment.
There are two specific fields of toxicology that are used in understanding
the dose-response relationship for a specific substance and effect. The field of
6 Risk Assessment and Management of Chemical Products
with f i = m i /M being the fraction of the chemical’s total amount that is present
in compartment i and k denoting the weighted average of the first-order loss
rate constants, k i . Equation 6.23 shows that the overall persistence is the inverse
of the weighted average of the loss rate constants in all media with the mass
fractions, f i , as weighting factors. This is a useful result because it shows how the
overall persistence combines information about a chemical’s degradability (the k i )
with information about the chemical’s partitioning (the f i ). Many level III models
calculate the P ov of chemicals in this way.
However, there is also a drawback of P ov as a metric of persistence. The f i
strongly depends on the way in which the chemical is emitted to the environment.
Emission to soil, for example, generally leads to a higher fraction of chemical in
soil than emission to air. In other words, the overall persistence includes an arbitrary
element, namely the choice of the emission pathway and its influence on the f i in
Eq. 6.23.
A solution to this problem was proposed by Stroebe et al. (2004). If in a multicompartment model a chemical is released to each compartment separately (i.e.,
100% to air, 100% to water, etc.), a P ov value is obtained for each of these model
runs. The highest of all these P ov values is a good estimate of the chemical’s
persistence in the temporal remote state (TRS). The persistence in the TRS describes
how rapidly (or, rather, slowly) the most long-lived reservoir of the chemical in the
multi-compartment model degrades. If a chemical’s longest half-life is in soil, this
most long-lived reservoir is in the soil. This reservoir consists of the amount of
chemical that is still left when most of the chemical has been degraded in the other
compartments. Therefore, the speed at which this last reservoir of the chemical
disappears is a meaningful metric of the chemical’s persistence, and notably, it is
independent of the emission pathway (Stroebe et al., 2004).
This concept of calculating the greatest P ov value in a model system and using
it as an estimate of the chemical’s persistence in the temporal remote state is also
employed in the OECD P ov and LRTP Screening Tool (Wegmann et al., 2009).
Persistence and LRTP can be determined from measurement data (laboratory
measurements on degradation half-lives, measured concentrations of chemicals in
the field) as well as from model calculations such as from the OECD’s P ov and LRTP
Screening Tool. Substituting highly persistent and highly mobile substances with
shorter-lived and less mobile substances can greatly limit environmental exposure
(Scheringer, 1997, 2002).
6.5
Effect Assessment (Step 3)
In this next step of product risk assessment, the relationship between the level of
exposure to a substance (dose) and the resulting effect (response) is investigated.
This is called the dose-response relationship and can be estimated in a similar way
for both humans and the environment.
There are two specific fields of toxicology that are used in understanding
the dose-response relationship for a specific substance and effect. The field of