240
Toxic Chemicals
Based on the ETFs developed in Chapter 10 of this book, we have proposed concentration reporting thresholds that could be used to report composition relative to
ETFs. If an individual is exposed over the course of a year to 1 lb of a product that
contains a toxic chemical at a concentration of 1 part per million (ppm), and if the
chemical in this product has an ETF of 0.01 (1.00E-02) doses/capita-lb (assuming
a total U.S. capita of 306 million people), the total doses that the person would be
exposed to would be
1 lb toxic chemical 0 0
. 1 doses
3 total doses
×
× 306,000,000 capita =
1,000,000
capi t ta-lb
yr
In essence, an annual equal exposure to the toxic chemical at a concentration of 1
ppm in 1 lb of the product could result in three times the acceptable threshold beyond
which an adverse effect of some type could occur in every single person in the United
States. An ETF resulting in this level of doses per year (on a total capita basis), or
this type of potential adverse effect, warrants a lower reporting limit. Therefore, the
reporting limit was set at 1 ppm for any toxic chemical with an ETF greater than
0.01 doses/capita-lb and progressively set at higher values for lower ETFs.
Specifically, as shown in Table 16.1, for ETFs higher than 0.01 (1.00E-02)
doses/capita-lb, the concentration reporting threshold was set to 1 ppm. For ETFs
between 1.00E-03 and 1.00E-02 doses/capita-lb, the concentration reporting
threshold was set to 10 ppm, and so on, with the highest concentration reporting
threshold, 10,000 ppm (1 percent), set for ETFs less than 1.00E-05 doses/capita-lb
ETFs (represent those ETFs that could not be established for a compound due to
lack of input data).
CHEMICAL TOXICITY RATING
In this book, we utilized available information on toxicity, mobility, persistence, and
bioconcentration for the 650-plus chemicals in the TRI program. There will need
to be an ongoing effort to collect and analyze similar data on other chemicals used,
particularly new chemicals that are developed to replace toxic chemicals currently
in use. For example, when trichloroethylene (TCE) was identified as having toxic
issues, facilities that used TCE in vapor degreasers replaced TCE with trichloroethane (TCA). At the time, there was little information on the toxicity of TCA. After
a significant conversion had taken place, data were developed that showed that TCA
also had toxicity issues, and there was a need to modify processes. Consequently, we
will need to have an ongoing program to evaluate chemical toxicity, with changes in
the targeted chemicals list based on changes in use as new chemicals are developed.
One option for those chemicals that do not have corresponding toxicity data available is the application of quantitative structure-activity, or structure-property, relationships (QSARs) (Nikolova and Jaworska 2004). QSAR is the process by which
a chemical structure is quantitatively correlated with a defined process, such as
chemical reactivity or biological activity. More specifically, QSARs represent predictive models, mathematic relationships or quantitative structure-activity relationships, derived from application of statistical tools correlating quantitative desirable
Toxic Chemicals
Based on the ETFs developed in Chapter 10 of this book, we have proposed concentration reporting thresholds that could be used to report composition relative to
ETFs. If an individual is exposed over the course of a year to 1 lb of a product that
contains a toxic chemical at a concentration of 1 part per million (ppm), and if the
chemical in this product has an ETF of 0.01 (1.00E-02) doses/capita-lb (assuming
a total U.S. capita of 306 million people), the total doses that the person would be
exposed to would be
1 lb toxic chemical 0 0
. 1 doses
3 total doses
×
× 306,000,000 capita =
1,000,000
capi t ta-lb
yr
In essence, an annual equal exposure to the toxic chemical at a concentration of 1
ppm in 1 lb of the product could result in three times the acceptable threshold beyond
which an adverse effect of some type could occur in every single person in the United
States. An ETF resulting in this level of doses per year (on a total capita basis), or
this type of potential adverse effect, warrants a lower reporting limit. Therefore, the
reporting limit was set at 1 ppm for any toxic chemical with an ETF greater than
0.01 doses/capita-lb and progressively set at higher values for lower ETFs.
Specifically, as shown in Table 16.1, for ETFs higher than 0.01 (1.00E-02)
doses/capita-lb, the concentration reporting threshold was set to 1 ppm. For ETFs
between 1.00E-03 and 1.00E-02 doses/capita-lb, the concentration reporting
threshold was set to 10 ppm, and so on, with the highest concentration reporting
threshold, 10,000 ppm (1 percent), set for ETFs less than 1.00E-05 doses/capita-lb
ETFs (represent those ETFs that could not be established for a compound due to
lack of input data).
CHEMICAL TOXICITY RATING
In this book, we utilized available information on toxicity, mobility, persistence, and
bioconcentration for the 650-plus chemicals in the TRI program. There will need
to be an ongoing effort to collect and analyze similar data on other chemicals used,
particularly new chemicals that are developed to replace toxic chemicals currently
in use. For example, when trichloroethylene (TCE) was identified as having toxic
issues, facilities that used TCE in vapor degreasers replaced TCE with trichloroethane (TCA). At the time, there was little information on the toxicity of TCA. After
a significant conversion had taken place, data were developed that showed that TCA
also had toxicity issues, and there was a need to modify processes. Consequently, we
will need to have an ongoing program to evaluate chemical toxicity, with changes in
the targeted chemicals list based on changes in use as new chemicals are developed.
One option for those chemicals that do not have corresponding toxicity data available is the application of quantitative structure-activity, or structure-property, relationships (QSARs) (Nikolova and Jaworska 2004). QSAR is the process by which
a chemical structure is quantitatively correlated with a defined process, such as
chemical reactivity or biological activity. More specifically, QSARs represent predictive models, mathematic relationships or quantitative structure-activity relationships, derived from application of statistical tools correlating quantitative desirable