The epidemiological evidence
has played a disproportionately large role in the policymaking
process. Time-series findings indicate associations of mortality
with not only PM and ozone, but with all of the criteria pollutants.
Because results of time-series studies implicate all of the criteria
pollutants, findings of mortality time-series studies do not
seem to allow one to confidently attribute observed effects specifically
to individual pollutants. This raises concern about the utility
of these types of studies in the NAAQS-setting process. Examples
of inconsistenties and inconclusive findings include the following:
- Instability of mortality
effect estimates resulting from different model specifications
of weather effects and time trends.
- Instability of effect
estimates resulting from different selections of monitoring sites
within cities.
- Increased heterogeneity
of effect estimates across cities.
- Greater diversity of findings
among studies and across study areas.
- Contradictory results
from mortality displacement studies.
- Effect lags that are inconsistent
across cities and across studies.
- Exposure-response relationships
that are inconsistent across cities and across studies.
- Inconsistencies between
short-term and long-term effect studies, such as respiratory
effects of fine particles.
- Contradictory findings
among long-term studies.
Smith et al. (2009) (Smith,
Xu, and Switzer) discussed some of the concerns about the use
of time-series data. The authors investigated intercity variability,
as well as the sensitivity of the ozone-mortality associations
to modeling assumptions and choice of daily ozone metric, based
on reanalysis of NMMAPS data. Smith et al. (2009) examined the
sensitivity of city-specific ozone-mortality estimates to adjustments
for confounders and effect modifiers, showing substantial sensitivity.
They examined ozone-mortality associations in different concentration
ranges, finding a larger incremental effect in higher ranges,
but also larger uncertainty. Alternative ozone exposure metrics
defined by maximum 8-h averages or 1-h maxima show different
ozone-mortality associations that the authors believed could
not be explained by simple scaling relationships. The authors'
view was that ozone-mortality associations, based on time-series
epidemiologic analyses of daily data from multiple cities, revealed
still-unexplained inconsistencies and showed sensitivity to modeling
choices and data selection that contribute to serious uncertainties
when epidemiological results are used to discern the nature and
magnitude of possible ozone-mortality relationships or are applied
to risk assessment.
Personal exposure is not
reflected adequately, and sometimes not at all, by concentrations
measured at central outdoor monitoring sites. Typically, personal
exposures are much lower than the ambient concentrations, and
can be dramatically lower depending on time-activity patterns,
housing characteristics, and season. In addition, and of particular
importance for the time-series studies, there can be no correlation
between personal concentrations measured over time and concentrations
measured at central outdoor sites.
Previous review comments
made by our research group were associated with spatial variability
and the statistical shortcomings associated with epidemiological
analyses. Dr. Paul Switzer's comments on some of the shortcomings
associated with the epidemiological findings can be read by clicking
here. In a slide presentation, Dr. Lefohn,
President of A.S.L. & Associates, summarized his group's
findings on some of the concerns associated with the epidemiological
methodology at an EPA
Clean Air Scientific Advisory Committee (CASAC) meeting in North Carolina. Dr. Paul Switzer,
a member of the technical team, provided written comments on
his concerns about the shortcomings of the statistical methodology
utilized in the time-series epidemiological analyses. His comments
can be viewed by clicking
here.
Professor Paul Switzer
(Stanford University) and Dr. Allen S. Lefohn (A.S.L. & Associates)
provided input to the EPA prior to the publication of the final
version of the Carbon Monoxide Criteria Document (CD). A summary
of our input is available in an Adobe
Acrobat PDF file.
The growing pattern of
inconsistent and inconclusive findings is troublesome and presents
both scientists and policymakers with a very difficult decision.
Simply stated, the science based on epidemiological results may
not be substantial enough at the moment to provide the foundation
upon which a clear path can be built that leads directly from
the science to the policymaking decision arena.
It its 2013-2015 review
by EPA of the national ambient ozone standard, the science based
on epidemiological results did not provide strong support for
reducing the current level of the Federal ozone standard in the
US (FR Vol. 80, No. 206). In November 2015, the EPA Administrator
concluded that the epidemiological risk analyses showed that
small net benefits resulted from changing the ozone standard
from its current level of 75 ppb to lower values (70, 65, or
60 ppb). EPA (2014) provided details supporting this observation
by the Administrator. The Administrator's conclusion was based
on the observation that because the short-term epidemiological
risk analyses were integrated from the maximum concentration
to zero concentration, minimum benefits occurred. As emission
reduction occurred to meet lower proposed ozone standards, the
lower concentrations began to rise (due to lack of NO scavenging)
and the epidemiological models predicted that additional morality
and morbidity might occur. Although benefits occurred as the
higher ozone concentrations were reduced, this benefit was greatly
neutralized by the rise in predicted mortality and morbitidy
due to the low end of the concentration distribution rising.
The result reported was associated with the model selected by
the epidemiologists. The model apparently ignored the scientific
observations reported (e.g., Hazucha and Lefohn, 2007; Lefohn
et al., 2010) that higher ozone concentrations should be provided
greater weight than lower concentrations of which many of the
lower values are in the background range (i.e., 25-55 ppb) (see
Lefohn et al., 2014). The large frequency of lower concentrations
results in the lower concentrations contributing an inappopriate
weighting when benefits are calculated. Additional discussion
of the lack of NO scavenging affecting the movement of the lower
hourly average ozone concentrations toward the mid-levels can
be found in Lefohn et al. (2017) and Lefohn et al. (2018). As
noted above, the observation that benefits were greatly neutralized
by the rise in predicted mortality and morbitidy due to lower
concentrations that were rising is an artifact of the epidemiological
modeling. The EPA in the 2013-2015 ozone rulemaking cycle attempted
to deal with this problem by artificially applying a "threshold"
to diminish the contribution of the lower concentrations.
In
the October 2015 national ambient ozone standard decision, the
EPA Administrator noted that she placed the greatest weight on
controlled human exposure studies, citing significant uncertainties
with epidemiologic studies. Reasons for placing less weight on
epidemiologic-based risk estimates were key uncertainties about
(1) which co-pollutants were responsible for health effects observed,
(2) the heterogeneity in effect estimates between locations,
(3) the potential for exposure measurement errors, and (4) uncertainty
in the interpretation of the shape of concentration-response
functions for ozone concentrations in the lower portions of ambient
distributions.
As
EPA initiates a review of the Agency's
December 2020 decision to retain the 2015 ozone human health
and vegetation standards, CASAC and the Agency will have to deal
with the uncertainties associated with integrating epidemiological
results into the standard-setting process. Uncertainties noted by the
EPA in its 2015 decision:
(1) which co-pollutants were responsible for health effects observed,
(2) the heterogeneity in effect estimates between locations,
(3) the potential for exposure measurement errors, and
(4) uncertainty in the interpretation of the shape of concentration-response
functions for ozone concentrations in the lower portions of ambient
distributions.
will
again have to be revisted.
Reference
Federal Register. Vol. 80, No. 206 / Monday, October 26,
2015. National Ambient Air Quality Standards for Ozone, 40 CFR
Part 50, 51, 52, 53, and 58, pp 65292-65468.
Hazucha, M. J.; Lefohn, A. S. (2007) Nonlinearity in Human
Health Response to Ozone: Experimental Laboratory Considerations.
Atmospheric Environment. 41:4559-4570.
Lefohn, A.S., Hazucha, M.J., Shadwick, D., Adams, W.C.
(2010). An Alternative Form and Level of the Human Health Ozone
Standard. Inhalation Toxicology. 22: 999-1011.
Lefohn, A.S., Emery, C., Shadwick, D., Wernli, H., Jung,
J., Oltmans, S.J. (2014). Estimates of Background Surface Ozone
Concentrations in the United States Based on Model-Derived Source
Apportionment. Atmospheric Environment, http://dx.doi.org/10.1016/j.atmosenv.2013.11.033.
84: 275-288.
Lefohn, A.S., Malley, C.S., Simon,
H., Wells. B., Xu, X., Zhang, L., Wang, T., 2017. Responses of
human health and vegetation exposure metrics to changes in ozone
concentration distributions in the European Union, United States,
and China. Atmospheric Environment 152: 123-145. doi:10.1016/j.atmosenv.2016.12.025.
Lefohn, A.S., Malley, C.S., Smith,
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M.G., Paoletti, E., De Marco, A., Xu, X., Zhang, L., Wang, T.,
Neufeld, H.S., Musselman, R.C., Tarasick, T., Brauer, M., Feng,
Z., Tang, T., Kobayashi, K., Sicard, P., Solberg, S., Gerosa.
G. 2018. Tropospheric ozone assessment report: global ozone metrics
for climate change, human health, and crop/ecosystem research.
Elem Sci Anth. 2018;6(1):28. DOI:
http://doi.org/10.1525/elementa.279.
Smith, R.L., Xu, B., and Switzer,
P. (2009). Reassessing the relationship between ozone and short-term
mortality in U.S. urban communities. Inhalation Toxicology, 29(S2):
3761.
US Environmental Protection Agency,
US EPA. (2014). Health Risk and Exposure Assessment for Ozone.
EPA/452/R-14-004a. Research Triangle Park, NC: Office of Air
Quality Planning and Standards. August.