Huntsman Petrochemical LLC v. Environmental Protection Agency

United States Court of Appeals
FOR THE DISTRICT OF COLUMBIA CIRCUIT
Argued February 16, 2024 Decided August 13, 2024
No. 23-1045
HUNTSMAN PETROCHEMICAL LLC,
PETITIONER
v.
ENVIRONMENTAL PROTECTION AGENCY,
RESPONDENT
AIR ALLIANCE HOUSTON, ET AL.,
INTERVENORS
Consolidated with 23-1047, 23-1085
On Petitions for Review of Final Actions
of the Environmental Protection Agency
John D. Lazzaretti argued the cause for petitioners. With
him on the briefs were Allen A. Kacenjar, Laura K. McAfee,
David M. Friedland, Elliott Zenick, and Tokesha Collins-
Wright.

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Matthew Z. Leopold and Elbert Lin were on the brief for
amici curiae the Chamber of Commerce of the United States of
America and the National Association of Manufacturers in
support of petitioners.
Eric G. Lasker was on the brief for amici curiae Ethylene
Oxide Sterilization Association and Sterigenics U.S., LLC in
support of petitioners.
Ken Paxton, Attorney General, Office of the Attorney
General for the State of Texas, Aaron L. Nielson, Solicitor
General, and Bill Davis, Deputy Solicitor General, were on the
brief for amicus curiae Texas Commission on Environmental
Quality in support of petitioners. Lanora C. Pettit, Principal
Deputy Solicitor General, entered an appearance.
Sue S. Chen, Senior Attorney, U.S. Department of Justice,
argued the cause for respondent. With her on the brief were
Todd Kim, Assistant Attorney General, and Monica Derbes
Gibson, Trial Attorney, U.S. Environmental Protection
Agency.
Kathleen Riley and Adam Kron were on the brief for
Environmental and Public Health respondent-intervenors.
Before: HENDERSON and GARCIA, Circuit Judges, and
ROGERS, Senior Circuit Judge.
Opinion for the Court filed by Circuit Judge GARCIA.
GARCIA, Circuit Judge: This case concerns challenges by
a chemical manufacturer and two trade associations to an EPA
rule regulating emissions from certain facilities. Petitioners
dispute EPA’s assessment of the cancer risk from exposure to
those facilities’ ethylene oxide emissions. EPA addressed and

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rejected petitioners’ arguments in detail, and petitioners fail to
show that in doing so EPA acted arbitrarily, capriciously, or
otherwise contrary to law. We therefore deny the petitions for
review.
I
Under Section 7412 of the Clean Air Act, EPA is required
to tighten emissions standards if it determines that certain
emissions pose an unacceptable risk to public health.
42 U.S.C. § 7412(f). This case concerns a 2020 rule that EPA
promulgated to regulate emissions by Miscellaneous Organic
Chemical Manufacturing facilities. See National Emission
Standards for Hazardous Air Pollutants: Miscellaneous
Organic Chemical Manufacturing Residual Risk and
Technology Review (“Rule”), 85 Fed. Reg. 49084 (Aug. 12,
2020). EPA determined that emissions from these sources
posed an unacceptable risk to public health under Section 7412,
primarily due to emissions of the chemical ethylene oxide, and
therefore tightened emissions standards for those sources. Id.
at 49088, 49094. Ethylene oxide is a gas at room temperature
and is used, as relevant to the Rule, to manufacture antifreeze,
plastics, adhesives, and other common products. EPA
concluded that for people living near these facilities, the
maximum lifetime individual risk of cancer from exposure to
ethylene oxide was four times what EPA generally considers
acceptable. Id. at 49095–96 & tbl.3.
The 2020 rule calculated the lifetime individual cancer risk
from exposure to these facilities’ emissions by multiplying the
estimated lifetime exposure to ethylene oxide for the relevant
populations by EPA’s assessment of the increased risk of
cancer from such exposure. National Emission Standards for
Hazardous Air Pollutants: Miscellaneous Organic Chemical
Manufacturing Residual Risk and Technology Review, 84 Fed.
Reg. 69182, 69191 (proposed Dec. 17, 2019). EPA’s cancer-

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risk assessment for ethylene oxide is sometimes referred to as
the “IRIS value,” after an EPA database of health hazards from
various chemicals called the Integrated Risk Information
System.
How EPA arrived at the ethylene oxide cancer-risk
assessment and whether EPA should have relied on it in the
Rule is at the heart of this appeal. EPA generated that cancer-
risk assessment in an extensive, eighteen-year process that
began in 1998, involved rounds of public comment and peer
review by EPA’s Science Advisory Board (“SAB”), and
concluded in 2016 when EPA issued a comprehensive report
on the subject.
The 2016 report first explained that “strong evidence”
supported the conclusion that inhalation of ethylene oxide
increases the risk of certain kinds of cancer. See J.A. 2299; see
also J.A. 2315–22. EPA then quantified that risk using
statistical modeling. EPA focused on the risk faced by
members of the public from low environmental exposures
because of Section 7412’s focus on “public,” rather than
occupational, health. See J.A. 2302. In general terms (with
details to come later in this decision as relevant), EPA’s
statistical modeling approach proceeded as follows. See J.A.
2383 fig.4-1; see also Oral Argument Tr. 18–19. First, EPA
selected underlying data about cancer rates in populations
exposed to ethylene oxide. See J.A. 2387–89. Second, EPA
developed multiple statistical models from that data. See J.A.
2389–97. Third, EPA considered which of the statistical
models best fit that data. See J.A. 2397–402. And finally, EPA
used its chosen model to perform additional statistical analysis
to arrive at the cancer risk from ethylene oxide exposure at low
environmental exposure levels. See J.A. 2403–13.
Petitioners here raised complaints about EPA’s data
selection and modeling choices during EPA’s eighteen-year

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process of updating the ethylene oxide cancer-risk assessment.
See generally J.A. 1847–2114. When EPA used the 2016
updated cancer-risk assessment in the 2020 rulemaking,
petitioners raised similar complaints in comments on the notice
of proposed rulemaking and in seeking reconsideration after
EPA issued the final rule. See generally J.A. 100–387, 388–
672, 673–1034, 3353–3560.
Petitioners asked EPA to consider, among many other
things, a different model developed and proposed by Texas’s
environmental agency (“TCEQ”) in May 2020. 85 Fed. Reg.
at 49098. TCEQ’s model estimated a cancer risk about 3,000
times lower than EPA’s model. See J.A. 3708. When the
comment period on the Rule closed in March 2020, the TCEQ
assessment was in draft form and had not yet been subject to
peer review. See 85 Fed. Reg. at 49098 & n.12. The TCEQ
assessment was finalized a few months after the comment
period closed. See id.
Once the assessment was finalized, petitioners sought
reconsideration. J.A. 3353–3560. In February 2022, EPA
granted reconsideration and solicited further public comment
on the use of EPA’s ethylene oxide cancer-risk assessment in
the 2020 Rule and the use of the TCEQ assessment as an
alternative. Reconsideration of the 2020 National Emission
Standards for Hazardous Air Pollutants: Miscellaneous
Organic Chemical Manufacturing Residual Risk and
Technology Review, 87 Fed. Reg. 6466, 6467 (proposed Feb.
4, 2022). EPA issued a final reconsideration decision in
December 2022. Reconsideration of the 2020 National
Emission Standards for Hazardous Air Pollutants:
Miscellaneous Organic Chemical Manufacturing Residual
Risk and Technology Review (“Reconsideration Decision”),
87 Fed. Reg. 77985 (Dec. 21, 2022). The Reconsideration
Decision affirmed EPA’s decision to use the IRIS value for
ethylene oxide for the 2020 Rule and explained EPA’s

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rejection of TCEQ’s cancer-risk assessment for ethylene oxide
as an alternative. Id. at 77985–95.
In a set of consolidated cases filed in this court in 2020,
petitioners Huntsman Petrochemical LLC and the American
Chemistry Council sought review of the Rule. These cases
were held in abeyance pending EPA’s reconsideration. After
the EPA issued its Reconsideration Decision, Huntsman
Petrochemical, the American Chemistry Council, and the
Louisiana Chemical Association again petitioned this court for
review. We severed the ethylene oxide cancer-risk assessment
issues raised in the petitions challenging the Rule and
consolidated them with the petitions for review of the
Reconsideration Decision (which concerned the cancer-risk
assessment issues, too). Mar. 28, 2023 Order.
II
Under the APA, courts must “hold unlawful and set aside
agency action” that is “arbitrary, capricious, an abuse of
discretion, or otherwise not in accordance with law.” 5 U.S.C.
§ 706(2)(A); see 42 U.S.C. § 7607(d)(9)(A) (Clean Air Act
provision requiring same). Most fundamentally, “[t]he APA’s
arbitrary-and-capricious standard requires that agency action
be reasonable and reasonably explained.” FCC v. Prometheus
Radio Project, 592 U.S. 414, 423 (2021).
An agency action is arbitrary or capricious if the agency
“entirely failed to consider an important aspect of the problem”
or “offered an explanation for its decision that runs counter to
the evidence before the agency.” Motor Vehicle Mfrs. Ass’n v.
State Farm Mut. Auto. Ins. Co., 463 U.S. 29, 43 (1983). An
agency also acts arbitrarily and capriciously when it fails to
“examine the relevant data and articulate a satisfactory
explanation for its action including a ‘rational connection
between the facts found and the choice made.’” Id. (quoting

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Burlington Truck Lines, Inc. v. United States, 371 U.S. 156,
168 (1962)).
In the case of EPA’s evaluation of scientific data within its
area of expertise, we accord an “extreme degree of deference.”
Miss. Comm’n on Env’t Quality v. EPA, 790 F.3d 138, 150
(D.C. Cir. 2015) (per curiam) (quoting City of Waukesha v.
EPA, 320 F.3d 228, 247 (D.C. Cir. 2003)). This is particularly
true for statistical and modeling analysis. See Appalachian
Power Co. v. EPA, 135 F.3d 791, 802 (D.C. Cir. 1998) (per
curiam) (identifying statistics as “the prime example of those
areas of technical wilderness into which judicial expeditions
are best limited to ascertaining the lay of the land”). We, “as
nonstatisticians,” id., do not ask whether, “[l]ooking at the
same data” we “would simply reach a different conclusion,”
Miss. Comm’n on Env’t Quality, 790 F.3d at 162. Instead, we
“will examine each step of EPA’s analysis to satisfy ourselves
that the agency has not departed from a rational course,” and
“only when the model bears no rational relationship to the
characteristics of the data to which it is applied” will we
conclude the use of the model was arbitrary and capricious.
Appalachian Power Co., 135 F.3d at 802.
III
Petitioners’ challenges to the Rule and Reconsideration
Decision fall into three groups: arguments that EPA’s modeling
of the lymphoid cancer risk of ethylene oxide was arbitrary and
capricious, arguments that EPA committed procedural errors in
promulgating the Rule and issuing the Reconsideration
Decision, and an argument that Section 7412(f) is an
unconstitutional delegation of congressional authority.1 We
address each in turn and conclude none has merit.
1 We decline to address the issue raised only by TCEQ as
amicus regarding whether EPA properly accounted for parity bias in

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A
We start with the foundational issue: EPA’s modeling of
the lymphoid cancer risk of ethylene oxide. Petitioners have
not shown that EPA’s modeling was arbitrary or capricious.
As briefly outlined above, EPA’s statistical modeling
approach included several steps. See J.A. 2383 fig.4-1; see also
Oral Argument Tr. 18–19. EPA first chose which underlying
data about cancer rates in populations exposed to ethylene
oxide to use. See J.A. 2387–89. EPA selected data from a
large-scale study conducted by the National Institute for
Occupational Safety and Health (“NIOSH”), which found that
sterilizer workers exposed to ethylene oxide faced higher risks
of lymphoid and breast cancer. See J.A. 2299.
Second, EPA developed multiple statistical models from
that data. See J.A. 2389–97. EPA developed what are called
dose-response models.2 A dose-response model describes
incremental cancer risk based on the level of exposure to the
carcinogen above any background exposures. See, e.g., J.A.
selecting breast cancer as a relevant health effect of ethylene oxide
exposure. TCEQ Amicus Brief 20–22. This issue is wholly
independent from those raised by petitioners and not implicated by
any of the arguments they do raise. See Michel v. Anderson, 14 F.3d
623, 625 (D.C. Cir. 1994). Further, petitioners bury some of their
contentions in footnotes. See, e.g., Petitioners’ Brief 32 n.39, 38
n.53; Reply Brief 21 n.8, 29 n.13. We do not consider these
arguments because “[a] footnote is no place to make a substantive
legal argument on appeal.” CTS Corp. v. EPA, 759 F.3d 52, 64 (D.C.
Cir. 2014).
2 EPA’s assessment of overall cancer risk included both
lymphoid cancer and breast cancer—the two cancers linked to
ethylene oxide in the data. See, e.g., J.A. 2383 fig.4-1. Because this
appeal focuses on challenges regarding the lymphoid cancer model,
our discussion does, too.

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2389–90, 2402, 3616. EPA developed multiple potential
models using the individual data points from the NIOSH study.
See J.A. 2393, 2396.
Third, EPA determined which of the statistical models best
fit the data. See J.A. 2397–402. EPA selected the model that
best fit the data based on two calculations referred to as fit
metrics and an assessment of visual fit. See J.A. 2396–97,
2400–01 tbl.4-6. The two fit metrics used by EPA calculated,
respectively, how well the model matches (or “fits”) the
underlying data and the likelihood that an observed outcome is
due to chance. See, e.g., J.A. 2396, 2160. EPA identified the
models with lower fit metrics, indicating better fit of the model
overall. See J.A. 2400 tbl.4-6. But while the fit metrics
indicate overall fit of the model across all exposure levels, EPA
explained that they may not indicate the model with the best
local fit at a particular exposure range. See J.A. 2739, 4357.
Because EPA was most interested in the effect of low levels of
environmental exposures for purposes of its Clean Air Act
analysis, EPA also used visual fit (essentially an assessment of
how well a model visually appears to fit the data when plotted
on a graph) to determine which of those models with good fit
metrics best fit the data at low exposure levels. See J.A. 2396–
97.
To make that visual fit assessment, EPA took the potential
models it had developed from the individual NIOSH data and
compared them to categorical averages of that data to see which
model had the best visual fit at low exposure levels. See J.A.
2393. EPA explained that plotting model fit compared to the
categorical averages of data “is a very useful and commonly
used tool in epidemiology” because it allows for comparison of
continuous models against the unstructured information in the
relevant exposure ranges. J.A. 4349–50. Put simply, it allowed
EPA to make sense of a large data set of 17,000 individual data
points and see an average person’s response within a

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categorical interval rather than all the variations in individual
responses. E.g., Oral Argument Tr. 20–21.
Based on both fit metrics and visual fit at low exposures,
EPA determined that the model that best fit the data was a two-
piece linear spline (essentially two straight line segments with
different slopes connected at what is called a “knot”), with a
steeper slope at lower exposure levels and a lower slope at
higher exposure levels. See J.A. 2397–402. EPA further
explained that “plateau-like” dose-response curves like its
chosen spline model “have been seen for many occupational
carcinogens” and noted several potential explanations in the
scientific literature for that phenomenon. J.A. 2617; see also
J.A. 1950, 2393.
Petitioners challenge four aspects of EPA’s modeling
process and model selection: (1) EPA’s use of the NIOSH data,
(2) its development and selection of its chosen two-piece spline
model, (3) its rejection of petitioners’ preferred model, and
(4) its rejection of petitioners’ favored studies. Within those
categories, petitioners raise a litany of complaints about EPA’s
choices, each of which we have carefully considered and
address below. It is important to note at the outset, however,
that petitioners have not identified any issue that they raised
during the rulemaking process to which EPA failed to respond.
They instead ask us to credit, for example, their interpretation
of the data and figures in the extensive record over EPA’s.
Petitioners’ arguments are of the type for which we accord EPA
an “extreme degree of deference.” Miss. Comm’n on Env’t
Quality, 790 F.3d at 150. Applying that standard, and having
“examine[d] each step of EPA’s analysis to satisfy ourselves
that the agency has not departed from a rational course,” we
conclude that EPA adequately explained its modeling approach
and decisions. Appalachian Power Co., 135 F.3d at 802.

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1
EPA extensively explained why it chose the NIOSH study
as the basis for its risk assessment, including that it was by far
the largest available human study and for several reasons was
“high-quality.” J.A. 2300; see also, e.g., J.A. 2445–46.
Petitioners raise one primary complaint about the NIOSH data:
The NIOSH study tracked cancer incidence in sterilizer
workers from 1938–1986 but did not have substantial directly-
measured data about the levels of ethylene oxide exposure such
workers faced before 1978, instead using projections based on
more recent data. Petitioners’ Brief 36–38. Per petitioners, this
made EPA’s reliance on the NIOSH study data arbitrary and
capricious.
EPA adequately explained its reliance on the NIOSH data
and its rejection of petitioners’ critiques. See J.A. 2445–46,
2536–38. Specifically, EPA credited the NIOSH study’s
explanation that pre-1978 exposure levels could be reliably
estimated using a regression model based on plant- and year-
specific sterilizer volume data that was available. J.A. 2445–
46. The SAB agreed with EPA that the NIOSH data was “the
most appropriate dataset to use” and supported EPA’s use of it.
E.g., J.A. 3301.
Petitioners argue that EPA’s explanation was inadequate.
Those arguments lack merit.
First, petitioners note that the SAB commented that certain
of the pre-1978 exposure levels estimated in the NIOSH study
were “unlikely” and “surprising.” Petitioners’ Brief 36. But,
as EPA explained, the SAB was not rejecting the NIOSH data;
instead, the SAB asked for EPA to respond to specific data that
appeared inconsistent, and EPA adequately explained why the
data were not, in fact, anomalous. See J.A. 2763–64, 3613.

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Second, petitioners argue that EPA ignored a 2019 study
that, according to petitioners, called the NIOSH data’s pre-
1978 exposure levels into question. Petitioners’ Brief 37. But
EPA reasonably explained that it rejected that 2019 study
because its methodology—which was based on interviews and
other data—was not sufficiently documented to evaluate how
the study’s model was derived, and so the results were not
reliable. See J.A. 4341. Further, EPA explained that the 2019
study’s model projections were also inconsistent with other
data. Id.
Petitioners also argue that the NIOSH study and EPA
ignored other evidence suggesting that exposure levels early in
the study period would have been much higher than what
NIOSH estimated, such as evidence that sterilization work
practices improved substantially over time. Petitioners’ Brief
37. Again, however, EPA specifically acknowledged and
addressed these assertions in its response to comments. See
J.A. 4339–41. EPA explained, for example, that the NIOSH
study did account for improvements in work practices in the
relevant period. J.A. 4340. Petitioners have not shown that
this explanation was arbitrary or capricious.
2
Petitioners’ challenges to EPA’s modeling process and its
choice of the spline model also fail.
a
We begin with petitioners’ arguments that EPA’s
modeling process was arbitrary and capricious. First,
petitioners challenge EPA’s use of categorical averages when
assessing the visual fit of potential models. Second, petitioners
challenge EPA’s reliance on visual fit. Petitioners also raise
two technical complaints related to the calculation of a fit
metric and graphing the models.

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Recall that EPA developed its potential models using the
individual-level NIOSH data and then, in a subsequent stage of
its model-selection process, relied on categorical averages of
the NIOSH data to assess the potential models’ visual fit to the
data at low exposures. See J.A. 2386, 2396. Petitioners argue
that using categorical averages was an oversimplification that
led EPA to choose the wrong model. Petitioners’ Brief 46–47.
But EPA adequately explained why it compared the models of
the individual data to categorical averages in the visual fit
analysis, instead of somehow visually assessing how well the
models fit 17,000 individual data points on a graph. J.A. 4349–
51. EPA explained that plotting model fit using categorical
averages of data “is a very useful and commonly used tool in
epidemiology” because it allows for visual comparison of
continuous models against the unstructured information in the
relevant exposure ranges. J.A. 4349–50. EPA further
explained that comparison was appropriate where the
categorical averages were developed from the same individual-
level data as the models and compared the same referent group.
Id. Petitioners fail to show how this explanation was
unreasonable or inconsistent.
Petitioners relatedly suggest that EPA’s approach ran
contrary to SAB feedback. Petitioners’ Brief 46 n.68; Reply
Brief 19. Not so. The SAB feedback recommended that the
models should be developed based on the individual, not
categorical data. See J.A. 3324. EPA complied. See J.A. 2393,
2396. The SAB feedback did not preclude EPA from then
relying on the categorical averages in separately assessing the
models’ visual fit after they had been developed.
Petitioners next seek to characterize EPA’s process as
“simply eyeballing” the data and relying solely on visual fit to
select the model it wanted. Petitioners’ Brief 44–45. In fact,
however, EPA selected the model that best fit the data based on
both calculated fit metrics and EPA’s assessment of the

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models’ visual fit at low exposures, not visual fit alone. See
J.A. 2400–01, 2396–97, 2400–01 tbl.4-6. As EPA repeatedly
detailed, that use of visual fit was consistent with both SAB
recommendations and EPA’s own guidance. See J.A. 4345,
4349; see also J.A. 3323.
Finally, petitioners raise two other technical objections
related to EPA’s modeling approach. First, petitioners contest
one aspect of one of EPA’s fit metric calculations. Petitioners’
Brief 42–43. EPA used that metric to calculate how well the
underlying data match (or “fit”) the model. Petitioners contend
that, in those calculations, EPA should have counted the knot
of its spline model (the point where the two line segments with
different slopes meet) as a third estimated parameter, instead of
running the fit calculations based on two parameters. But EPA
addressed this contention and adequately explained why and
how its calculations were based on two parameters. See J.A.
4356–57. Particularly given the “extreme degree of deference”
we give to EPA’s evaluation of scientific data within its area of
expertise, petitioners have not shown that explanation was
arbitrary. Miss. Comm’n on Env’t Quality, 790 F.3d at 150.
The fact that some modelers may have chosen petitioners’
approach to this calculation does not automatically render
EPA’s approach unreasonable.
Moreover, EPA explained that using petitioners’ preferred
approach would not have changed its choice of model. See J.A.
4357–58. Petitioners have not shown otherwise, and EPA’s
explanation makes sense. As already explained, EPA did not
simply pick the model with the best calculated fit metrics
overall; rather, it picked the model with good fit metrics and
the best fit at low exposures.
Second, petitioners argue that EPA misused one of its own
figures in assessing the potential models. They argue,
Petitioners’ Brief 48, that EPA used the figure (at J.A. 2402) as

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if it represented the actual cancer risk predicted by the models
as opposed to the relative risk, when the model itself is clear
(as EPA confirms) that it depicts relative risks. But petitioners
point to nothing in the record that indicates EPA actually
misused the figure in the way petitioners suggest. In fact, the
record citation petitioners rely upon is to EPA’s discussion of
a different figure altogether; one submitted by TCEQ. See
Petitioners’ Brief 48 (citing J.A. 4352). And on
reconsideration, EPA explained that it focused on the figure for
the shape of the models in relation to the underlying data, just
as EPA’s figure says was appropriate. See J.A. 4354.
Petitioners have provided us no basis to disturb EPA’s
conclusion.
b
We turn now to petitioners’ arguments that EPA’s
selection of its chosen spline model was arbitrary and
capricious.
First, petitioners argue that EPA’s chosen model lacks
biological plausibility. Biological plausibility refers to the idea
that the model should be consistent with understandings of the
biology of cancer and how carcinogenic processes operate.
E.g., J.A. 2187. EPA explained its basis for concluding that its
chosen model was biologically plausible and why its choice did
not conflict with EPA’s own guidance. See J.A. 2617, 2740,
2754, 4345–46. EPA described that “plateau-like” dose-
response curves like its chosen spline model “have been seen
for many occupational carcinogens” and cited potential
explanations in the literature for that response. J.A. 2617; see
also J.A. 1950, 2393. Petitioners in their opening brief do not
directly challenge EPA’s explanation that similar dose-
response models are used for other carcinogens.
Second, petitioners argue that EPA’s chosen model is
inaccurate compared to real-world data, as calculated in the

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TCEQ “reality check.” Petitioners’ Brief 49–51, 55–57. That
“reality check” is a statistical analysis that ran EPA’s model
against real-world data to gauge the accuracy of the model’s
predictive power. J.A. 4386–88. Here, the TCEQ reality check
compared the number of lymphoid cancer deaths predicted by
EPA’s model with the number of lymphoid cancer deaths that
actually occurred in the NIOSH study data. See id. TCEQ
concluded from this reality check that EPA’s model
significantly overpredicted the number of lymphoid cancer
deaths from ethylene oxide exposure compared to the real-
world data on which the model was based. See id.
EPA adequately explained, however, why the TCEQ
reality check erred and thus did not call the accuracy of EPA’s
model into question. See id. EPA explained that the TCEQ
reality check did not appropriately account for the “healthy
worker effect” in its calculations and thus misused EPA’s
model. J.A. 4386. As EPA detailed, the healthy worker effect
is often seen in occupational epidemiology and reflects a
selection bias that leads to lower disease rates among workers
(like those involved in the NIOSH study) than the general
population. Id. Petitioners counter that TCEQ did, in fact,
account for a healthy worker effect. Reply Brief 29. But as
EPA explained, the healthy worker effect that TCEQ accounted
for (15 to 16%), J.A. 3752, was materially smaller than the
effect indicated by the relevant data (22 to 28%), J.A. 4387; see
also J.A. 4333–34. Petitioners did not address that explanation
in their briefing. Cognizant of our limited role in assessing
EPA’s evaluation of scientific data within its area of expertise,
we find this explanation adequate. Miss. Comm’n on Env’t
Quality, 790 F.3d at 150.
3
We turn next to EPA’s rejection of the TCEQ model
petitioners asked EPA to endorse. EPA adequately explained

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why it rejected that model: The TCEQ model did not fit the
data, and EPA’s chosen model did. See J.A. 4346–49. The
TCEQ model was a single line with a constant shallow slope at
both lower exposure and higher exposure levels. E.g., J.A.
4353. EPA explained that the TCEQ model was inconsistent
with the data, J.A. 4346, and with the pattern of all the other
model results indicating a plateauing response with a relatively
steeper slope in the lower exposure range of the NIOSH data,
a pattern the SAB specifically recognized, J.A. 4349. EPA
concluded that the TCEQ model’s inflexible shape thus
prevented it from usefully representing the NIOSH study data.
Id.; see also J.A. 4356, 4358.
Petitioners in effect argue that, had EPA not made the
purported errors addressed above in developing and selecting
its model, EPA would have selected the TCEQ model. But, as
described above, EPA reasonably developed and selected its
chosen spline model and adequately explained its reasons for
doing so.
As noted above, one of petitioners’ complaints pertained
to EPA’s use of figures representing the models. But, as
previewed, EPA’s reading of graphs does not undermine its
rejection of the TCEQ model. See J.A. 4350–52. Per EPA,
TCEQ purported to “adjust” an EPA figure that graphed the
models to show how the TCEQ model was in fact consistent
with the other models and the data. See J.A. 3799–800, 4350–
52. But, as EPA explained, that “adjusted” figure
inappropriately shifts the TCEQ model vertically—and while
this shift makes the TCEQ model appear more consistent with
the other modeling results, it is inappropriate to simply shift the
model up on the y-axis. J.A. 4350–51. As EPA noted, the
result was that TCEQ’s own adjusted figure suggests that its
model predicts a person with no additional exposure faces
twice their baseline cancer risk—a prediction of doubled risk
from no additional exposure cannot be correct. Id. TCEQ’s

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“adjusted” figure thus does not demonstrate that its model is
consistent with the other models and data. Accordingly, it does
not undermine EPA’s reasons for rejecting the TCEQ model.
4
Finally, we turn to EPA’s rejection of petitioners’ studies
of cancer incidence in tobacco smokers and data about
endogenous and background levels of ethylene oxide that
petitioners contend run contrary to the NIOSH data and EPA’s
model. Again, EPA acknowledged that evidence and gave an
adequate explanation for not altering its conclusions.
a
Petitioners point to studies showing no link between
ethylene oxide and lymphoid cancer in tobacco smokers.
Petitioners’ Brief 31–33. EPA provided two reasons for why
the conclusions of those studies could not be relied on. See J.A.
4328, 4365–66. Petitioners fail to undermine either.
First, EPA explained that the studies lack a quantitative
analysis of the relationship between lymphoid cancer and
ethylene oxide specifically. J.A. 4365–66. The studies did not
account for the interactions between the multiple carcinogens
in cigarette smoke, and thus faced the issue of what EPA terms
on appeal “confounding exposures.” EPA also explained that
even if the studies had been limited to the relationship between
ethylene oxide and lymphoid cancer, the studies still lacked a
sufficient quantitative analysis of that relationship showing
how the studies’ observed lymphoid-cancer rates compared
with the rate of non-smokers. J.A. 4365–66.
Petitioners do not even acknowledge the “confounding
exposure” explanation in their opening brief. Petitioners argue
on reply that EPA did not provide that rationale in the
rulemaking. Reply Brief 26–27. EPA did not use that phrase,
but in substance it provided the very same rationale it repeats

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on appeal. See J.A. 4365–66. Petitioners also do not
sufficiently undermine EPA’s explanation that the smoker
studies they rely upon did not have a sufficient quantitative
analysis to make them reliable. See id.
Second, EPA explained that the studies use an unvalidated
method—a hemoglobin biomarker—as a proxy to measure
ethylene oxide exposure. J.A. 4328, 4366. Per EPA, the
method was not validated to assess the low environmental
exposures that EPA was examining (in contrast to high
occupational exposures), and the biomarker is a less accurate
proxy regardless because smoking causes other changes that
could affect it. Id. Petitioners forfeited any challenge to this
rationale by failing to address it until their reply brief. See Bd.
of Regents of Univ. of Washington v. EPA, 86 F.3d 1214, 1221
(D.C. Cir. 1996).
b
Petitioners also point to data about endogenous and
background levels of ethylene oxide that they argue show such
levels were higher than what EPA assumed for purposes of its
model. Petitioners’ Brief 33–35; Reply Brief 27–28. Per
petitioners, higher background levels would make it harder to
assess additional health impacts from low environmental
exposures if additional exposures were a statistically
insignificant variation from background levels.
EPA acknowledged this evidence but rejected it on two
grounds. First, EPA rejected petitioners’ study as “provid[ing]
little quantitative data,” “highly speculative,” and offering
findings of only an “exploratory and qualitative nature.” J.A.
4363. Second, EPA acknowledged that if, as petitioners
suggested, there were reliable and high measurements of
endogenous and background levels, that would make it more
difficult to measure risks from marginal additional exposures.
E.g., J.A. 2475. But EPA explained that it is not possible to

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identify background levels of ethylene oxide with confidence
because of how difficult it is to reliably monitor and measure
such low levels. See J.A. 4366–67. EPA also explained how
the NIOSH study mitigated these general concerns. See J.A.
4361. Petitioners do not directly engage with the reasons EPA
gave for rejecting the studies, see Petitioners’ Brief 33–35;
Reply Brief 27–28, and they therefore fail to show EPA acted
arbitrarily or capriciously.
* * *
Petitioners’ approach to statistical modeling and the TCEQ
model itself may have advantages. But EPA’s explanations of
its model development and selection sufficiently articulate a
rational connection between the facts and the choices EPA
made, including in response to petitioners’ critiques. For
purposes of our arbitrary-and-capricious review, that is
enough.
B
We turn now to petitioners’ procedural arguments that
EPA improperly relied exclusively on its cancer-risk
assessment in promulgating the Rule, failed to respond to
National Academy of Sciences (“NAS”) recommendations as
required by 42 U.S.C. § 7607(d)(3)(C), and avoided
meaningful public comment on the bases for its decision. None
of these arguments has merit.
1
First, petitioners contend that EPA improperly relied
exclusively on its 2016 ethylene oxide cancer-risk assessment
in promulgating the Rule and that this conflicted with
commitments EPA made to Congress and with EPA’s own
guidance. Petitioners’ Brief 25–29. Petitioners point to EPA’s
commitment to Congress in a 1999 report that EPA would
“consider[] all credible and readily available assessments” in

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evaluating health risks from emissions of hazardous air
pollutants. J.A. 4580. EPA’s guidance similarly indicates that
EPA will “use all relevant information, . . . evaluate that
information based on sound scientific practices[,] . . . and reach
a position based on careful consideration of all such
information.” J.A. 5800.
Petitioners contend that EPA broke those promises by
relying exclusively on its 2016 cancer-risk assessment in this
rulemaking. But EPA considered petitioners’ studies and
explained why it found them unreliable. And when the TCEQ
assessment became available in finalized peer-reviewed form
after the close of the public comment period, EPA granted
reconsideration and considered it. Nothing in EPA’s guidance
or otherwise required EPA to agree with petitioners’ preferred
studies or assessments. Instead, EPA was required to consider
that information, and it did so.
Finally, petitioners suggest that EPA’s reliance on its 2016
ethylene oxide cancer-risk assessment is improper because that
assessment was not subject to APA notice-and-comment or
immediate judicial review. Petitioners’ Brief 28–29; see also
Chem. Mfrs Ass’n v. EPA, 28 F.3d 1259, 1263 (D.C. Cir. 1994)
(IRIS values are not final agency actions and thus are not
subject to direct APA challenge). But the IRIS value is not
shielded from public comment or judicial review: It is subject
to public comment and can be challenged when it is used in a
rulemaking, as this very case demonstrates.
2
Next, petitioners argue that EPA failed to respond to NAS
recommendations as required by 42 U.S.C. § 7607(d)(3)(C).

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But none of the NAS recommendations to which petitioners
point required a response from EPA in promulgating the Rule.
For certain rules, including the Rule at issue here,
42 U.S.C.§ 7607(d)(3)(C) requires EPA to include in the notice
of proposed rulemaking a statement of any “pertinent findings,
recommendations, and comments” by the NAS and explain any
divergence in the proposed rule. In a 2011 report, the NAS
reviewed EPA’s IRIS assessment for formaldehyde. J.A.
1642–1846. And in a 2014 report, an NAS committee
reviewed the IRIS process generally and ongoing EPA efforts
to improve it. J.A. 1471–1641. The NAS has not specifically
reviewed the IRIS value for ethylene oxide.
Petitioners argue that EPA violated Section 7607(d)(3)(C)
and acted arbitrarily and capriciously in not identifying the
2011 and 2014 NAS recommendations and explaining any
divergence in the proposed rule. Petitioners’ Brief 38–41. But
as EPA explained in responding to comments on
reconsideration, the NAS reports to which petitioners point
included general recommendations for the IRIS program and
did not make any specific recommendations about the IRIS
ethylene oxide cancer-risk assessment. See J.A. 4310–11.
Further, EPA reasonably proceeded with the Rule without
waiting for further improvements to the IRIS program
generally. As the 2014 NAS report noted, EPA was
undertaking efforts and making substantial progress in
improving various aspects of the IRIS process generally. E.g.,
J.A. 1496. And the NAS recommendations themselves
recognized that the recommended improvements were of an
ongoing nature, e.g., J.A. 1623, 1626, and that those long-term
efforts should not delay individual IRIS assessments, e.g., J.A.
1670–71 (“[NAS] is not recommending that EPA delay the
revision of the formaldehyde assessment to implement a new
approach.”), 1625.

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In any event, EPA stated that, even if it had made the NAS-
recommended changes to the IRIS program prior to finalizing
the 2016 ethylene oxide cancer-risk assessment, it would not
have changed the result. J.A. 4310. Petitioners’ argument to
the contrary is purely speculative.
3
Petitioners’ final procedural argument is that EPA denied
them the opportunity for “meaningful public comment”
because EPA did not provide its reasons for rejecting the TCEQ
assessment until the Reconsideration Decision. Petitioners’
Brief 54–57. This too fails.
As already explained, the TCEQ assessment was not
available in final, peer-reviewed form until after the public
comment period on the rulemaking had closed. 85 Fed. Reg.
at 49098 & n.12. When the final version of the TCEQ
assessment became available, petitioners were able to submit it
for EPA’s consideration. See J.A. 4098–108. EPA granted
reconsideration, invited public comment on the TCEQ model,
and then explained why it was rejecting that alternative
approach. Id. The Clean Air Act specifically envisions that the
Administrator will “convene a proceeding for reconsideration”
in this fashion if new and “central” information becomes
available after the period for public comment. 42 U.S.C.
§ 7607(d)(7)(B). Petitioners fail to show they were deprived
of a meaningful opportunity to comment.
Petitioners alternatively argue that EPA should have
considered the draft, not-peer-reviewed version of the TCEQ
assessment that was available during the initial public comment
period. E.g., Petitioners’ Brief 56. But petitioners fail to show
that EPA acted unreasonably in waiting to evaluate the final,
peer-reviewed version, or that this was inconsistent with EPA’s
past practice. None of petitioners’ examples involve EPA
considering a draft assessment during the public comment

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period. Petitioners do identify one instance in which EPA
considered a draft assessment after the comment period closed,
but that is not sufficient to show that EPA must always consider
non-final studies during its comment periods.
More broadly, EPA provided multiple opportunities for
meaningful public comment on the issues petitioners are
focused on. Those opportunities included not just two rounds
of public comment during the eighteen-year process leading to
the 2016 cancer-risk assessment, but also an initial round of
public comment and further public comment on
reconsideration in this rulemaking proceeding, not to mention
that EPA also responded to comments submitted outside those
comment periods. See, e.g., J.A. 1394–99, 1465–70, 1933–54,
2698–737, 2815–24, 4292–394. Petitioners had ample
opportunity to meaningfully comment on these issues.
C
Finally, petitioners argue that 42 U.S.C. § 7412(f)(2) is an
unconstitutional delegation of congressional authority.
Petitioners’ Brief 57–59. Petitioners forfeited this argument by
failing to raise it in the rulemaking as required by the Clean Air
Act’s mandatory exhaustion rule. 42 U.S.C. § 7607(d)(7)(B).
Indeed, we have specifically held that the Act’s mandatory
exhaustion rule applies to nondelegation challenges. Heating,
Air Conditioning & Refrigeration Distribs. Int’l v. EPA,
71 F.4th 59, 64–65 (D.C. Cir. 2023). That holding squarely
applies here. Petitioners observe that in Heating we suggested
that the Act’s exhaustion requirement might not be mandatory
in all circumstances. Reply Brief 30. But the footnote they
point to suggested only that the requirement might not apply to
cases raising certain challenges directly in district court.
Heating, 71 F.4th at 65 n.2. That situation is not presented
here.

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IV
For the foregoing reasons, the petitions for review are
denied.
So ordered.

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