Opinion ID: 4521335
Heading Depth: 2
Heading Rank: 1

Heading: The Function and Context of the Core Model

Text: “Whether [the core model] is exempt under (b)(5) depends not only on the intrinsic character of the [core model] itself, but also on the role it play[s] in the administrative process.” Lead Indus. Ass’n, Inc. v. Occupational Safety and Health Admin., 610 F.2d 70, 80 (2d Cir. 1979). We thus begin by describing both the core model and its role within the broader OMEGA context. Both EPA and NRDC 3 We further decline to address NRDC’s additional arguments regarding the segregability of the OMEGA model machine code and the foreseeable harm requirement of 5 U.S.C. § 552(a)(8)(A)(i)(I) because resolving those issues is also not necessary to resolve this case. 10 submitted declarations detailing the workings of the OMEGA model, and these declarations are largely consistent in their depictions.4 While the NRDC declarations are somewhat more detailed, EPA did not dispute their accuracy before the district court and does not do so before us on appeal. We draw on this undisputed factual record to form our understanding of the core model and its context within OMEGA. Each “run” of the OMEGA model involves five components or stages. In the first component, input data is loaded into the model. The inputs are Excel spreadsheets filled with raw data that establish the factors and constraints to be modeled in that run of OMEGA. These inputs include (1) market data, including the characteristics of the vehicles at issue and current emissions levels; (2) technology data, such as the available emissions-reduction options and their 4 EPA submitted declarations from William L. Wehrum, the then-assistant administrator for the EPA Office of Air and Radiation (“OAR”); and William Charmley, the director of the Assessment and Standards Division within the EPA Office of Transportation and Air Quality (“OTAQ”), which falls under OAR. NRDC submitted declarations from Margo Oge, the former director of OTAQ; Nicholas Lutsey, a program director at the International Council on Clean Transportation; and Dave Cooke, a senior vehicles analyst at the Union of Concerned Scientists. 11 costs; (3) scenario data, primarily the GHG standard being modeled; and (4) other data relevant to the projection, such as anticipated fuel prices. Once the input files have been loaded, the second component takes over. A series of pre-processors take the raw input data and organize it into datasets to facilitate the modeling. For example, one pre-processor groups together technologies that might commonly be implemented together while another accounts for emissions-reduction technologies already in use to avoid doublecounting. The third component is the core model, which consists of a series of algorithms, written in the C# computer programming language. These algorithms “run thousands of calculations” on the processed input data to forecast the emissions-reduction technologies automakers would likely incorporate to meet the simulated GHG standard in the particular scenario created by the input data. J. App’x 131 ¶13. The core model begins by “determin[ing] the specific emission standard applicable for each manufacturer and its vehicle class (car or truck). Then the model determines the emission standard applicable to each manufacturer’s car and truck sales.” Id. at 87 ¶20. With the emissions goals identified from the input data, the core model 12 “considers the range of technology packages available to each automaker’s individual vehicles” and applies different combinations of the available technologies to an automaker’s fleet until it meets the simulated GHG standard in the most cost-effective way possible. Id. at 131 ¶11. The core model results are turned into a series of output Excel files, the fourth component of OMEGA.5 The outputs detail the technologies automakers are projected to deploy as well as the costs of compliance. In the final component, the raw output data is put through a series of post-processors, which organize the results into a more user-friendly format and provide additional analysis. EPA can then review the results of the run to get a sense of the compliance time and costs likely to be associated with the simulated scenario.