Natural Exceptions or Exceptional Natures? Regulatory Science and the Production of Rarity

Abstract

The Exceptional Events Rule (EER) of the Clean Air Act was intended to address “exceptional” air quality events but, in practice, the way the rule is employed has significant impacts on regulatory data sets that are used to understand and manage air quality. Through this rule, the Environmental Protection Agency is entangled in the politics of classification, striving to separate the unnatural from the natural and the exceptional from the common with important consequences for air quality data and regulation. If deemed exceptional, the data can be removed from the regulatory record, not only altering our understanding of air quality—and, importantly, risk and exposure—but also the management of it. By analyzing regulatory data sets, texts, and appeals, this article explores the consequences of the rule’s data exclusions. I argue that the act of producing “natural exceptions” has another unintended consequence: It inadvertently creates exceptional natures; that is, natures that despite their common occurrence are deemed rare. By repeatedly removing data, the EER changes understandings of normal or expected events and becomes a powerful tool for deregulation. Ironically, even as regulations produce exceptional natures, they are simultaneously undermined by them, leading to regular and repeated surprises, unnoticed hazards, undetected exposures, and deregulation.

美国《清洁空气法案》的“例外事件规则”（Exceptional Events Rule, EER）旨在处理“例外”的空气质量事件。但在实践中, EER的使用方式对理解和管理空气质量的监管数据产生了重大影响。EER使得美国环境保护局卷入了分类政治, 试图区分非自然和自然、特殊和普通, 给空气质量数据和监管带来了严重后果。如果被视为例外, 就可以从监管记录中排除这些数据。这不仅改变了我们对空气质量（尤其是风险和暴露）的理解, 还改变了对空气质量的管理。通过分析监管数据、文本和诉讼, 本文探讨了EER数据排除的后果。我认为, “自然的例外”行为产生了意外后果：它无意中创造了例外的自然；即, 常见自然被视为罕见。通过反复排除数据, EER改变了对正常或预期事件的理解, 成为放松管制的有力手段。具有讽刺意味的是, 监管产生特殊自然的同时也受到它的破坏, 导致了经常性和重复性的意外、未被注意到的危险、未被发现的风险以及监管的放松。

La Regla de Eventos Excepcionales (EER) de la Ley del Aire Limpio se expidió para enfrentar los eventos “excepcionales” de la calidad del aire, aunque, en la práctica, el modo como la norma es empleada tiene impactos significativos sobre los conjuntos de datos reglamentarios que se usan para entender y manejar la calidad del aire. A través de esta norma, la Agencia de Protección Ambiental tiene que meterse en la política de clasificación, esforzándose por separar lo no natural de lo natural y lo excepcional de lo común, con consecuencias importantes para calidad de los datos y la regulación. Si se consideran excepcionales, los datos pueden eliminarse de los registros regulatorios, no solo alterando nuestra comprensión de la calidad del aire –y, sobre todo, del riesgo y la exposición– sino también su gestión. Analizando los conjuntos de datos regulatorios, los textos y las apelaciones, este artículo explora las consecuencias de las exclusiones de datos de la norma. Sostengo que el acto de producir “excepciones naturales” tiene otra consecuencia inesperada: Crea inadvertidamente naturalezas excepcionales; es decir, naturalezas que, pese a ser comunes, se consideran raras. Al eliminar repetidamente datos, la EER cambia la manera como se comprenden los eventos normales o esperados, convirtiéndose en una poderosa herramienta de desregulación. Irónicamente, incluso cuando las regulaciones producen naturalezas excepcionales, estas son simultáneamente socavadas por aquellas, lo cual conduce a sorpresas regulares y repetidas, peligros inadvertidos, exposiciones no detectadas y desregulación.

Key Words:

• Clean Air Act
• data exclusion
• dust
• environmental management
• ignorance
• outlier

关键词:

• 《清洁空气法案》
• 数据排除
• 灰尘
• 环境管理
• 无知
• 异常。

Palabras clave:

• atípico
• exclusión de datos
• ignorancia
• Ley del Aire Limpio
• manejo ambiental
• polvo

Acknowledgments

I thank the many colleagues who gave feedback on this work. I am especially grateful for the insightful feedback and support from Rebecca Lave, Gregory Simon, Adrianne Kroepsch, William Travis, and Laura Nash, as well as the three anonymous reviewers and the Annals editor. Thanks to Erica Clifford for the design of graphics.

Funding

The author acknowledges the financial support of the Babbitt Dissertation Award, Western Water Assessment, the Social Science Research Council, and the Charles Redd Center for Western Studies.

Notes

1 Another form of naturalness and boundary work is also at play here. The thresholds used to divide safe and unsafe levels of dust are deeply social. The regulatory concern assigned to different levels of dust is also shaped by conceptions of what is natural.

2 PM₁₀ refers to particulate matter—airborne particles—that have a diameter of ten micrometers or less. This is one of two sizes of particles measured and regulated by the EPA. Importantly, PM₁₀ includes dust but is not fully made up of dust, because the instruments collect all particles in that size class, which can include other sources like industrial emissions. Hence, there can be a lot of uncertainty about what are the sources and causes of PM₁₀ rates, but in the desert U.S. Southwest, dust is considered an important factor, often even a dominant factor.

3 The majority of dust-related fatalities in this report come from large, multicar pile-ups. Dust impacts to health are not well studied or understood, however, and are not fully included in this calculation.

4 The categories other than exceedance days (blue) actually start before 2007 when the rule was established. This is likely not because this designation predated the rule but rather is indicative of the long time frames involved in regulation. It is a time-intensive process, and these earlier events were probably designated as exceptional once the rule passed to avoid nonattainment status.

5 It is hard to find these cases, because there is no national database of exceptional events materials and not all state governments post the community dissents. There also are not as many community dissents as in other cases of environmental deregulation because these exclusions are not often something communities are aware of. I have found another example of the Sierra Club in Kansas also fighting the designation (see Volland [2013]). Others likely exist that I am not aware of.

6 The definition of dust is not well defined, so although many people think of dust as PM₁₀, PM_2.5 can also include particles that would be considered dust but likely mixed with a greater concentration of particles made through combustion (by cars, industry, etc.). In general, smaller particles travel much further and might be considered “fine dust” from further sources than larger particles that might represent regional or local dust systems.

7 Additionally, these events surpass standards for PM_2.5, which are finer particles than the PM₁₀ events in Maricopa County. Generally, smaller particles travel further, so local and regional dust is often larger (i.e., PM₁₀) and global dust events like the Saharan events experienced in Houston are finer (i.e., PM_2.5). Although they have important differences, including different standards, both can be elevated by dust storms.

Additional information

Notes on contributors

Katherine R. Clifford

KATHERINE R. CLIFFORD is a Researcher in the Western Water Assessment at the University of Colorado, Boulder, CO 80302. E-mail: [email protected]. Her research examines questions of environmental knowledge, regulation, and decision making in the context of environmental change.