Toxic air pollution is arguably the most pressing human health concern today, accounting for approximately 7–9 million premature deaths worldwide. In the United States, more than 200,000 early deaths are attributable to air pollution and almost half of these are estimated to result from emissions originating in neighboring states–i.e., transboundary air pollution. Yet more than 40% of these deaths are assessed to be cause by air pollution produced by neighboring states. This article examines the governance mechanisms used by the US to address this transboundary issue, with a focus on section 126 of the Clean Air Act. All section 126 petitions submitted from 2000–2022 (N = 13), critical factors including case length, evidence used, and case outcome are compiled and assessed using comparative case analysis. From this analysis, four main issues and corresponding recommendations to enhance US governance mechanisms related to section 126 are developed: the need for policy and procedural reforms to adjust the burden of proof on petitioning states the need for clarity on the criteria for sufficient evidence for petitioners; potential practical measures to address challenges with response timelines in petitioning process; and the means by which section 126 petitioning capacity can be made accessible to all states. The article concludes with a discussion on the significance of modeling techniques employed in the petitioning process by the US EPA and states to facilitate informed–and fair–decision-making processes.
Research Article
Interstate Air Pollution Governance in the United States: Exploring Clean Air Act Section 126
https://doi.org/10.21203/rs.3.rs-3555222/v1
This work is licensed under a CC BY 4.0 License
Journal Publication
published 19 Jun, 2024
You are reading this latest preprint version
Human-produced toxic pollution is reshaping the Earth system and planetary health (Rockström et al. 2009; 2023; Persson et al. 2022). As part of this, it is directly harming human health. In fact it is estimated to be the largest source of human-caused early mortality, resulting in at least 7-9 million premature deaths and 275 million disability adjusted life years—that is, a year of human life lived with a substantially restrictive morbidity or ailment—annually (Fuller et al. 2022; Landrigan et al. 2017). The forms of human-produced pollution that humans and planetary ecosystems are now exposed to are wide ranging, from an estimated 22 megatons of plastic waste now entering ecosystems annually (Landrigan et al. 2023) to over 350,000 registered industrial chemicals on global markets with, in 2017 when combined with plastics and other novel entities, 92 million tons of feedstocks extracted to produce them (Persson et al. 2022; UNEP 2019). And industrial pollution is only increasing, with the number of corresponding premature mortality increasing by 66% since 2000 (Fuller et al. 2022).
The single largest toxic pollution stream harming human health today is toxic air pollution (Fuller et al. 2022; Burnett et al. 2018; Pope et al. 2020; Vohra et al. 2021). Of the estimated at least 9 million annual premature deaths from toxic pollution, Fuller et al. (2022) attribute 7 million of those deaths to air pollution. However, estimates vary, for example Vohra et al. (2021) estimate that at least 10 million deaths are attributable to air pollution from fossil fuel combustion alone. Importantly, most of these premature deaths occur in low- and middle-income countries and low-income areas within wealthy countries (Fuller, Sandilya, and Hanrahan 2019; Fuller et al. 2022; Yin et al. 2020; Burnett et al. 2018). While there are many other hazardous air pollutants, such as nitrogen oxide and ozone, the primary air pollutant hazard driving premature mortality is PM2.5—or airborne particles 2.5 microns in size or smaller.
There are many challenges presented in attempting to regulate air pollution. For example, there is the challenge of stationary versus mobile air pollution sources, often categorized as point sources and nonpoint sources of air pollution (Lame and Marcantonio 2022). There is also the challenge of measuring or estimating the amount of pollution produced per emitting unit, whether mobile or not. And, layered atop these is the challenge of jurisdictional authority and accountability (Lame and Marcantonio, 2022). As a result, most air pollution today is not effectually regulated. In fact, there is no comprehensive international environmental policy convention that regulates toxic air pollution, leaving it to national pollution monitoring and enforcement. There are some regional frameworks such as the European 1979 Convention on Long-range Transboundary Air Pollution; however, most geographic regions and boundaries do not have similar governance. This poses a particular challenge for national, and even within nations where regulatory authority is decentralized to sub-national units, environmental management and policy given the growing presence and effect of transboundary air pollution (Jung, Choi, and Yoon 2022; Zhao et al. 2022; Zhang et al. 2017). Transboundary air pollution is argued to be one of the largest growing challenges to ecological and national sovereignty, especially given the attributable human health impacts (Green and Colgan 2013; McCarthy 2005). But even in domestic contexts, its challenges are felt. In the United States, almost half of all premature deaths from air pollution are caused by emissions from neighboring states (Dedoussi et al. 2020). To work against this challenge, recent regulatory rule making has been leveraged to combat transboundary air pollution, specifically the “Good Neighbor” provision of the Clean Air Act, a policy that has proven contentious and currently a hot topic of debate given the implications for alleged perpetrating states and their downwind recipients (US EPA 2023).
Using the United States’ “Good Neighbor” provision of the US Clean Air Act as an example, this article illustrates the challenges of air quality management across political boundaries. It first explores the history of litigation regarding transboundary air pollution, then maps out the regulatory process for air pollution permitting, monitoring, and enforcement.
The Clean Air Act (CAA), first passed by Congress in 1963, is a comprehensive regulatory statute governing stationary and mobile air pollution sources in the United States. Among its many provisions, the CAA includes the establishment of the National Ambient Air Quality Standards (NAAQS) for specific air pollutants. Given the transitory nature of air pollution, a state or county’s ability to achieve its NAAQS is dependent not only on its own sources of emissions but also those from neighboring areas. In order to address this transboundary reality, the CAA includes a ‘Good Neighbor’ provision, section 126, to manage potential upwind-downwind issues. There is an abundance of literature examining the Good Neighbor Provision from a legal perspective, a portion of which also addresses section 126 of the Clean Air Act. Luh’s (2021) “Being a Good Neighbor: Evaluating Federal Regulation of Interstate Air Pollution under the Cross-State Air Pollution Rule,” presents a comprehensive recent history of section 126 petitions, as well as detailing the distinct regulatory niches of the Good Neighbor Provision (section 110(a)(2)(D)(i)(I)) and section 126. Among the issues with past interstate transport programs outlined by Luh, the shortcomings of the Cross-State Air Pollution Rule (CSAPR) is shown to be most critical and contentious. The recently implemented Good Neighbor Plan that was established by the US EPA in March 2023, however, has not been assessed regarding its ability to reconcile issues identified with the previous CSAPR by Luh and others.
The Good Neighbor Provision was a component of the CAA Amendments of 1970 (Clean Air Act Amendments of 1970). Initially requiring “intergovernmental cooperation,” the provision was reinforced in 1977 with stricter requirements for the inclusion of plans to address interstate transport in state implementation plans (SIPs), which are collections of state regulations to meet the NAAQS (Clean Air Act Amendments of 1977). Section 126 was part of the 1977 amendments to the CAA and includes a) the requirement that states provide written notice to all potentially affected states about “major proposed new (or modified) source[s],” b) a mechanism for states or political subdivisions to petition EPA to find that a “source or group of stationary sources” violates the Good Neighbor Provision, and c) requirements for implicated sources, which must cease operation no more than “three months after such finding,” unless EPA determines that the source can achieve compliance within three years (42 U.S.C. § 7426(b) 2023).
Section 126 was meant to fill a gap in the Good Neighbor Provision. In 1977, Congress pointed out the ineffectiveness of relying on upwind states to regulate interstate pollution when it is the downwind states that have the “incentive and need to act” (H.R. REP. No. 95-294, at 330, 1977). Therefore, section 126 provides an avenue for downwind states to take action by petitioning EPA to directly regulate a source or group of sources, whereas the Good Neighbor Provision is a state-level remedy whereby the EPA initiates a call for SIPs from upwind states responsible for regulating the sources within their borders. This procedural difference between the Good Neighbor Provision and section 126 is one of three differences highlighted by Luh (2021). The second is a difference in regulated entities: states are regulated by the Good Neighbor Provision, whereas stationary sources are regulated by section 126. The third difference is in EPA’s role. The Good Neighbor Provision only allows EPA to directly regulate sources if a state has not adequately revised its SIP, at which point a federal implementation plan is required. In contrast, section 126 petitions call for direct regulation from the EPA, which is mandated to do so upon approval of the petition (42 U.S.C. § 7410(k)(5) 2023).
Another critical component of interstate air pollution governance in the U.S. is the various interstate transport programs that have been issued, starting with the Nitrous Oxide (NOx) Budget Trading Program in 2003 (EPA, 2023a). Whereas the Good Neighbor Provision and section 126 are laws created by Congress, these programs are rules created by EPA. They have included cap-and-trade, or emissions trading, of NOx, sulfur dioxide (SO2), and particulate matter (PM) allowances for between 19 and 28 states, primarily in the eastern United States. Each interstate transport program has faced litigation, sometimes from environmental groups calling for stricter regulation, as in North Carolina vs. EPA (North Carolina v. EPA, 2008), and sometimes from industry groups calling for more lenience, as in EPA v. EME Homer City Generation, L.P. (Kendall and Sweet 2014), with states and local governments participating on both sides of the aisle. The four governance mechanisms discussed—CAA amendments, section 126 petitions, interstate transport programs, and litigation—influence one another in a regulatory ecosystem with feedback loops.
Two key issues with EPA’s regulatory framework for interstate air pollution have been identified in previous investigations and are expanded on here (Luh 2021). The first is that the burden of proof on downwind states filing section 126 petitions is both unclear and unmanageable. The EPA expects petitioning states to conduct a global comparative analysis proving that cost-effective reductions can be made at each implicated source (New York vs. EPA 2020, line 1217). Upwind states possess the information necessary for such an analysis, and it is often difficult or impossible for downwind states to obtain this data (New York vs. EPA 2020, line 1217). This necessitates downwind states to access and analyze appropriate data, contradicting the intended purpose of providing states with an additional, expedited avenue for interstate pollution reduction for NAAQS compliance.
Appendix W of Title 40 of the Code of Federal Regulations (CFR) Part 51, also known as the Guideline on Air Quality Models, specifies the modeling techniques accepted by the EPA (“preferred models”) and outlines requirements that “alternative models” must meet to be used for regulatory purposes (CAA, 2023). Additionally, when interstate transport programs are promulgated, the EPA has historically released technical support documents that provide modeling guidance especially applicable to states building a petition case. The most recent of these documents was released in 2023 alongside the Good Neighbor Plan (EPA, 2015). For the 2015 ozone NAAQS, the EPA recommends using the Weather Research and Forecasting (WRF) (Shamarock et al., 2008) model to generate meteorological fields required as input in a chemical transport model called CAMx (EVIRON, 2016). The modeling recommendations are thorough (Federal Register 2020). Nonetheless, even with pollutant transport modeling that meets EPA’s standards and shows attribution, it is often insufficient to get a section 126 petition approved. This is because downwind states must also prove that there are cost-effective pollution abatement measures that would significantly reduce the air pollution they are receiving from upwind sources. This study examines the relationship between the modeling methods used by petitioning states and the resulting outcomes of the petitions.
A critical disconnect exists between section 126 and the Good Neighbor Provision (Luh, 2021). The Good Neighbor Provision deals with SIPs, and upwind states must include in their SIPs provisions prohibiting pollution “in amounts which will contribute significantly to nonattainment in…any other State” (42 U.S.C. § 7410(a)(2) 2023). The submission of a section 126 petition against a state implies that either its SIP is inadequate, or it has failed to implement its SIP. However, the EPA is not required to review an implicated upwind state’s SIP when it receives a section 126 petition (New York vs. EPA 1988, line 578). One solution for this shortcoming is for section 126 petitions to automatically trigger a SIP call (Luh, 2021). The data and modeling techniques used by upwind states in their SIPs would then be re-evaluated and compared to those used by downwind states in their petitions.
In analyzing interstate air pollution there is a fundamental complexity challenge such that, for a given area, how much pollution originates within a particular state versus a neighboring state must be determined, in order to allocate responsibilities between the state in question and upwind states (Farber, 2015). This also means the attribution of upwind emissions to a number of contributing upwind states to the downwind state must be delineated. This need for attributable delineation makes interstate air pollution regulation complex both technically and governmentally. The way the system is currently designed, though states are primarily focused on implementing the CAA within their borders (e.g., designation recommendations and most SIP components), they must also evaluate their pollution contributions to downwind states and provide plans to reduce any significant contribution to downwind nonattainment areas. States may be less motivated to do the latter, as their constituents would more likely support emissions cuts to improve the air they breathe than to improve the air out-of-state, at potential economic costs. As recently as 2023 states failed to produce satisfactory transport SIPs. The EPA disapproved of the transport SIPs of 19 states, with modeling issues cited as a key factor in the disapproval determination of several states (Federal Register 2023). This article explores this key factor to understand the challenges states have faced in their petitioning using section 126 and potential ways to improve this avenue for faster and better relief for downwind recipients of air pollution.
3.1 Information Sources
For the cases of petitions under Clean Air Act Part A Section 126, information on the EPA rules in the Code of Federal Regulations in the National Archives, specifically title 40, part 52, on Approval and Promulgation of Implementation Plans, was located and utilized to map the process. Critical factors of interest related to this research from the case descriptions included in these sources were extracted and are included in Table 1 and Fig. 1 (see below). Technical guidance from the EPA for modeling is also generally released in tandem with new interstate transport programs and is included and assessed here.
3.2 Case Selection
To examine the efficacy of Clean Air Act Part A Section 126, we identified and documented the population of cases of petitions (see Table 1) from 2000–2023. This step helped us to understand the range of evidence, timelines, and outcome diversity in the cases.
For case comparisons (Table 1), critical independent factors included in the table were 1) petitioning state, 2) date filed, 3) date of final EPA action, 4) length of case, 5) implicated emitters (upwind stationary sources and states), 6) evidence used, with a particular focus on modeling, and 7) evidence source, meaning entities that generated the evidence. We also included critical dependent information in the table for the outcome/determination and the EPA rationale for the decision. These factors, distilled from case related records, were highlighted to provide for comparisons between the quality of petitions as well as outcomes across petitions. From this population of cases, we selected a typical case (Gerring et al. 2007) to represent the population of cases. Maryland was selected because it was similar to most petitions filed since 2000 with regard to actions taken by the state, EPA, and the US Court of Appeals for the D.C. Circuit. Despite this, it is influential as a case for the purpose of system mapping in that the D.C. Circuit ultimately granted, in part, Maryland’s petition for review of EPA’s denial of its initial section 126 petition. In other words, Maryland’s petition went further than most in the legal system, though it was not ultimately approved by EPA.
3.3 Process and Case Analysis
To illustrate and analyze both the EPA designation process for an attainment or nonattainment area and EPA accountability mechanisms for Clean Air Act (CAA) implementation, Kumu (2023) was used, to develop the visualization of relationship maps (see Figs. 1 and 2). The interactive maps produced and included in this article are publicly available on the Kumu platform included under the titles 1) Clean Air Act: Designation and Sanctions Processes and 2) Maryland Section 126 Petition.
The case comparison table (Table 1) was used to identify potential relationships between the variables, such as the type, source, and quality of the evidence-base for petitions and EPA determination. This step facilitated findings regarding information needs for Section 126 petition preparation, sufficiency of EPA guidelines for petitions, the role of modeling, and the relationship between determinations on petitions and the independent factors in the table, if any. Given the different contexts and circumstances of the petition, we were not looking for causal homogeneity (Collier et al. 2004; Ragin 2004), but a general pattern. For pattern-matching (Yin, 2003), the expectation was a relationship between the quality and of the evidence for the petition with regard to EPA standards and the outcome of the determination.
For the case analysis of the Maryland petition, the Maryland Section 126 Petition figure (Fig. 1) was used to visualize and detail case information to follow the Maryland petition from submission to decision. The combination of information made it possible to examine the movement of the petition through the process with relevant details of the evidence and the ruling. The analysis included examining challenges identified in the literature, such as the burden of proof on downwind states and lack of clarity from the EPA about what constitutes sufficient evidence; as well as highlighting new challenges, such as the practicality of response timelines and states' unequal capacities to generate evidence. This analysis allowed for systematic review of the process with regard to the evidentiary benchmarks for the petitioning state.
The legal actions taken in response to Maryland’s 2016 section 126 petition are displayed in Fig. 1, and Table 1 lists all of the section 126 petitions filed since 2000 with the seven assessment variables introduced in the methods section. The 2016 Maryland petition illustrated in Fig. 1 implicated 36 coal plants in Indiana, Kentucky, Ohio, Pennsylvania, and West Virginia (EPA 2018). According to CAA section 126(b), EPA has 60 days to either make a finding that the implicated sources do, indeed, violate the Good Neighbor Provision, or deny the petition. Determining that this was insufficient time to complete the review process, EPA extended their timeline to respond by six months (EPA 2018). This was not unique to Maryland’s case as the EPA extended timelines to respond to North Carolina’s 2004 petition; Warrick County and Newburgh, Indiana’s 2008 petition; both of New Jersey’s 2010 petitions; Eliot, Maine’s 2013 petition; Connecticut’s 2016 petition; Delaware’s 2008 petition and all four of its 2016 petitions; and New York’s 2018 petition.The legal actions taken in response to Maryland’s 2016 section 126 petition are displayed in Fig. 1, and Table 1 lists all of the section 126 petitions filed since 2000 with the seven assessment variables introduced in the methods section. The 2016 Maryland petition illustrated in Fig. 1 implicated 36 coal plants in Indiana, Kentucky, Ohio, Pennsylvania, and West Virginia (EPA 2018). According to CAA section 126(b), EPA has 60 days to either make a finding that the implicated sources do, indeed, violate the Good Neighbor Provision, or deny the petition. Determining that this was insufficient time to complete the review process, EPA extended their timeline to respond by six months (EPA 2018). This was not unique to Maryland’s case as the EPA extended timelines to respond to North Carolina’s 2004 petition; Warrick County and Newburgh, Indiana’s 2008 petition; both of New Jersey’s 2010 petitions; Eliot, Maine’s 2013 petition; Connecticut’s 2016 petition; Delaware’s 2008 petition and all four of its 2016 petitions; and New York’s 2018 petition.
This map displays the legal actions taken by EPA (orange), Maryland (green), and the D.C. Circuit (yellow) following Maryland’s submission of a section 126 petition in November 2016. Original figure; Data Source: HLS Environmental and Energy Law Program
Table 1 Assessment of Section 126 Petitions Since 20001
- The Federal Register includes EPA extensions of deadline for action on three additional section 126 petitions: one filed by Warrick County, IN, and the Town of Newburgh, IN, on 3/6/2008; one by the state of Delaware on 12/18/2008; and one by the town of Eliot, ME on 8/20/2013. These are not included in the table because there is no record of EPA final action in the register. Further investigation is required to determine whether EPA dropped the petitions because the petitioners did not have the resources to sue EPA and demand final action. A news article published one year after Eliot’s petition was filed says the EPA requested that Eliot consider withdrawing the petition, which the town rejected (https://www.seacoastonline.com/story/news/local/portsmouth-herald/2014/08/02/epa-should-help-not-hurt/36458357007/).
Maryland was not alone in suing EPA when it failed to make a finding by the extended deadline–Delaware, Connecticut, and New York are among the other states that brought suits to EPA in order to prompt a final action. For the petitions included in Table 1, EPA took between 14 and 27 months from the date the petition was filed to make a final determination. Section 126 is meant to provide states an expedited avenue for obtaining relief from interstate pollution in order to comply with NAAQS, often under deadlines (H.R. REP. No. 95–294, at 331, 1977). Clearly this avenue is not satisfying its intended purpose, as EPA consistently fails to meet its 60-day deadline, often only taking final action after being sued by the state.
The case of Maryland illustrates how slow response rates reduce the effectiveness of section 126. Maryland submitted its petition when the 2008 ozone NAAQS were in effect, howevery by the time EPA took final action on the petition, the 2015 ozone NAAQS had come into effect. At the public hearing for EPA’s denial of the petition, Maryland challenged EPA’s assessment of the petition only for the 2008 NAAQS (Federal Register 2018). As the 2015 NAAQS are more stringent, Maryland asserted that EPA’s analysis “necessarily demonstrate[d] that the named sources are also linked to the same monitor under the 2015 ozone standard.” EPA leaned on technicalities, responding that Maryland’s petition specifically requests the agency make a decision with regard to the 2008 NAAQS and that EPA had not informed the public of any findings with regard to the 2015 NAAQS.
As with North Carolina and Delaware’s petitions, the EPA ultimately denied Maryland’s petition on the basis that an existing regulation (which was not in existence at the time the petition was filed) addressed emissions from implicated facilities. One such “existing regulation” was the Cross-State Air Pollution Rule (CSAPR) Update, which was finalized in September 2016 (Federal Register 2016). Two of Delaware’s petitions were submitted earlier that year, which indicates the possibility that these petitions influenced the CSAPR Update–if not EPA’s decision to make an update, perhaps the nature of the updates made. Further research is needed to determine whether the CSAPR Update resulted in emissions reductions at the sources implicated in the section 126 petitions, to the extent that they no longer violate the Good Neighbor Provision.
Maryland and Delaware’s follow-up actions suggest they were not satisfied with the CSAPR Update as the sole response to their petitions, as only seven days after EPA finalized the denial, Maryland petitioned the D.C. Circuit to review EPA’s decision (Federal Register 2017), and less than a month later, Delaware did the same (USCA 2018). In a brief submitted to the D.C. Circuit, Maryland said that “EPA’s reliance on the CSAPR Update to deny the petition was arbitrary and capricious,” the updated rule would not satisfy the Good Neighbor Provision, and EPA could not use it to avoid the additional regulations proposed in the petition (USCA 2018).
The D.C. Circuit took almost as long to make a finding as EPA had taken, ultimately denying Delaware’s petition and granting Maryland’s in part, finding that the EPA was too quick to dismiss the state’s argument that four electric generating units (out of the 36 included in the petition) should be required to operate non-catalytic controls (Federal Register 2018). This finding came down to a question of cost-effectiveness: EPA stated in the CSAPR Update Rule that non-catalytic controls were not cost-effective (Federal Register 2016), but in Wisconsin vs. EPA the D.C. Circuit concluded that this statement was “impermissibly partial” and that a comparative cost-effectiveness analysis was in order (USCA 2019).
This points again to the issue that downwind states must not only prove that implicated sources in upwind states are contributing at least one percent of the NAAQS to receptors within their borders that are in danger of nonattainment–they must also prove that cost-effective reductions can be made at those sources. In order to assess the weight EPA places on each of these factors (proof of pollution contribution and proof of cost-effectiveness), we examine the modeling techniques used by petitioning states in light of EPA’s final action. If EPA prioritizes proof of pollution contribution, we would expect petitions to be approved for which the state used modeling techniques that a) closely follow the guidelines provided in EPA’s technical support documents and/or b) produce relatively low error and bias, compared with EPA’s interstate transport modeling.
The only section 126 petition since 2000 to have been officially approved by EPA is New Jersey’s 2010 petition, which asked EPA to find that an electric generating unit (EGU) in Pennsylvania was contributing illegally to 1-hour sulfur dioxide (SO2) levels in New Jersey (Martin 2010). The New Jersey Department of Environmental Protection (NJDEP) used both the AERMOD (EPA, 2022) model recommended by the EPA for 1-hour SO2 at transport distances of less than 50 kilometers, and an alternative CALPUFF model (EPA 2010). AERMOD assumes meteorological conditions do not change over the domain of interest for each unit of time considered (e.g., every hour) and that the transport and dispersion processes occur directly in the downwind direction of the emitting unit. Despite recent advances to the model, it is generally not accurate at distances larger than 50 km, as the assumption of uniformity and constant meteorological conditions is likely to be unrealistic. Conversely, CALPUFF, which is now included in the list of alternative models that the EPA suggests for more complex analyses or to quantify impacts at a larger distance (e.g., hundreds of kilometers), is able to account for spatio-temporal variability of meteorological conditions, as well as for chemical reactions in the atmosphere. Such a model is more computationally expensive than simpler alternatives, such as AERMOD.
NJDEP’s petition included a model validation study, concluding that “CALPUFF performed better and produced predictions of greater accuracy than AERMOD (EPA 20210).” Both models found that the impacts of the EGU were significantly higher than the NAAQS, so EPA would have hypothetically approved the petition with either model, but because the CALPUFF model showed far greater impacts, the use of this alternative model would have required a higher level of emissions reductions. Different meteorological inputs and model setup were key drivers of discrepancies in the predicted SO2 concentrations. While NJDEP provided evidence that CALPUFF performed better than AERMOD at one specific location in complex terrain, EPA did not deem this result sufficient to consider the use of CALPUFF for the entire domain, as prior AERMOD evaluations at five complex terrain locations were cited to indicate a good performance of AERMOD. This case demonstrates the importance of conducting a detailed model evaluation. If NJDEP had provided stronger evidence that CALPUFF performed better than AERMOD (i.e., model evaluation at multiple locations instead of just one), EPA might have considered the CALPUFF results credible, which could have led to more drastic emission controls. However, it is possible that NJDEP did not have the resources necessary to conduct a sufficiently detailed model evaluation, further affirming the issue of the excessive burden of proof on downwind states.
Returning to the case of Maryland, the state’s 2016 petition used modeling conducted by the University of Maryland, which consisted of the chemical transport model CAMx (EPA 2018). This model receives as input meteorological fields from WRF and emissions from the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system (Houyoux et al., 2000), which is recommended by EPA. In EPA’s final ruling on the petition, they find that Maryland provided sufficient evidence for steps one and two of the four-step transport framework used by EPA to assess petitions: 1) receptors within the state were in danger of nonattainment and 2) upwind sources contributed above one percent of the NAAQS to these receptors (Federal Register 2018). EPA denied the petition at step 3, at which they use a multi-factor test to assess the cost, potential for NOx reduction, and downwind air quality effects of the proposed emissions reduction strategy.
Maryland’s petition provided evidence that the installed NOx control equipment at the analyzed EGUs were not optimally operated, resulting in higher NOx emissions deemed responsible for ozone exceedances experienced in Maryland (EPA 2018). Maryland’s petition focused on ensuring that more controls were run at the units during the ozone season, to prevent higher NOx emissions, and urged EPA to implement regulations on control practices. EPA did not find that Maryland’s petition was technically deficient, but rather finalized the denial based on an independent assessment run by EPA, from which they concluded there were no additional cost-effective reductions for the EGUs named in the petition (Federal Register 2018). According to this assessment, the emissions reduction strategy proposed by Maryland would have cost $3,400 per ton of NOx reduced, and, as laid out in the CSAPR Update, a control strategy is only deemed cost effective if its marginal cost is no more than $1,400 per ton.
The preceding analyses of the New Jersey and Maryland cases indicate that a) EPA has high standards for accepting anything other than their recommended modeling techniques, with the expectation that states not only prove the new model is adequate, but also that the recommended model is inadequate; and b) high-quality evidence of the effects of upwind source emissions is not enough for a petition to be accepted, as EPA’s multi-factor cost-benefit assessment ultimately determines the fate of a petition.
Another factor to consider is the absence of certain states from Table 1, which may be just as revealing as the petitions that have been filed. Recent investigations conducted in 2020 found that 50.90% of premature deaths caused by air pollution in Ohio in 2018 were from out of state emissions, yet Ohio has not submitted a section 126 petition since 2000 (Dedoussi et al 2020). An evaluation of the relationship between the budget a state allocates to its environmental agency and the frequency with which it has submitted section 126 petitions would shed some light on whether this mechanism is accessible to all states, or only those with large budgets.
Our analysis and previous studies illuminate three primary issues with section 126 as a mechanism to provide timely relief to downwind states: lengthy response timelines; the excessive burden of proof placed on downwind states; and the lack of clarity about what constitutes sufficient evidence. These three issues together increase the cost, complexity, and unpredictability of filing a section 126 petition. States with fewer resources are unlikely to invest the time, money, and personnel necessary to create a section 126 petition and take the follow-up legal actions that are often necessary (suing EPA and taking the case to the DC Circuit).
Further research is needed to determine the reasons for the EPA’s consistent failure to meet the 60-day deadline for making findings on section 126 petitions. Potential reasons may involve insufficient resources or personnel allocated to this issue, but may also involve a lack of political will or resistance and/or incentives from actors, such as corporations, that would be hurt by the stricter regulations proposed in section 126 petitions. If the former, insufficient resources, is the primary reason, the solution is more straightforward: dedicate more resources to the EPA offices that review and respond to section 126 petitions, either by increasing EPA’s overall budget or redirecting funds. The latter, lack of political will, is a more insidious and complex problem, which may be entrenched in the larger governance systems in which EPA operates. One way to combat this is to institutionalize a penalty to the EPA, perhaps in the form of a rule, for missing the deadline. Another potential solution is for EPA to impose a monetary penalty to be paid to the petitioning state when the deadline has been missed.
To reduce the burden of proof on downwind states, the conclusions of this sutdy align with and affirm previous findings (Luh, 2021): Downwind states should only be required to prove a) that monitoring receptors within their borders are in danger of nonattainment of NAAQS, and b) that stationary sources in upwind states are contributing at least one percent of the NAAQS to those receptors. he burden of proof would then shift to upwind states to demonstrate whether and how much reductions should be enforced at the implicated sources and by what “cost-effective” means (Luh, 2021). Our findings further indicate that, if petitioning states wish to use a modeling technique other than those recommended by the EPA, they should only have to prove that the new model is contextually adequate, not that the EPA’s recommended model is inadequate.
The New Jersey case illustrates how different models and model setups can lead to large discrepancies, thus posing the question of what information decision making should be based on. We recommend that the EPA establish concrete requirements, with regard to bias and error, for modeling results used in petitions. An effective first step would be to invest more in modeling advancements generally, as currently even the best models are arguably far too biased for reliable policymaking. The EPA Air Quality Modeling Final Rule Technical Support document of 2015 includes an evaluation of the EPA suggested modeling approach against monitoring sites that indicates that six of the U.S. climate regions have a mean bias within ± 5 ppb, while the Northern Rockies, the Northwest and the West have a mean bias larger than that, when considering days with a maximum daily average 8hr ozone concentration > 60 ppb. While these numbers are aligned with the performance benchmark in (Emery et al, 2017), they appear comparatively large if the attribution is based on 1% of the ozone standard (i.e., 0.75 ppb for an ozone limit of 75 ppb), thus prompting to invest in further model developments or in the use of more complex modeling tools. In order to reduce uncertainty for states considering submitting a petition, the EPA should make it clear that petitions with modeling results with error/bias below set numbers will be approved. We also recommend that the EPA increase clarity about the actions it is required to take upon approval of a petition. The EPA should establish a timeline for additional regulation of the implicated source(s) and for relief to downwind states–perhaps in the form of delayed nonattainment sanctions–if the source does not comply. Achieving this “clarity” may involve producing non-legal materials about section 126 and distributing them to states.
Finally, to ensure equal access and capacity for reciprocity, it is recommended that funding resources be made available to under-resourced states to aid their initiation and evidencing of section 126 petitions. These funds could be administered by a third party, as the work and potential political strife accompanying applications for the funds could pose a conflict of interest for the EPA.
Taken collectively, if these recommendations are followed, section 126 would be made accessible to all states. It would achieve the essence of the provision: the equal protection of states and their citizenry from an undue burden of toxic air pollution.
Acknowledgements
The authors acknowledge funding support from the Lucy Institute for Data and Society at the University of Notre Dame.
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No competing interests reported.