Regulatory Impact Analysis of the Proposed Revisions to the National Ambient Air Quality Standards for Lead (This page intentionally left blank) October 2008 Regulatory Impact Analysis of the Proposed Revisions to the National Ambient Air Quality Standards U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impact Division Air Benefit-Cost Group Research Triangle Park, North Carolina (This page intentionally left blank) ES.1 OVERVIEW This Regulatory Impact Analysis (RIA) estimates the incremental costs and monetized human health benefits of attaining a revised primary lead (Pb) National Ambient Air Quality Standard (NAAQS). There are important overall data limitations and uncertainties in these estimates. They are described in section E.S.4 below. Hypothetical control strategies were developed for final NAAQS of 0.15 μg/m3 plus several alternative lead standards. These alternatives include at least one more stringent and one less stringent alternative than the selected standard, consistent with the OMB Circular A-4 Guidelines. This summary outlines the basis for and approach used for estimating the incremental costs and monetized benefits of these standards, presents the key results of the analysis, and highlights key uncertainties and limitations. This Regulatory Impact Analysis (RIA) provides illustrative estimates of the incremental costs and monetized human health benefits of attaining a revised primary lead (Pb) National Ambient Air Quality Standard (NAAQS) within the current monitoring network of 189 monitors representing 86 counties. Many of the highest-emitting lead sources do not have nearby Pb-TSP monitors, and it is important to note that there may be many more potential nonattainment areas than have been analyzed in this RIA. It is important to note at the outset that overall data limitations are very significant for this analysis, compared to other NAAQS reviews. One critical area of uncertainty is the limited TSP-Pb monitoring network (discussed in chapter 2). Because monitors are present in only 86 counties nationwide, the universe of monitors exceeding the final NAAQS level of 0.15 µg/m3 represent only 16 counties. It is important to note that data limitations prevented us from identifying a full range of controls which would bring eight of these counties all the way to attainment of the final NAAQS. It is also important to note that because many of the highest- emitting Pb sources in the 2002 NEI do not have nearby Pb-TSP monitors (see section 2.1.7), it is likely that there may be many more potential nonattainment areas than have been analyzed in this RIA. In addition, EPA would prefer to use a detailed air quality model that simulates the dispersion and transport of lead to estimate local ambient lead concentrations with the hypothetical alternative emission control strategies expected under the NAAQS. Although models with such capabilities are available for pollutants for which EPA frequently conducts air quality analyses (e.g., particulate matter and ozone), regional scale models are currently neither available nor appropriate for lead.1 As discussed in Chapter 3, EPA developed an air quality assessment tool to estimate the air quality impacts of each lead emissions control strategy. In setting primary ambient air quality standards, EPA’s responsibility under the law is to establish standards that protect public health, regardless of the costs of implementing a new standard. The Clean Air Act requires EPA, for each criteria pollutant, to set a standard that 1 U.S. Environmental Protection Agency (2007c), Review of the National Ambient Air Quality Standards for Lead: Policy Assessment of Scientific and Technical Information, OAQPS Staff Paper, section 2.4, EPA-452/R-07-013, Office of Air Quality Planning and Standards, RTP, NC. ES-1 protects public health with “an adequate margin of safety.” As interpreted by the Agency and the courts, the Act requires EPA to create standards based on health considerations only. The prohibition against the consideration of cost in the setting of the primary air quality standard, however, does not mean that costs or other economic considerations are unimportant or should be ignored. The Agency believes that consideration of costs and benefits is essential to making efficient, cost effective decisions for implementation of these standards. The impacts of cost and efficiency are considered by states during this process, as they decide what timelines, strategies, and policies are most appropriate. This RIA is intended to inform the public about the potential costs and benefits associated with a hypothetical scenario that may result when a new lead standard is implemented, but is not relevant to establishing the standards themselves. The analysis year for this regulatory impact analysis is 2016, consistent with the attainment year for the final lead NAAQS. For the purposes of this analysis, we assess attainment by 2016 for all areas. Some areas for which we assume 2016 attainment may in fact need more time to meet one or more of the analyzed standards, while others will need less time. This analysis does not prejudge the attainment dates that will ultimately be assigned to individual areas under the Clean Air Act, which provides flexibility to postpone compliance dates, provided that the date is as expeditious as practicable. EPA presents this RIA pursuant to Executive Order 12866 and the guidelines of OMB Circular A-4.2 These documents present guidelines for EPA to assess the benefits and costs of the selected regulatory option, as well as one less stringent and one more stringent option. OMB Circular A-4 also requires both a benefit-cost, and a cost-effectiveness analysis for rules where health is the primary effect. Within this RIA we provide a benefit-cost analysis. ES.2 Summary of Analytic Approach Our assessment of the selected lead NAAQS includes several key elements, including specification of baseline lead emissions and concentrations; development of illustrative control strategies to attain the standard in 2016; development of an air quality assessment tool to assess the air quality impacts of these control strategies; and analyses of the incremental impacts of attaining the alternative standards. Figure ES-1 provides an illustration of the methodological framework of this RIA. Additional information on the methods employed by the Agency for this RIA is presented below. Overview of Baseline Emissions Forecast and Baseline Lead Concentrations The baseline lead emissions and lead concentrations for this RIA are based on lead emissions data from the 2002 National Emissions Inventory (NEI) and lead concentration values for 21 lead monitors included in the 2003-2005 Pb-TSP NAAQS-review database. Consistent with the PM2.5 NAAQS RIA and ozone RIA, no growth factors were applied to the 2002 NEI emissions estimates to generate the emissions or air quality projections for 2016. Where 2 U.S. Office of Management and Budget. Circular A-4, September 17, 2003. Found on the Internet at <http://www.whitehouse.gov/omb/circulars/a004/a-4.pdf>. ES-2 possible, however, we adjusted these values to reflect the estimated control efficiency of MACT standards with post-2002 compliance deadlines, because the 2002 NEI and observed lead concentrations during the 2003-2005 period would not reflect the impact of MACT controls reasonably anticipated to be in place by 2016. The analysis includes similar adjustments for compliance measures simulated by the September 2006 revision to the PM2.5 NAAQS (as included in the illustrative PM2.5 control strategy described in the PM2.5 NAAQS RIA) and measures listed in the 2007 Missouri Lead SIP revisions.3 Development of Illustrative Control Strategies Our analysis of the emissions control measures required to meet the selected standard is limited to controls for point source emissions at active sources inventoried in the 2002 NEI. To identify point source lead emissions controls for our analysis, we collected information on PM control technologies, assuming that the control efficiency for PM would also apply to lead emissions. Most of this information was obtained from EPA's AirControlNET database, but a limited number of controls were identified from New Source Performance Standards and operating permits that apply to facilities with similar Source Classification Codes as the point sources included in our analysis.4 Controls identified through this process include major emissions controls, such as fabric filters, impingement-plate scrubbers, and electrostatic precipitators; and minor controls, such as increased monitoring frequency, upgrades to continuous emissions monitors, and diesel particulate filters for stationary sources. In addition, we modeled replacement of the large primary lead smelter in Jefferson County, Missouri with a more modern, lower-emitting smelter. To identify the least-cost approach for reaching attainment in each area, EPA developed a linear programming optimization model that systematically evaluates the changes in air quality and costs associated with controlling each source to find the optimal control strategy for each area. The optimization model first identifies the measures that each source would implement if it were controlled as part of a local lead attainment strategy. Based on these controls, the optimization model then identifies sources to control such that each area would reach attainment at the least aggregate cost possible for the area. It is important to remember that, compared to recent NAAQS RIAs, our current knowledge of the costs and nature of lead emissions controls is relatively poor. Lead in ambient air has not been a focus for all but a few areas of the country for the last decade or more; the selected standard of 0.15 μg/m3 represents a substantial tightening of the existing NAAQS. As a result, although AirControlNET contains information on a large number of different point source controls, we would expect that State and local air quality managers would have access to additional information on the controls available to the most significant source.