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Did the Clean Air Act Amendments of 1990 really improve air quality?

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Abstract

The degree to which federal policies, such as the Clean Air Act (CAA), actually improve air quality is not fully understood. We investigate what portion of reductions in ambient fine particulate matter (PM2.5) that occurred 1999–2005 can be attributed to sulfur dioxide (SO2) and nitrogen oxide (NO x ) emissions reductions from implementation of title IV, phase 2, of the 1990 CAA Amendments. A detailed statistical model links sources and receptors over time and space to estimate the relationship between changes in emissions and observed improvements in air quality. We employ relatively transparent statistical methods incorporating uncertainty bounds to complement point estimates of the complex physico-chemical fate and transport models commonly used to estimate source-receptor relationships associated with long-range emissions transport. Monitor-specific estimates of changes in PM2.5 from changes in emissions from individual power plants are highly significant and mostly of the expected relative magnitudes for distance and direction from sources; and the model performs well on out-of-sample forecasts. Although we observe substantial model uncertainty, using our preferred specification, we estimate that the title IV, phase II emissions reduction policy implemented 1999–2005 reduced PM2.5 in the eastern USA by an average of 1.07 μg/m3, roughly 8 % (standard deviation, 0.11 μg/m3) versus a counterfactual of no change in emission rates per unit of energy input. On a population-weighted basis, the comparable reduction in PM2.5 is 0.89 μg/m3, roughly 6 %. This model presents a practical tool that can be used for policy analysis of air quality.

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Notes

  1. Using statistical techniques, Chay et al. (2003) do not find evidence that changes in TSP NAAQS attainment status for 1971–1972 were associated with changes in adult morality rates over the same period, although the authors suggest that results be viewed with caution due to several study limitations. Chay and Greenstone (2003) find that reductions in TSP corresponding to the timeframe of the 1981–1982 US recession are associated with lower infant mortality rates, especially for neonatal births. Highlighting the complex chemistry of ozone, Lin (2010) uses a spatial econometric approach to examine how changes in NOx emissions under a cap-and-trade program in one area affects ozone levels in another. Finding that without spatial restrictions such a program is not an effective policy mechanism, the author also notes some of the potential advantages of using statistical techniques, including the absence of assumptions about the functional form of relationships between ozone precursors and resulting ozone levels.

  2. Fixed effects are additional independent variables. They are logical variables designed to account for unobserved heterogeneity. They take on a value of 1 or 0 for each observation depending on whether the observation is true or not for that variable. Thus, for example, the site fixed effect is defined by \( R_{{iym}}^{{{i^{\prime }}}} = \left\{ {\matrix{ 1 &{{\text{if}}\,{i^{\prime }} = i} \\ 0 &{\text{otherwise}} \\ }<!end array> } \right. \). The fixed effects for year and month are defined similarly.

  3. Note that the emissions from industrial sources that opt into the Acid Rain Program are explicitly measured; those that do not opt in are included in the fixed-effects variables.

  4. We also cross-checked the Clean Air Markets data sets by comparing them with the National Emissions Inventory for 1999 and 2002, which included estimates of annual emissions for all point, mobile, and area sources.

  5. In other regressions (not shown), mixed specifications including weighted sums of NO x and SO2 also performed worse than SO2 alone.

  6. The actual coefficients for the two models are given in Table 4. To facilitate the comparison, we multiply the coefficients in the TEMP × EMIS specifications by the average temperature for the entire sample, 287.8°K.

  7. One can easily argue for other options here, although the convention in this type of analysis is to adopt similar assumptions. For example, based on the advice of a committee of outside experts, EPA adopted a similar approach in its analysis of costs and benefits of the Clean Air Act (EPA 1997). At the same time, there is substantial empirical evidence to support the notion that the Title IV emissions trading program actually encouraged innovation in pollution control technology (see Burtraw and Palmer 2004).

  8. The standard deviation is calculated by the procedure described in the online supplemental material. Without county-level temperature data, we were not able to calculate a standard deviation of the county estimates.

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Conflict of Interest

This study is supported by HEI Research Agreement #4742-RFA04-4/06-2.

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Correspondence to Richard Morgenstern.

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Glossary of statistical terms

FGLS: Feasible generalized least squares

MLE: Maximum likelihood estimation

MSE: Mean square error

OLS: Ordinary least squares

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Harrington, W., Morgenstern, R., Shih, JS. et al. Did the Clean Air Act Amendments of 1990 really improve air quality?. Air Qual Atmos Health 5, 353–367 (2012). https://doi.org/10.1007/s11869-012-0176-5

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