te on the total annual NOx emissions from own and neighboring states. Because prevailing winds between 30˚N and 50˚N in latitude blow from the Southwest [25], and because emissions from up to 1000 km away can affect local air quality, state j is considered a neighbor of state i if it is located within 1000 km either to the South, West or Southwest of state i. The unit of observation is an ozone monitoring site in a given year. County population density and county per capita income are controlled for. The controls reduce the possibility of spatial autocorrelation in the error term due to omitted variables that have a spatial dimension.

The state-by-state source-receptor transport coefficients measure how an additional 1000 tons of NOx emissions in one state affects the 90th percentile ozone level in a downwind state. The individual coefficients are available in an online appendix.6 For instance, if Ohio emitted an additional 100,000 tons of NOx over the course of one year, which is less than 10% of its average annual emission of 1.17 million tons, the annual 90th percentile ozone level in Michigan would increase by a statistically significant 17 ppb. Some of the statistically significant source-receptor coefficients are negative; this is likely due to the non-monotonic nature of ozone formation.

One main advantage of the spatial econometric approach over the atmospheric chemistry modeling approach is that the estimates from the former approach have standard errors associated with them, and it is therefore possible to assess whether certain effects are statistically significant. For instance, while they both have positive sourcereceptor transfer coefficients, neither the impact of NOx emissions from Illinois on air quality in Indiana, nor the impact of NOx emissions from Ohio on air quality in New Jersey is statistically significant; without the standard errors, one may have mistakenly interpreted the effects to be positive.

Reference [19] reports, for each source state, the total net effect of NOx emissions from that state, as measured by the sum of its effect on air quality in all of its receptor states, including itself. Only coefficients that are significant at a 5% level are included in calculating the total net effect. Each of the total net values is an estimate of the impact of an additional 1000 tons of emissions in a particular state on ozone exposure throughout the rest of the country. These estimates could be used in the design of efficient environmental regulation, which would equate the marginal damage of pollution to marginal abatement costs across space [26]. For example, the resulting ratios of these estimates could be used as a starting point for the determination of a location-differentiated permit system. These estimates could therefore have a significant impact on policy.

6. Conclusions

My work in [19] uses spatial econometrics to analyze air pollution externalities. Results affirm the importance of regional transport in determining local ozone air quality. However, the transport of NOx can sometimes be a positive externality rather than a negative one; this is likely due to non-monotonicities in ozone production.

General features of the spatial econometric results are consistent with atmospheric science and with the results of atmospheric chemistry models. Ozone exhibits spatial correlation and, except in the Los Angeles basin, as is consistent with the science, this correlation is due to transport rather than simply to spatially correlated omitted variables. NOx and VOC emissions from up to 1000 km away have significant effects on ambient ozone concentrations. High temperature is correlated with high ozone levels.

The spatial econometric approach improves upon the atmospheric chemistry modeling approach because its estimates have standard errors associated with them, because it does not make prior assumptions on the parameters, and because spatial econometric models are less computationally expensive and take less time to run. Moreover, the spatial econometric approach yields a test for the appropriateness of a non-spatially differentiated NOx cap and trade program as well as state-by-state source-receptor transfer coefficients that can be used as a basis for a location-differentiated permit system.

Cap and trade programs have been used to decrease pollution in a variety of contexts. In the 1980s, a cap and trade program was used to facilitate the phase-out of stratospheric ozone-depleting chlorofluorocarbons. In the 1990’s, a cap-and-trade program was adopted to reduce sulfur dioxide emissions and consequent acid rain by 50 percent under the Clean Air Act amendments of 1990. Most recently, cap and trade programs have emerged as the preferred national and regional policy instrument to address carbon dioxide emissions linked with global climate change [27]. These non-spatially differentiated cap and trade system are appropriate for decreasing the target pollutant—whether it be chlorofluorocarbons, sulfur dioxide or carbon dioxide—because the source of the emissions did not matter. Only the overall quantity of the pollutant mattered to overall damages.

Similarly, a non-spatially differentiated NOx cap and trade program amongst multiple states would be an appropriate mechanism for reducing ozone pollution if it did not matter to ambient ozone concentrations whence each ton of NOx was emitted. A ton of NOx emitted from Indiana should have the same effect on Connecticut’s air quality as a ton of NOx emitted from Kentucky; only the total quantity of NOx emitted should matter. However, results show that is not the case: the location of NOx emissions does matter to overall ozone air quality. As a consequence, a non-spatially differentiated cap and trade program is not appropriate for either the states in the OTC or the states in the NOx SIP call as a mechanism for reducing ozone smog. Unlike cap and trade programs for chlorofluorocarbons, sulfur dioxide or carbon dioxide, a program that aims to decrease ozone pollution by capping and trading NOx pollution permits would need to be spatially differentiated in order to be effective.

Results of [19], particularly the state-by-state sourcereceptor transfer coefficients, have important implications for policy. Because NOx emissions in one state can affect the ozone air quality in other states, a regional approach to ozone smog control is needed. Moreover, rather than use a non-spatially differentiated NOx cap and trade program to reduce ozone smog, policymakers should use a spatially differentiated program, for example one that takes into account the state-by-state source-receptor coefficients estimated in [19], instead.

7. Acknowledgements

I benefited from discussions with Gary Chamberlain, Roger Bivand, Richard Cebula, Wayne Gray, Francois Goreaud, Larry Goulder, Richard Green, Arthur Havenner, Matthew Kahn, John List, Robert Stavins, James Stock, James Wilen, and Roberton Williams, and from comments from participants at the Interdisciplinary Spatial Statistics Workshop 2004 in Paris and at workshops in econometrics at Harvard University and MIT. Tom McMullen from the EPA extracted the annual countylevel NOx and VOC data for me. Arlene Fiore and Tracey Holloway provided information about atmospheric chemistry models. Tom Helms, Daniel Jacob, Dave McKee, and Joe Pinto provided valuable information about ozone chemistry and regulation. I thank Dennis Flynn for giving me a tour of the Waltham, MA air quality monitoring station. I received financial support from an EPA Science to Achieve Results graduate fellowship, a National Science Foundation graduate research fellowship and a Repsol YPF-Harvard Kennedy School Pre-Doctoral Fellowship in energy policy. Conference expenses were generously subsidized by an Environmental Economics Program at Harvard University Conference Travel Grant. All errors are my own.


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1According to [1], only 30 states plus DC were identified.

2For a scientific explanation of NOx titration, see [11].

3The majority of models are Eulerian models, which simulate the concentration and transport of air pollution at every grid point and time step. Another type of model is a Lagrangian model, which follows a given air parcel, but must make the assumption that each air parcel is independent and therefore that there are no interactions between air parcels.

4Virginia was not a signatory of the MOU. The OTC NOx Budget Program ran from 1999 to 2002 and is now replaced by the NOx SIP call [21].

5Wisconsin was removed via court order. Georgia is not listed on: http://www.dep.state.wv.us/item.cfm?ssid=8&ss1id=295 but Georgia’s website does mention NOx SIP call: http://www.air.dnr.state.ga.us/ sspp/noxsipcall/


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