A Direct Sensitivity Approach to Predict Hourly Ozone Resulting from Compliance with the National Ambient Air Quality Standard

Abstract

In setting primary ambient air quality standards, the EPA's responsibility under the law is to establish standards that protect public health. As part of the current review of the ozone National Ambient Air Quality Standard (NAAQS), the US EPA evaluated the health exposure and risks associated with ambient ozone pollution using a statistical approach to adjust recent air quality to simulate just meeting the current standard level, without specifying emission control strategies. One drawback of this purely statistical concentration rollback approach is that it does not take into account spatial and temporal heterogeneity of ozone response to emissions changes. The application of the higher-order decoupled direct method (HDDM) in the community multiscale air quality (CMAQ) model is discussed here to provide an example of a methodology that could incorporate this variability into the risk assessment analyses. Because this approach includes a full representation of the chemical production and physical transport of ozone in the atmosphere, it does not require assumed background concentrations, which have been applied to constrain estimates from past statistical techniques. The CMAQ-HDDM adjustment approach is extended to measured ozone concentrations by determining typical sensitivities at each monitor location and hour of the day based on a linear relationship between first-order sensitivities and hourly ozone values. This approach is demonstrated by modeling ozone responses for monitor locations in Detroit and Charlotte to domain-wide reductions in anthropogenic NOx and VOCs emissions. As seen in previous studies, ozone response calculated using HDDM compared well to brute-force emissions changes up to approximately a 50% reduction in emissions. A new stepwise approach is developed here to apply this method to emissions reductions beyond 50% allowing for the simulation of more stringent reductions in ozone concentrations. Compared to previous rollback methods, this application of modeled sensitivities to ambient ozone concentrations provides a more realistic spatial response of ozone concentrations at monitors inside and outside the urban core and at hours of both high and low ozone concentrations.

Two reduced form air quality modeling techniques for rapidly calculating pollutant mitigation potential across many sources, locations and precursor emission types

“…This is because the Taylorexpansion approach was not expected to accurately estimate very large changes in emission inputs that were used in these out-ofsample simulations (e.g., cuts up to 70e99% of base levels). Previous studies have demonstrated the accuracy of DDM-3D for emission perturbations within ±50% (Cohan et al, 2005;Simon et al, 2012). This behavior was also evident in the validation analysis, where errors in the DDM-3D-based predictions for O 3 tended to increase with increasingly large cuts to NO x emissions from mobile sources.…”

“…For the remainder of the discussion, the hourly DDM-3D concentrations for the month are averaged in order to be consistent with the RSM output. However, the flexibility of hourly output from either model could be used to provide additional information on the impacts of emission cuts on different air quality metrics such as maximum 8 h average or peak daily ozone (e.g., Simon et al, 2012).…”

Assessing Temporal and Spatial Patterns of Observed and Predicted Ozone in Multiple Urban Areas

“…The methodology for adjusting observed O 3 to scenarios of 50% and 75% NO x reductions was adapted from the methods developed by Simon et al (2013) and by the U.S. EPA (2014a).…”

“…These reactions also result in the production of other oxidized nitrogen species, which form O 3 away from the emission source location while the wind transports the air mass, thus contributing to elevated O 3 downwind (Cleveland and Graedel 1979). As a result of this chemistry, decreasing NO x and VOC emissions generally decrease O 3 at times and locations in which O 3 concentrations are high (Simon et al 2013). In limited circumstances, reductions of NO x emissions can lead to O 3 increases in the immediate vicinity of highly concentrated NO x sources, whereas these same emissions changes generally lead to reductions of O 3 downwind over longer timescales (Cleveland and Graedel 1979; Kelly et al 2015; Murphy et al 2007; Sillman 1999; Xiao et al 2010).…”

Source apportionment and sensitivity analysis: two methodologies with two different purposes

“…to apportion the difference between the current atmosphere (and natural conditions) to specific human activities. Along the same lines, Simon et al (2013) used first-order sensitivity to construct emission response surfaces. To cope with potential nonlinearities and the need to compute higherorder derivatives, a powerful alternative is to compute firstorder sensitivities at several emission levels.…”