Issues with ozone attainment methodology for Houston, TX

To comply with the federal 8-hr ozone standard, the state of Texas is creating a plan for Houston that strictly follows the U.S. Environmental Protection Agency's (EPA) guidance for demonstrating attainment. EPA's attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houston's ozone violations at monitoring sites are realized as gradual hour-to-hour increases in ozone concentrations, or by large hourly ozone increases that exceed up to 100 parts per billion/hr. Given the time profiles at the violating monitors and those of nearby monitors, these large increases appear to be associated with small parcels of spatially limited plumes of high ozone in a lower background of urban ozone. Some of these high ozone parcels and plumes have been linked to a combination of unique wind conditions and episodic hydrocarbon emission events from the Houston Ship Channel. However, the regulatory air quality model (AQM) does not predict these sharp ozone gradients. Instead, the AQM predicts gradual hourly increases with broad regions of high ozone covering the entire Houston urban core. The AQM model performance can be partly attributed to EPA attainment guidance that prescribes the removal in the baseline model simulation of any episodic hydrocarbon emissions, thereby potentially removing any nontypical causes of ozone exceedances. This paper shows that attainment of all monitors is achieved when days with observed large hourly variability in ozone concentrations are filtered from attainment metrics. Thus, the modeling and observational data support a second unique cause for how ozone is formed in Houston, and the current EPA methodology addresses only one of these two causes.     

An appraisal of emissions control requirements in the California South Coast Air Basin

The purpose of this study is to evaluate the effect of reductions of reactive organic gases (ROG) and NO_x emissions on short-term O₃ and NO₂ concentrations and annual average NO₂ concentrations in the California South Coast Air Basin. Short-term air quality predictions were obtained by applying the Systems Applications Airshed Model to summer O₃ and autumn NO₂ episodes. Effects of emission controls on annual NO₂ concentrations were estimated using CDM and a new parcel tracking model NOXTRAK. Results for the summer O₃ episode indicate that ROG emission reduction in an effective means for reducing peak O₃ concentrations. NO_x emission reduction imposed in addition to ROG emission reductions are counterproductive in reducing peak O₃ concentrations. The modeling results also suggest that attainment of the 1-h federal O₃ standard requires ROG emission reductions on the order of 80% from 1987 levels. Results for the autumn NO₂ episode indicate that NO_x emission reductions approximating those recommended in a proposed Air Quality Management Plan (about 22%) will result in only small (about 5%) reductions in the peak NO₂ concentrations. ROG emission reduction may be more effective than NO_x emission reduction in reducing the peak NO₂ concentration. For the episode studied, a reduction of 36% in ROG emissions is estimated to result in a reduction in peak NO₂ concentrations commensurate with that required to attain the 1-h state NO₂ standard. Model calculations also indicate that the federal NO₂ standard may not be meet by 1987 at one or two stations, but may blosely approached.     

Air Quality Modeling and Decisions for Ozone Reduction Strategies

Abstract

Despite the widespread application of photochemical air quality models (AQMs) in U.S. state implementation planning (SIP) for attainment of the ambient ozone standard, documentation for the reliability of projections has remained highly subjective. An “idealized” evaluation framework is proposed that provides a means for assessing reliability. Applied to 18 cases of regulatory modeling in the early 1990s in North America, a comparative review of these applications is reported. The intercomparisons suggest that more than two thirds of these AQM applications suffered from having inadequate air quality and meteorological databases. Emissions representations often were unreliable; uncertainties were too high. More than two thirds of the performance evaluation efforts were judged to be substandard compared with idealized goals. Meteorological conditions chosen according regulatory guidelines were limited to one or two cases and tended to be similar, thus limiting the extent to which public policy makers could be confident that the emission controls adopted would yield attainment for a broad range of adverse atmospheric conditions. More than half of the studies reviewed did not give sufficient attention to addressing the potential for compensating errors. Corroborative analyses were conducted in only one of the 18 studies reviewed. Insufficient attention was given to the estimation of model and/or input database errors, uncertainties, or variability in all of the cases examined. However, recent SIP and policy‐related regional modeling provides evidence of substantial improvements in the underlying science and available modeling systems used for regulatory decision making. Nevertheless, the availability of suitable databases to support increasingly sophisticated modeling continues to be a concern for many locations. Thus, AQM results may still be subject to significant uncertainties. The evaluative process used here provides a framework for modelers and public policy makers to assess the adequacy of contemporary and future modeling work.     

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.     

Air quality modeling and decisions for ozone reduction strategies

Despite the widespread application of photochemical air quality models (AQMs) in U.S. state implementation planning (SIP) for attainment of the ambient ozone standard, documentation for the reliability of projections has remained highly subjective. An "idealized" evaluation framework is proposed that provides a means for assessing reliability. Applied to 18 cases of regulatory modeling in the early 1990s in North America, a comparative review of these applications is reported. The intercomparisons suggest that more than two thirds of these AQM applications suffered from having inadequate air quality and meteorological databases. Emissions representations often were unreliable; uncertainties were too high. More than two thirds of the performance evaluation efforts were judged to be substandard compared with idealized goals. Meteorological conditions chosen according regulatory guidelines were limited to one or two cases and tended to be similar, thus limiting the extent to which public policy makers could be confident that the emission controls adopted would yield attainment for a broad range of adverse atmospheric conditions. More than half of the studies reviewed did not give sufficient attention to addressing the potential for compensating errors. Corroborative analyses were conducted in only one of the 18 studies reviewed. Insufficient attention was given to the estimation of model and/or input database errors, uncertainties, or variability in all of the cases examined. However, recent SIP and policy-related regional modeling provides evidence of substantial improvements in the underlying science and available modeling systems used for regulatory decision making. Nevertheless, the availability of suitable databases to support increasingly sophisticated modeling continues to be a concern for many locations. Thus, AQM results may still be subject to significant uncertainties. The evaluative process used here provides a framework for modelers and public policy makers to assess the adequacy of contemporary and future modeling work.     

Photochemical dispersion modeling: Review of model concepts and applications studies

Over the last decade, the development and application of sophisticated atmospheric models that simulate the transport and dispersion of ozone and its precursors have advanced rapidly. Further advancements are most likely to be found in more complete temporal and spatial characterization of photochemical smog formation processes via measurement. This paper provides an overview of the development of atmospheric photochemical dispersion models, first discussing in general terms the various physical processes occurring in the atmosphere that govern the formation, transport, and ultimate fate of ozone. Procedures for representing these physical processes in mathematical terms are presented next. Nearly all of the photochemical models in use today are derived from the semiempirical atmospheric diffusion equation, though theoretical formulations vary depending on which of the various terms in the pollutant mass balance equation are deemed significant for the application at hand. Examples of recent applications of the range of available photochemical model are presented, together with estimates of the accuracy of each generic modeling concept. Several topics warranting future research are identified, including the need to incorporate explicitly more of the stochastic (or probabilistic) nature of the atmosphere into the form of current photochemical model predictions (i.e., estimates of the variance and higher order moments of the predicted concentration distribution).