Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston,Texas

In Houston, some of the highest measured 8-hr ozone (O₃) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr, or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O₃ concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O₃ changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O₃ concentrations, the AQM predicted high O₃ over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O₃, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O₃ concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O₃ concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O₃ standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O₃, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.

Implications To show the attainment of the O₃ standard, the U.S. Environmental Protection Agency (EPA) requires the use of observations and model predictions under the assumption that simulations are capable of reproducing observed phenomena. The regulatory model is unable to reproduce observed behavior measured in the observational database. If the large observed hourly changes were indicative of a separate cause of high O₃, then the model would not include that cause. Inaccurate model predictions may prompt air quality regulators to enact control strategies that are effective in the modeling system, but prove ineffective in the real world.     

Evaluating Aggregate Terrestrial Impacts of Road Construction Projects for Advanced Regional Mitigation

This study presents a GIS-based database framework used to assess aggregate terrestrial habitat impacts from multiple highway construction projects in California, USA. Transportation planners need such impact assessment tools to effectively address additive biological mitigation obligations. Such assessments can reduce costly delays due to protracted environmental review. This project incorporated the best available statewide natural resource data into early project planning and preliminary environmental assessments for single and multiple highway construction projects, and provides an assessment of the 10-year state-wide mitigation obligations for the California Department of Transportation. Incorporation of these assessments will facilitate early and more strategic identification of mitigation opportunities, for single-project and regional mitigation efforts. The data architecture format uses eight spatial scales: six nested watersheds, counties, and transportation planning districts, which were intersected. This resulted in 8058 map planning units statewide, which were used to summarize all subsequent analyses. Range maps and georeferenced locations of federally and state-listed plants and animals and a 55-class landcover map were spatially intersected with the planning units and the buffered spatial footprint of 967 funded projects. Projected impacts were summarized and output to the database. Queries written in the database can sum expected impacts and provide summaries by individual construction project, or by watershed, county, transportation district or highway. The data architecture allows easy incorporation of new information and results in a tool usable without GIS by a wide variety of agency biologists and planners. The data architecture format would be useful for other types of regional planning.