Meteorological based parameters and ozone exceedances in Houston and other cities in Texas.

In the Houston-Galveston-Beaumont (HGB) region considerable scientific effort has been directed at elucidating the relationships among atmospheric circulations and urban mixed-layer ozone concentrations. These studies of the HGB region have provided guidance on the conditions that are used herein to identify specific meteorological parameters that relate with observed exceedances of the National Ambient Air Quality Standard for ozone. These parameters were developed using 15 years of ozone concentrations and localized wind conditions enhanced by incorporating data from a private monitoring network. Using these data, several key parameters were found that described the most common meteorological conditions for an exceedance day in HGB. The most relevant parameters included: the wind direction at midnight, wind speeds from 0 to 6 LST, and the extent of wind direction rotation in a 24-hour period. These parameters, and the meteorological conditions they describe, were also found to occur in an analysis of observational data throughout the state of Texas suggesting large scale forces beyond the influence of a sea breeze. A mixed layer model was developed and shown to illustrate the large-scale synoptic forces found in the observational data. The meteorological parameters, and conditions they describe, could be part of a diagnostic model performance evaluation to assure that accurate predictions of ozone for Texas were not the result of compensating errors.Implications: This study identified meteorological-based parameters that coincided with observed exceedances of the National Ambient Air Quality Standard for ozone across the state of Texas. These parameters can be used in support of regulatory model performance evaluations to assure accuracy in predicting ozone conducive conditions. In Houston, the vast majority of meteorlogical ozone conducive days did not produce an exceedance, suggesting other as yet unidentified conditions that are necessary such as an intermittent emission of precursors.

Toward a consistent modeling framework to assess multi-sectoral climate impacts.

Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

Modeled response of ozone to electricity generation emissions in the northeastern United States using three sensitivity techniques.

UNLABELLED: Electrical generation units (EGUs) are important sources of nitrogen oxides (NOx) that contribute to ozone air pollution. A dynamic management system can anticipate high ozone and dispatch EGU generation on a daily basis to attempt to avoid violations, temporarily scaling back or shutting down EGUs that most influence the high ozone while compensating for that generation elsewhere. Here we investigate the contributions of NOx from individual EGUs to high daily ozone, with the goal of informing the design of a dynamic management system. In particular, we illustrate the use of three sensitivity techniques in air quality models-brute force, decoupled direct method (DDM), and higher-order DDM-to quantify the sensitivity of high ozone to NOx emissions from 80 individual EGUs. We model two episodes with high ozone in the region around Pittsburgh, PA, on August 4 and 13, 2005, showing that the contribution of 80 EGUs to 8-hr daily maximum ozone ranges from 1 to >5 ppb at particular locations. At these locations and on the two high ozone days, shutting down power plants roughly 1.5 days before the 8-hr ozone violation causes greater ozone reductions than 1 full day before; however, the benefits of shutting down roughly 2 days before the high ozone are modest compared with 1.5 days. Using DDM, we find that six EGUs are responsible for >65% of the total EGU ozone contribution at locations of interest; in some locations, a single EGU is responsible for most of the contribution. Considering ozone sensitivities for all 80 EGUs, DDM performs well compared with a brute-force simulation with a small normalized mean bias (-0.20), while this bias is reduced when using the higher-order DDM (-0.10). IMPLICATIONS: Dynamic management of electrical generation has the potential to meet daily ozone air quality standards at low cost. We show that dynamic management can be effective at reducing ozone, as EGU contributions are important and as the number of EGUs that contribute to high ozone in a given location is small (<6). For two high ozone days and seven geographic regions, EGUs would best be shut down or their production scaled back roughly 1.5 days before the forecasted exceedance. Including online sensitivity techniques in an air quality forecasting model can provide timely and useful information on which EGUs would be most beneficial to shut down or scale back temporarily.

Houston's rapid ozone increases: preconditions and geographic origins.

Many of Houston's highest 8-h ozone (O3) peaks are characterised by increases in concentrations of at least 40 ppb in 1 h, or 60 ppb in 2 h. These rapid increases are called non-typical O3 changes (NTOCs). In 2004, the Texas Commission on Environmental Quality (TCEQ) developed a novel emissions control strategy aimed at eliminating NTOCs. The strategy limited routine and short-term emissions of ethene, propene, 1,3-butadiene and butene isomers, collectively called highly reactive volatile organic compounds (HRVOCs), which are released from petrochemical facilities. HRVOCs have been associated with NTOCs through field campaigns and modelling studies. This study analysed wind measurements and O3, formaldehyde (HCHO) and sulfur dioxide (SO2) concentrations from 2000 to 2011 at 25 ground monitors in Houston. NTOCs almost always occurred when monitors were downwind of petrochemical facilities. Rapid O3 increases were associated with low wind speeds; 75 % of NTOCs occurred when the 3-h average wind speed preceding the event was less than 6.5 km h-1. Statistically significant differences in HCHO concentrations were seen between days with and without NTOCs. Early afternoon HCHO concentrations were greater on NTOC days. In the morning before an observed NTOC event, however, there were no significant differences in HCHO concentrations between days with and without NTOCs. Hourly SO2 concentrations also increased rapidly, exhibiting behaviour similar to NTOCs. Oftentimes, the SO2 increases preceded a NTOC. These findings show that, despite the apparent success of targeted HRVOC emission controls, further restrictions may be needed to eliminate the remaining O3 events.

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.

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.

Evaluation of relative response factor methodology for demonstrating attainment of ozone in Houston, Texas.

In 2007, the U.S. Environmental Protection Agency (EPA) released guidance on demonstrating attainment of the federal ozone (O3) standard. This guidance recommended a change in the use of air quality model (AQM) predictions from an absolute to a relative way. This was accomplished by using a ratio, and not the absolute difference of AQM O3 predictions from a historical year to an attainment year. This ratio of O3 concentrations, labeled the relative response factor (RRF), is multiplied by an average of observed concentrations at every monitor. In this analysis, whether the methodology used to calculate RRFs is severing the source-receptor relationship for a given monitor was investigated. Model predictions were generated with a regulatory AQM system used to support the 2004 Houston-Galveston-Brazoria State Implementation Plan. Following the procedures in the EPA guidance, an attainment demonstration was completed using regulatory AQM predictions and measurements from the Houston ground-monitoring network. Results show that the model predictions used for the RRF calculation were often based on model conditions that were geographically remote from observations and counter to wind flow. Many of the monitors used the same model predictions for an RRF, even if that O3 plume did not impact it. The RRF methodology resulted in severing the true source-receptor relationship for a monitor. This analysis also showed that model performance could influence RRF values, and values at monitoring sites appear to be sensitive to model bias. Results indicate an inverse linear correlation of RRFs with model bias at each monitor (R2 = 0.47), resulting in a change in future O3 design values up to 5 parts per billion (ppb). These results suggest that the application of RRF methodology in Houston, TX, should be changed from using all model predictions above 85 ppb to a method that removes any predictions that are not relevant to the observed source-receptor relationship.