Evan Couzo

Relationship between boundary layer heights and growth rates with ground‐level ozone in Houston, Texas

Measurements and predictions of ambient ozone (O3), planetary boundary layer (PBL) height, the surface energy budget, wind speed, and other meteorological parameters were made near downtown Houston, Texas, and were used to investigate meteorological controls on elevated levels of ground-level O3. Days during the study period (1 April 2009 to 31 December 2010 for measurements and 15 April 2009 to 17 October 2009 for modeled) were classified into low (LO3) and high ozone (HO3) days. The majority of observed high HO3 days occurred in a postfrontal environment. Observations showed there is not a significant difference in daily maximum PBL heights on HO3 and LO3 days. Modeling results showed large differences between maximum PBL heights on HO3 and LO3 days. Nighttime and early morning observed and modeled PBL heights are consistently lower on HO3 days than on LO3 days. The observed spring LO3 days had the most rapid early morning PBL growth (~350 m h−1) while the fall HO3 group had the slowest (~200 m h−1). The predicted maximum average hourly morning PBL growth rates were greater on HO3 (624 m h−1) days than LO3 days (361 m h−1). Observed turbulent mixing parameters were up to 2–3 times weaker on HO3 days, which indicate large-scale subsidence associated with high-pressure systems (leading to clear skies and weak winds) substantially suppresses mixing. Lower surface layer ventilation coefficients were present in the morning on HO3 days in the spring and fall, which promotes the accumulation of O3 precursors near the surface.

Issues with Ozone Attainment Methodology for Houston, TX

ABSTRACT 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 Agencys (EPA) guidance for demonstrating attainment. EPAs attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houstons 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. IMPLICATIONS Observational analysis in Houston provides compelling evidence that ozone design values at some surface monitors are dominantly influenced by large hourly changes in ozone concentration that are not predicted by the regulatory model. The use of these models, with current EPA attainment methodology, produces policies that likely overestimate precursor control requirements because only one cause of ozone is functioning in the model. This issue has significant regulatory and economic implications for Houston, especially under lower National Ambient Air Quality Standards. An attainment methodology that recognizes two unique causes for high ozone potentially offers a more reliable means for developing and justifying control policies.

Evaluation of Relative Response Factor Methodology for Demonstrating Attainment of Ozone in Houston, Texas

Abstract 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.

Houston’s rapid ozone increases: preconditions and geographic origins

Many of Houstons 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. 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.

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

ABSTRACT 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.