Houston Galveston Research Articles

TRACER Perspectives on Gulf-Breeze and Bay-Breeze Circulations and Coastal Convection

Abstract This study explores gulf-breeze circulations (GBCs) and bay-breeze circulations (BBCs) in Houston–Galveston, investigating their characteristics, large-scale weather influences, and impacts on surface properties, boundary layer updrafts, and convective clouds. The results are derived from a combination of datasets, including satellite observations, ground-based measurements, and reanalysis datasets, using machine learning, changepoint detection method, and Lagrangian cell tracking. We find that anticyclonic synoptic patterns during the summer months (June–September) favor GBC/BBC formation and the associated convective cloud development, representing 74% of cases. The main Tracking Aerosol Convection Interactions Experiment (TRACER) site located close to the Galveston Bay is influenced by both GBC and BBC, with nearly half of the cases showing evident BBC features. The site experiences early frontal passages ranging from 1040 to 1630 local time (LT), with 1300 LT being the most frequent. These fronts are stronger than those observed at the ancillary site which is located further inland from the Galveston Bay, including larger changes in surface temperature, moisture, and wind speed. Furthermore, these fronts trigger boundary layer updrafts, likely promoting isolated convective precipitating cores that are short lived (average convective lifetime of 63 min) and slow moving (average propagation speed of 5 m s−1), primarily within 20–40 km from the coast.

Characterizing Overwater High Ozone Events in the Houston–Galveston–Brazoria Region during the 2021 GO3 and TRACER-AQ Campaigns

Abstract Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston–Galveston–Brazoria (HGB) region have not been previously verified using in situ observations. Such data were collected systematically, for the first time, from July to October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions Experiment—Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea-breeze recirculation and postfrontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.

A co-design method for including stakeholder perspectives in nature-based flood risk management

Intervention methods to establish commitment to (collaborative) action are of potential interest to researchers and policymakers intent upon including stakeholder perspectives in natural risk governance (Scolobig, Nat Hazards 81:27–43, 2016). In this paper, a 6-step co-design method for engaging with local people in collaboratively envisioning nature-based solutions for flood defence is described. The problem structuring base of the participatory method is extended to accommodate the multi-actor situation and the local context of flood risk management. The intervention method is applied in a workshop in the Houston–Galveston Bay area in October 2014. At that time there was strong contestation surrounding the proposed Ike Dike with alternative combinations of nature-based and smaller conventional engineering solutions being proposed. The results indicate that the local participants were able to envision a wide range of future outcomes for the bay and were able to use the insights on nature-based solutions and the social contacts that they acquired at the transdisciplinary workshop to mobilize commitment to joint action. This action focused on collaboration rather than specifying ecological or technical infrastructural requirements and was instrumental in initiating more open discourse on flood defence options for the Houston–Galveston Bay area. The paper concludes that the generic applicability of the co-design method is limited by the requirement to understand and accommodate local circumstances and participants’ insights within the workshop.

Exploring the Impact of Winter Storm Uri on Power Outage, Air Quality, and Water Systems in Texas, USA

Texas was hit by a record-setting cold snap from the 14–17 February 2021 after three decades that resulted in power outages, disruption of the public water systems, and other cascading effects. This study investigates the unprecedented impact of winter storm Uri on power outages, air quality, and water systems in Texas, USA. Analysis of the Parameter Regression of Independent Slopes Model (PRISM) gridded climate data showed that the average daily freezing temperature range was 0–−19 °C on 14 February 2021, with severe levels (−17–−19 °C) occurring in the Texas High Plains. Our results showed that the extreme freezing temperature persisted from 14–17 February 2021, significantly affecting power operation and reliability, and creating power outages across Texas. Uri impacted the public water systems and air quality on time scales ranging from a few minutes to several days, resulting in 322 boiling notices. The air quality index level exceeded the standard limit by 51.7%, 61.7%, 50.8%, and 60% in Dallas–Fort Worth, Houston–Galveston, Austin, and Lubbock regions. The level of the pollutants exceeded the EPA NAAQS standard allowable limits during winter storm Uri. In general, this study gives information on the government’s future preparedness, policies, communication, and response to storm impacts on vulnerable regions and communities.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

Use of Vehicle Telematics Data to Characterize Drayage Heavy-Duty Truck Idling

The goal of this study is to evaluate potential air-quality applications of global positioning system (GPS) data from trucks in the Houston–Galveston Area Council’s (H-GAC) Drayage Loan Program (DLP), along with data collection using portable activity measurement systems (PAMS). PAMS data were collected at 1 Hz frequency from 39 heavy-duty trucks. Of these, 31 were diesel-powered DLP participant trucks operating in the Houston area and the remainder were local CNG trucks. The DLP participant trucks were also being tracked by H-GAC via GPS. PAMS and GPS data were used for data analyses to provide insight into idling events, truck activity (vehicle miles traveled and speeds), and geospatial analysis of trip origins and destinations. Finally, the GPS and PAMS datasets for the DLP participant trucks were used to analyze differences between GPS and PAMS data for vehicle idling and activity. The data analyses were conducted using an integrated data analytics tool (Microsoft Power BI), which allowed for data integration, analysis, dashboarding, and mapping on a single platform. The study results show that 91% of DLP participant truck activities occur during the day, with low average speeds largely from extensive idling. The data analytics system developed in this study can be used to identify, implement, and measure performance of idling reduction strategies for a specific region and operation type. For example, the data can be used to investigate whether a battery–electric air conditioning system is effective for the operation of a target fleet.

Examining of the actor collaboration networks around hazard mitigation: a hurricane harvey study

The objective of this study is to examine the properties of actor collaboration networks and to analyze how they influence the coordination of hazard mitigation in resilience planning in Harris County, Texas. Effective resilience planning can only be achieved through the collective actions of various actors and the network structures unfold the collaboration among the actors. Understanding the structural properties of actor collaboration networks for hazard mitigation may hold the key to understanding and improving the resilience planning process. To this end, after Hurricane Harvey, we administered a stakeholder survey to actors in various urban sectors involved in hazard mitigation (e.g., flood control, transportation, and emergency response). The survey aimed to capture actor collaboration networks for hazard mitigation in Harris County, Texas prior to Harvey. The collaboration represents that the survey respondents worked with the actors in the survey roster for hazard mitigation. We asked the respondents the frequency of the collaboration in the survey (e.g., yearly, monthly, weekly and daily). We examined three network structural properties to study actor positions in the network: degree centrality, boundary spanners, and core-periphery structure, because degree centrality could indicate what actors had more collaborations; boundary spanners could reveal what actors were in strategic positions to connect otherwise separate actors; and core-periphery structure could identify what actors formed the core of actor collaboration network for hazard mitigation and whether the core was composed of actors from diverse sectors. The results showed: (1) governmental actors from different sectors had high degree centrality and betweenness centrality, which indicated that governmental actors had a more influential role in coordination and information dissemination in hazard mitigation planning and implementation; and (2) fewer flood control and non-governmental actors were at the core of the actor collaboration networks, which reduced the extent of hazard mitigation coordination. The results identify potential influential actors (such as City of Houston, Harris County, and Houston–Galveston Area Council) in coordination of hazard mitigation and yield recommendations for increased actor network cohesion for better coordination of hazard mitigation across diverse sectors in resilience planning.

HGBEnviroScreen: Enabling Community Action through Data Integration in the Houston-Galveston-Brazoria Region.

The Houston–Galveston–Brazoria (HGB) region faces numerous environmental and public health challenges from both natural disasters and industrial activity, but the historically disadvantaged communities most often impacted by such risks have limited ability to access and utilize big data for advocacy efforts. We developed HGBEnviroScreen to identify and prioritize regions of heightened vulnerability, in part to assist communities in understanding risk factors and developing environmental justice action plans. While similar in objectives to existing environmental justice tools, HGBEnviroScreen is unique in its ability to integrate and visualize national and local data to address regional concerns. For the 1090 census tracts in the HGB region, we accrued data into five domains: (i) social vulnerability, (ii) baseline health, (iii) environmental exposures and risks, (iv) environmental sources, and (v) flooding. We then integrated and visualized these data using the Toxicological Prioritization Index (ToxPi). We found that the highest vulnerability census tracts have multifactorial risk factors, with common drivers being flooding, social vulnerability, and proximity to environmental sources. Thus, HGBEnviroScreen is not only helping identify communities of greatest overall vulnerability but is also providing insights into which domains would most benefit from improved planning, policy, and action in order to reduce future vulnerability.

Estimating Evacuation Shelter Deficits in the Houston-Galveston Metropolitan Area.

Evacuation is frequently used by emergency managers and other officials as part of an overall approach to reducing the morbidity and mortality associated with hurricane landfall. In this study, the evacuation shelter capacity of the Houston-Galveston Metropolitan Statistical Area (MSA) was spatially assessed and shelter deficits in the region were estimated. These data provide essential information needed to eliminate shelter deficits and ensure a successful evacuation from a future storm. Spatial statistical methods-Global Moran's I, Anselin Local Moran's I (Local Indicators of Spatial Association [LISA]), and Hot Spot Analysis (Getis-Ord Gi*) were used to assess for regional spatial autocorrelation and clustering of evacuation shelters in the Houston-Galveston MSA. Shelter deficits were estimated in four ways-the aggregate deficit for the Houston-Galveston MSA, by evacuation Zip-Zone, by county, and by distance or radii of evacuation Zip-Zone. Evacuation shelters were disproportionately distributed in the region, with lower capacity shelters clustered closer to evacuation Zip-Zones (50 miles from the Coastal Zip-Zone), and higher capacity shelters clustered farther away from the zones (120 miles from the Coastal Zip-Zone). The aggregate shelter deficit for the Houston-Galveston MSA was 353,713 persons. To reduce morbidity and mortality associated with future hurricanes in the Houston-Galveston MSA, authorities should consider the development and implementation of policies that would improve the evacuation shelter capacity of the region. Eliminating shelter deficits, which has been done successfully in the state of Florida, is an essential element of protecting the public from hurricane impacts.

Uneven Neighborhood Recovery: Hurricane Damage and Neighborhood Change in the Houston–Galveston Region since 1970

Despite the growing number of natural disasters around the globe, limited research exists on post–disaster patterns of neighborhood change. In this paper, we test two theories of neighborhood change, the “recovery machine” and “rent gap,” which predict opposing effects for low socioeconomic status (SES) neighborhoods following damage from hurricanes, tropical storms, and other natural hazard events. The recovery machine theory posits that after natural hazard events, local communities experience patterns of recovery based on their pre–disaster SES and access to resources, suggesting that wealthier neighborhoods will recover robustly while lower status neighborhoods languish. In contrast, the rent gap theory suggests that developers will identify a profit opportunity in the depressed values created by damage from natural hazard events, and seek to redevelop low SES areas. We use fixed effects models with census data from 1970 to 2015 to test the impact of damage from natural hazards on neighborhood change. We find substantial recovery and change in low–income neighborhoods, but not in the high–income neighborhoods supporting the rent gap theory. We conclude that natural hazard events resulting in damage produce uneven recovery by socioeconomic status of neighborhoods, potentially leading to displacement of low SES groups.

Performance analysis of WRF and LES in describing the evolution and structure of the planetary boundary layer

We implemented the Weather Research and Forecast (WRF) model and WRF Large-Eddy Simulation (WRF–LES), focusing on calculations for the planetary boundary layer (PBL), and compared the results against a data set of a well-documented campaign, in the Houston–Galveston area, Texas, in summer 2006. A methodology using WRF in a mesoscale and LES was implemented to assess the performance of the model in simulating the evolution and structure of the PBL over Houston during the Vertical Mixing Experiment. Also, the WRF model in a real case mode was examined to explore potential differences between the results of each simulation approach. We analyzed both WRF results for key meteorological parameters like wind speed, wind direction and potential temperature, and compared the model results against the observations. The reasonably good agreement of LES results forced with observed surface fluxes provides confidence that LES describes turbulence quantities such as turbulent kinetic energy correctly and warrants further turbulence structure analysis. The LES results indicate a weak but noticeable nighttime turbulent kinetic energy which was produced by wind shear in Houston’s planetary boundary layer and which may likely be related to intermittent turbulence. This is supported by observations made at the University of Houston Moody Tower air quality station when intermittent peaks of carbon monoxide occurred in the evening, although the variability in wind conditions was very little.

INTEGRATED DESIGN FOR FLOOD RISK AND SPATIAL QUALITY—EXAMPLES FROM THE DUTCH DELTA PROGRAMME

INTRODUCTION The Netherlands faces a significant flood risk task. In order to remain a safe place to live the Netherlands has to upgrade its extensive flood risk protection system. This results in an elevation and reinforcement task for many of the Netherlands water barriers. When those barriers are positioned in an open landscape, the technical reinforcement is often easy to embed specially. However, many barriers have been built over the years making the reinforcement into a challenging spatial assignment. This article shows different case study examples of a research by design study (performed in the broader context of the Dutch Delta programme) that explores integral design solutions for flood risk and spatial (re)development. The Houston Galveston Bay case study demonstrates the international applicability of the research by design method.

A data mining framework for environmental and geo-spatial data analysis

Mining geo-spatial data is an important task in many application domains, such as environmental science, geographic information science, and social networks. In this paper, we introduce a data mining framework, which includes pre-processing of environmental and geo-spatial data, geo-spatial data mining techniques, and visual analysis of environmental and geo-spatial data. In particular, we propose new density-based clustering algorithms to identify interesting distribution patterns from geo-spatial data, a change pattern discovery technique to detect dynamic change patterns within spatial clusters, and a post-processing technique to extract interesting patterns and useful knowledge from geo-spatial data. Our density-based clustering algorithms are based on the well-established density-based shared nearest neighbor clustering algorithm, which can find clusters of different shape, size, and densities in high-dimensional data. The post-processing analysis technique allows automatic screening of interesting spatial clusters. The change pattern discovery algorithm is able to detect and analyze dynamic patterns of changes within spatial clusters. This paper focuses on developing a framework integrating a sequence of data mining process including clustering algorithm, analysis technique and pattern changing discovery algorithm. In contrast to previous works in this area, our approaches can cluster and analyze dynamically evolved complex objects, i.e., polygons. We evaluate the effectiveness of our techniques through a challenging real case study involving ozone pollution events in the Houston–Galveston–Brazoria area. The experimental results show that our approaches can discover interesting patterns and useful information from geo-spatial air-quality data.

Regional background O<sub>3</sub> and NO<sub><i>x</i></sub> in the Houston–Galveston–Brazoria (TX) region: a decadal-scale perspective

Abstract. Ozone (O3) in the lower troposphere is harmful to people and plants, particularly during summer, when photochemistry is most active and higher temperatures favor local chemistry. Local precursor emissions, such as those of volatile organic compounds (VOCs) and nitrogen oxides (NOx), together with their chemistry contribute to the O3 and NOx mixing ratios in the Houston–Galveston–Brazoria (HGB) region. In addition to local emissions, chemistry and transport, larger-scale factors also contribute to local O3 and NOx. These additional contributions (often referred to as regional background) are not well quantified within the HGB region, impeding more efficient controls on precursor emissions to achieve compliance with the National Ambient Air Quality Standards for O3. In this study, we estimate ground-level regional background O3 and NOx in the HGB region and quantify their decadal-scale trends.We use four different approaches based on principal component analysis (PCA) to quantify background O3 and NOx. Three of these approaches consist of independent PCA on both O3 and NOx for both 1 and 8 h levels to compare our results with previous studies and to highlight the effect of both temporal and spatial scales. In the fourth approach, we co-varied O3, NOx and meteorology.Our results show that the estimation of regional background O3 has less inherent uncertainty when it was constrained by NOx and meteorology, yielding a statistically significant temporal trend of −0.68 ± 0.27 ppb yr−1. Likewise, the estimation of regional background NOx trend constrained by O3 and meteorology was −0.04 ± 0.02 ppb yr−1 (upper bound) and −0.03 ± 0.01 ppb yr−1 (lower bound). Our best estimates of the 17-year average of season-scale background O3 and NOx were 46.72 ± 2.08 ppb and 6.80 ± 0.13 ppb (upper bound) or 4.45 ± 0.08 ppb (lower bound), respectively. Average background O3 is consistent with previous studies and between the approaches used in this study, although the approaches based on 8 h averages likely overestimate background O3 compared to the hourly median approach by 7–9 ppb. Similarly, the upper bound of average background NOx is consistent between approaches in this study (A–C) but overestimated compared to the hourly approach by 1 ppb, on average. We likely overestimate the upper-bound background NOx due to instrument overdetection of NOx and the 8 h averaging of NOx and meteorology coinciding with MDA8 O3.Regional background O3 and NOx in the HGB region both have declined over the past 2 decades. This decline became steadier after 2007, overlapping with the effects of controlling precursor emissions and a prevailing southeasterly–southerly flow.

Influence of the Bermuda High on interannual variability of summertime ozone in the Houston–Galveston–Brazoria region

Abstract. The Bermuda High (BH) quasi-permanent pressure system is the key large-scale circulation pattern influencing summertime weather over the eastern and southern US. Here we developed a multiple linear regression (MLR) model to characterize the effect of the BH on year-to-year changes in monthly-mean maximum daily 8 h average (MDA8) ozone in the Houston–Galveston–Brazoria (HGB) metropolitan region during June, July, and August (JJA). The BH indicators include the longitude of the BH western edge (BH-Lon) and the BH intensity index (BHI) defined as the pressure gradient along its western edge. Both BH-Lon and BHI are selected by MLR as significant predictors (p < 0.05) of the interannual (1990–2015) variability of the HGB-mean ozone throughout JJA, while local-scale meridional wind speed is selected as an additional predictor for August only. Local-scale temperature and zonal wind speed are not identified as important factors for any summer month. The best-fit MLR model can explain 61–72 % of the interannual variability of the HGB-mean summertime ozone over 1990–2015 and shows good performance in cross-validation (R2 higher than 0.48). The BH-Lon is the most important factor, which alone explains 38–48 % of such variability. The location and strength of the Bermuda High appears to control whether or not low-ozone maritime air from the Gulf of Mexico can enter southeastern Texas and affect air quality. This mechanism also applies to other coastal urban regions along the Gulf Coast (e.g., New Orleans, LA, Mobile, AL, and Pensacola, FL), suggesting that the BH circulation pattern can affect surface ozone variability through a large portion of the Gulf Coast.

Characterizing the hydraulic interactions of hurricane storm surge and rainfall–runoff for the Houston–Galveston region

Planning of traditional coastal flood risk management strategies are largely predicated on storm surge protection against extreme hurricanes, i.e. storm surge. However, (1) hurricane storm surge and (2) hurricane rainfall–runoff are not mutually exclusive flood hazards. Little research has emphasized the need for quantifying and characterizing the joint hydraulic processes between hurricane storm surge and rainfall–runoff during real events for enhancing effective flood risk mitigation. In this regard, an improved hydrological and hydrodynamic modeling framework has been developed for the Houston Ship Channel (HSC) and Galveston Bay to serve as a quantitative testbed for evaluating coupled hurricane storm surge and rainfall–runoff. Modularity within the modeling framework allows for landfall shifting of historical hurricane tracks, wind fields, and corresponding rainfall patterns to serve as numerical model inputs, as well as providing an expanded dataset of storm events. Distributed hydrologic and unsteady hydraulic analyses of upstream rainfall–runoff and storm surge are conducted for hurricanes Katrina (2005), Ike (2008), and Isaac (2012) under three synthetically shifted landfall locations near the HSC and Galveston Bay regions. For the modeled scenarios, results show that peak flows from storm surge easily dominate those of rainfall–runoff, but that rainfall–runoff can constitute more than half of the total flood volume draining towards the HSC. Most modeled scenarios reveal less than 24h of separation between peak surge and peak rainfall–runoff. In the same way that storm surge is sensitive to hurricane landfall location and angle of approach, so are spatial rainfall distributions and associated inland runoff processes, due to wide topological variations in coastal watershed boundaries. Analysis of coastal flood mitigation is extended with the dynamic modeling of a proposed storm surge barrier system at the HSC, with its performance quantified under the given hurricanes. The surge barrier system is demonstrated to be hydraulically feasible for all scenarios, with maximum water surface elevation reductions ranging between 0.63m and 3.28m. However, accurate storm surge and riverine flood forecasting methods will be critical for achieving optimal gate and barrier operations.

Mapping ground deformation over Houston–Galveston, Texas using multi-temporal InSAR

Abstract Houston–Galveston (HG) region in Texas has been subsiding due to the combined effects of groundwater withdrawal, hydrocarbon extraction, salt dome movement, and faulting. This human- and partially nature-induced ground deformation has gradually threatened the stability of urban infrastructure and caused the loss of wetland habitat along the Gulf of Mexico. Interferometric synthetic aperture radar (InSAR) techniques can measure ground motions in high spatial resolution over large coverage. The purpose of this study is to map the spatial and temporal variations in surface deformation around the HG region using a Multi-Temporal InSAR (MTI) technique and to assess the role of fluid withdrawal (groundwater withdrawal and hydrocarbon extraction), salt tectonics, and fault activity in land surface deformation. MTI-derived land surface deformation measurements are then compared to GPS and extensometer observations, geologic and hydrologic data, and information about hydrocarbon extraction to address the causes of the observed deformation. The MTI measurements based on ERS-1/2 datasets have mapped regional subsidence up to 53 mm/yr in the northwestern HG as well as a slight uplift at 20 mm/yr in the southeastern HG from 1993 to 2000. InSAR measurements obtained from Envisat and ALOS data reveal subsidence rate of up to 30 mm/yr over the northwestern HG between 2004 and 2011. Our results indicate that the pattern of ground deformation was nearly concentric around locations of intense groundwater withdrawal and the spatial extent of the subsiding area has been shrinking and migrating toward the northeast after 2000. We have resolved localized ground subsidence cones over hydrocarbon exploration fields, which were likely caused by reservoir compaction. We have differentiated ground surface deformation over salt domes, which was due to ongoing differential movement of individual salt spines. We have identified 5–40 mm/yr differential subsidence across a number of faults in the region. These faults functioned as water barriers disrupting the integrity of ground water flow and aggravating localized surface displacements.

Photochemical model simulations of air quality for Houston–Galveston–Brazoria area and analysis of ozone–NO x –hydrocarbon sensitivity

As part of the State Implementation Plan for the Houston–Galveston–Brazoria (HGB) area which has been declared as a non-attainment area, it was required to assess the impacts of pollutant emissions, meteorological conditions, and initial and boundary conditions on air quality. In this study, photochemical model simulations using the Comprehensive Air Quality Model with extensions (CAMx) were conducted for three ozone episodes between May and October of 2006. The CAMx simulations compared fairly well with the hourly average concentrations of ozone measured at the monitoring sites, and the index of agreement (IOA) values for all the three ozone episodes were found greater than 0.65, which proved to be good for CAMx model performance. Both simulated and observed peak ozone concentrations were observed to occur between 12:00 and 15:00 h. The CAMx simulation results showed that there were 68 days where the maximum 8-h mean ozone concentrations exceeded the NAAQS of 75 ppb out of a total of 72 days simulated in the three ozone episodes. For all three episodes, ozone concentrations were highest during the third quarter of the day. The photochemical indicator ratios of hydrogen peroxide (H2O2) to nitric acid (HNO3) ([H2O2]/[HNO3]) showed the HGB area to be a nitrogen oxide (NO x )-sensitive regime for the episodes studied. This indicated that volatile organic compounds (VOCs) are plentiful, and NO x is the limiting precursor for ozone formation in the HGB area. The plentiful VOCs in this region are possibly produced from industries and refineries in the HGB area.

Prediction of surface ozone episodes using clusters based generalized linear mixed effects models in Houston–Galveston–Brazoria area, Texas

A two–stage strategy is proposed to predict regional peak ozone episodes in the Houston–Galveston–Brazoria (HGB) area of Texas, USA. With the forecasted meteorological information, ozone episodes can be predicted one day in advance. Three generalized linear mixed effects models (GLMMs) are built with air quality and meteorological data monitored at CAMS35, CAMS403 and CAMS1015; wind field data from 8 monitoring sites in HGB area are used to generate clusters which represent distinct weather patterns. Air quality and meteorological data during ozone seasons (Apr. 1st – Oct. 31st) from 2003 to 2005 are used to build site–specific prediction models. Data of ozone season from 2006 to 2007 are used to test these models. Compared to linear regression models (LM), generalized linear models (GLMs), multilayer perceptron (MLP) and support vector machine (SVM), GLMM which considers differences in ozone formation and diffusion in distinct weather patterns has the smallest fitting and prediction error on ozone exceedances and can detect the most number of exceedance days correctly.

Economic Assessment of Access Management Projects in the Houston, Texas, Region

The goal of the access management study of the Houston–Galveston Area Council in Texas, was to examine the effects of recommended improvements before, during, and after project implementation in three areas: operations (traffic flow, intersection delay, and corridor delay), safety (crash frequency, crash rates, and comparisons with state averages), and economic (comparison of taxable sales receipts and control for other economic factors occurring during those times). This paper focuses on an economic assessment that was not addressed by previous studies and on local concerns about the economic impacts of access management. This economic evaluation methodology focused on collection and analysis of taxable sales data to examine possible changes in business activity before, during, and after any implemented access management improvements for various classes of businesses in the corridor study areas. Three corridors, consisting of principal arterials in a large urban area with retail and residential development, were studied. The trends from the three corridors studied suggested that business sales increased at a greater rate along these corridors than in the adjacent control zip code analysis zone. The data showed that overall economic activity in the three corridors was not negatively affected by the implementation of access management. Although confounding factors (Hurricanes Rita and Ike and the economic recession of 2007 to 2009) were in play in an examination of economic impacts during these types of projects, the results of this evaluation indicated that corridor economic activity typically remained steady, and in many cases, increased after access management projects were implemented.