Hector A. Olvera

Temporal-spatial analysis of U.S.-Mexico border environmental fine and coarse PM air sample extract activity in human bronchial epithelial cells.

Particulate matter less than 10 microm (PM10) has been shown to be associated with aggravation of asthma and respiratory and cardiopulmonary morbidity. There is also great interest in the potential health effects of PM2.5. Particulate matter (PM) varies in composition both spatially and temporally depending on the source, location and seasonal condition. El Paso County which lies in the Paso del Norte airshed is a unique location to study ambient air pollution due to three major points: the geological land formation, the relatively large population and the various sources of PM. In this study, dichotomous filters were collected from various sites in El Paso County every 7 days for a period of 1 year. The sampling sites were both distant and near border crossings, which are near heavily populated areas with high traffic volume. Fine (PM2.5) and Coarse (PM10-2.5) PM filter samples were extracted using dichloromethane and were assessed for biologic activity and polycyclic aromatic (PAH) content. Three sets of marker genes human BEAS2B bronchial epithelial cells were utilized to assess the effects of airborne PAHs on biologic activities associated with specific biological pathways associated with airway diseases. These pathways included in inflammatory cytokine production (IL-6, IL-8), oxidative stress (HMOX-1, NQO-1, ALDH3A1, AKR1C1), and aryl hydrocarbon receptor (AhR)-dependent signaling (CYP1A1). Results demonstrated interesting temporal and spatial patterns of gene induction for all pathways, particularly those associated with oxidative stress, and significant differences in the PAHs detected in the PM10-2.5 and PM2.5 fractions. Temporally, the greatest effects on gene induction were observed in winter months, which appeared to correlate with inversions that are common in the air basin. Spatially, the greatest gene expression increases were seen in extracts collected from the central most areas of El Paso which are also closest to highways and border crossings.

Principal Component Analysis Optimization of a PM2.5 Land Use Regression Model with Small Monitoring Network

The use of land-use regression (LUR) techniques for modeling small-scale variations of intraurban air pollution has been increasing in the last decade. The most appealing feature of LUR techniques is the economical monitoring requirements. In this study, principal component analysis (PCA) was employed to optimize an LUR model for PM2.5. The PM2.5 monitoring network consisted of 13 sites, which constrained the regression model to a maximum of one independent variable. An optimized surrogate of vehicle emissions was produced by PCA and employed as the predictor variable in the model. The vehicle emissions surrogate consisted of a linear combination of several traffic variables (e.g., vehicle miles traveled, speed, traffic demand, road length, and time) obtained from a road network used for traffic modeling. The vehicle-emissions surrogate produced by the PCA had a predictive capacity greater (R2=.458) than the traffic variable, Traffic Demand summarized for a 1 km buffer, with best predictive capacity (R2=.341). The PCA-based method employed in this study was effective at increasing the fit of an ordinary LUR model by optimizing the utilization of a PM2.5 dataset from small-n monitoring network. In general, the method used can contribute to LUR techniques in two major ways: 1) by improving the predictive power of the input variable, by substituting a principal component for a single variable and 2) by creating an orthogonal set of predictor variables, and thus fulfilling the no colinearity assumption of the linear regression methods. The proposed PCA method, should be universally applicable to LUR methods and will expand their economical attractiveness.

Ultrafine particle levels at an international port of entry between the US and Mexico: Exposure implications for users, workers, and neighbors

Exposure to diesel-emitted particles has been linked to increased cancer risk and cardiopulmonary diseases. Because of their size (<100 nm), exposure to ultrafine particles (UFPs) emitted from heavy-duty diesel vehicles (HDDV) might result in greater health risks than those associated with larger particles. Seasonal UFP levels at the International Bridge of the Americas, which connects the US and Mexico and has high HDDV traffic demands, were characterized. Hourly average UFP concentrations ranged between 1.7 × 103/cc and 2.9 × 105/cc with a mean of 3.5 × 104/cc. Wind speeds <2 m s−1 and temperatures <15 °C were associated with particle number concentrations above normal conditions. The presence of HDDV had the strongest impact on local UFP levels. Varying particle size distributions were associated with south- and northbound HDDV traffic. Peak exposure occurred on weekday afternoons. Although in winter, high exposure episodes were also observed in the morning. Particle number concentrations were estimated to reach background levels at 400 m away from traffic. The populations exposed to UFP above background levels include law enforcement officers, street vendors, private commuters, and commercial vehicle drivers as well as neighbors on both sides of the border, including a church and several schools.

The effect of ventilation, age, and asthmatic condition on ultrafine particle deposition in children.

Ultrafine particles (UFPs) contribute to health risks associated with air pollution, especially respiratory disease in children. Nonetheless, experimental data on UFP deposition in asthmatic children has been minimal. In this study, the effect of ventilation, developing respiratory physiology, and asthmatic condition on the deposition efficiency of ultrafine particles in children was explored. Deposited fractions of UFP (10–200 nm) were determined in 9 asthmatic children, 8 nonasthmatic children, and 5 nonasthmatic adults. Deposition efficiencies in adults served as reference of fully developed respiratory physiologies. A validated deposition model was employed as an auxiliary tool to assess the independent effect of varying ventilation on deposition. Asthmatic conditions were confirmed via pre-and post-bronchodilator spirometry. Subjects were exposed to a hygroscopic aerosol with number geometric mean diameter of 27–31 nm, geometric standard deviation of 1.8–2.0, and concentration of 1.2 × 106 particles cm−3. Exposure was through a silicone mouthpiece. Total deposited fraction (TDF) and normalized deposition rate were 50% and 32% higher in children than in adults. Accounting for tidal volume and age variation, TDF was 21% higher in asthmatic than in non-asthmatic children. The higher health risks of air pollution exposure observed in children and asthmatics might be augmented by their susceptibility to higher dosages of UFP.

Evaluation of land use regression models for NO2 in El Paso, Texas, USA

Developing suitable exposure estimates for air pollution health studies is problematic due to spatial and temporal variation in concentrations and often limited monitoring data. Though land use regression models (LURs) are often used for this purpose, their applicability to later periods of time, larger geographic areas, and seasonal variation is largely untested. We evaluate a series of mixed model LURs to describe the spatial-temporal gradients of NO(2) across El Paso County, Texas based on measurements collected during cool and warm seasons in 2006-2007 (2006-7). We also evaluated performance of a general additive model (GAM) developed for central El Paso in 1999 to assess spatial gradients across the County in 2006-7. Five LURs were developed iteratively from the study data and their predictions were averaged to provide robust nitrogen dioxide (NO(2)) concentration gradients across the county. Despite differences in sampling time frame, model covariates and model estimation methods, predicted NO(2) concentration gradients were similar in the current study as compared to the 1999 study. Through a comprehensive LUR modeling campaign, it was shown that the nature of the most influential predictive variables remained the same for El Paso between 1999 and 2006-7. The similar LUR results obtained here demonstrate that, at least for El Paso, LURs developed from prior years may still be applicable to assess exposure conditions in subsequent years and in different seasons when seasonal variation is taken into consideration.

Health, Hope, and Human Development: Building Capacity in Public Housing Communities on the U.S.-Mexico Border

Summary: In this paper we highlight results from our recent survey of public housing residents living in the U.S.-Mexico border region. Our data inform our interdisciplinary (public health, education, environmental engineering, sociology) efforts to improve health and educational equity in our community, and provide ripe opportunities for policy advocacy.

In-Cab Air Quality of Trucks Air Conditioned and Kept in Electrified Truck Stop

At night, long-haul truck drivers rest inside the cabins of their vehicles. Therefore, the in-cab air quality while air conditioning (A/C) is being provided can be a great concern to the drivers’ health. The effect of using different A/C methods [trucks A/C, auxiliary power unit (APU), and truck stop electrification (TSE) unit] on in-cab air quality of a heavy-duty diesel vehicle was investigated at an electrified truck stop in the El Paso, Texas, area. The research team measured the in-cabin and the ambient air quality adjacent to the parked diesel truck as well as emissions from the truck and an APU while it was providing A/C. The measured results were compared and analyzed. On the basis of these results, it was concluded that the TSE unit provided better in-cab air quality while supplying A/C. Furthermore, the truck and APU exhaust emissions were measured, and fuel consumption of the truck (while idling) and the APU (during operation) were compared. The results led to the finding that emissions from the APU were less than those from the trucks engine idling, but the APU consumed more fuel than the engine while providing A/C under given conditions.

The Relationship of Childhood Adversity on Burnout and Depression Among BSN Students

Background: Research evidence strongly suggests that Adverse Childhood Experiences (ACEs) predispose individuals to development of an increased sensitivity to stress and negative physical and mental health outcomes in adulthood. Purpose: To determine if there was a relationship between the number of ACEs reported by first semester BSN students and their reported level of Burnout and Depression. Methods: 211 students enrolled in the first semester of upper division courses of their BSN program completed self‐report questionnaires which measured the number of ACEs, the level of Depression and the level of Burnout. Results: The number of reported ACEs by participants had a significant relationship on the levels of burnout and severity of depressive symptoms. Female students with a higher number of ACEs were more likely to report higher levels of Burnout A (Emotional Exhaustion) and Burnout B (Depersonalization), and higher depression severity scores compared to males. Conclusion: Nursing programs should educate faculty concerning the frequency and range of adverse experiences that students may have had prior to admission to the nursing program, and the possible relationship with Burnout and Depression. Faculty can provide early information on counseling and support services.