Analysis of temporal and spatial dichotomous PM air samples in the El Paso-Cd. Juarez air quality basin

Associations between Dust Exposure and Hospitalizations in El Paso, Texas, USA

The Southwestern USA has been identified as one of the most persistent dust-producing regions of North America, where exposure to inhalable particulate matter (PM10) originating from desertic landscape during dust events/dust exposures (DEs) can reach hazardous levels. El Paso, Texas’s ambient air has reached hazardous levels of PM10 from dust with near zero visibility due to these natural events originating in the surrounding Chihuahuan Desert. The aim of this study was to investigate whether dust exposures in El Paso (generally acute, short-term exposures from nearby source areas) are associated with significant increases in hospitalizations on the day of the exposure and up to seven days afterwards. Using a Poisson regression, it was found that the relative risks of hospitalizations due to a variety of conditions were associated with dust exposures (through increases of 100 μg/m3 maximum hourly PM10 and/or increases of 4.5 m/s maximum hourly wind speed) in El Paso County, Texas between 2010 and 2014. Valley fever, coronary atherosclerosis, genitourinary diseases, neurodegenerative diseases, injury and poisoning, circulatory system conditions, respiratory system diseases, births, septicemia, Associated Diseases (the aggregation of hospital admissions for all causes, each associated with at least 5% of hospitalizations), and all ICD-9 admissions were significantly positively associated with dust exposures, indicated from higher to lower significant risk, at different lag periods after exposure. These findings, showing that an association does exist between dust exposures and hospitalizations, have important implications for residents of the world’s dryland cities.

Assessment of mobile source contributions in El Paso by PMF receptor modeling coupled with wind direction analysis

It is well-known that El Paso is the only border area in Texas that has violated national air quality standards. Mobile source emissions (including vehicle exhaust) contribute significantly to air pollution, along with other sources including industrial, residential, and cross-border. This study aims at separating unobserved vehicle emissions from air-pollution mixtures indicated by ambient air quality data. The level of contributions from vehicle emissions to air pollution cannot be determined by simply comparing ambient air quality data with traffic levels because of the various other contributors to overall air pollution. To estimate contributions from vehicle emissions, researchers employed advanced multivariate receptor modeling called positive matrix factorization (PMF) to analyze hydrocarbon data consisting of hourly concentrations measured from the Chamizal air pollution monitoring station in El Paso. The analysis of hydrocarbon data collected at the Chamizal site in 2008 showed that approximately 25% of measured Total Non-Methane Hydrocarbons (TNMHC) was apportioned to motor vehicle exhaust. Using wind direction analysis, researchers also showed that the motor vehicle exhaust contributions to hydrocarbons were significantly higher when winds blow from the south (Mexico) than those when winds blow from other directions. The results from this research can be used to improve understanding source apportionment of pollutants measured in El Paso and can also potentially inform transportation planning strategies aimed at reducing emissions across the region.

Understanding Potential Exposure of Bicyclists on Roadways to Traffic-Related Air Pollution: Findings from El Paso, Texas, Using Strava Metro Data

As bicycling on roadways can cause adverse health effects, there is an urgent need to understand how bicycle routes expose bicyclists to traffic emissions. Limited resources for monitoring reveal that bicycle travel patterns may constrain such understanding at the network level. This study examined the potential exposure of bicyclists to traffic-related air pollution in El Paso, Texas, using Strava Metro data that revealed bicycle patterns across the city networks. An initial spatial mapping analysis was conducted to explore the spatial patterns of bicycling and traffic pollutant emission, followed by exploratory descriptive statistics. A spatial bicycle model was then developed to explore factors influencing bicycling activity in El Paso. Analysis results indicated significant associations between greater bicycle volume and both higher levels of particulate matter (PM2.5) emissions and more frequent bus services, implying adverse health concerns related to traffic-related air pollution. The results also indicated significant effects of various environmental characteristics (e.g., roadway, bicycle infrastructure, topography, and demographics) on bicycling. The findings encourage extending this study to provide guidance to bicyclists whose regular trips take place on heavily trafficked roads and during rush hours in this region and to evaluate the net health impacts of on-road bicycling for the general population.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM_2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM_2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM_2.5 events that contributed to elevated seasonal PM_2.5 levels. Similarly, in spring, high PM_2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM_2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM_2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM_2.5.

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales, Sonora, Mexico

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States-Mexico border During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14-30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM3 concentrations in the range of 134 to 157 microg m(-3) and biomass stoves 163 to 504 microg m(-1). Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM3: 130 to 770 microg m(-3)). The former is evident in the median and range of daytime PM values (median PM3: 250 microg m(-3), maximum: 9411 microg m(-3)), while the meteorological influences appear to be dominant during nighttime periods (median PM3: 251 microg m(-3), maximum: 10,846 microg m(-3)). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 microg m(-3)). Implications: Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States-Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.

Air pollution and hospital emergency room and admissions for cardiovascular and respiratory diseases in Doña Ana County, New Mexico

INTRODUCTION

Doña Ana County in New Mexico regularly experiences severe air pollution episodes associated with windblown dust and fires. Residents of Hispanic/Latino origin constitute the largest population group in the region. We investigated the associations of ambient particulate matter and ozone with hospital emergency room and admissions for respiratory and cardiovascular visits in adults.

METHODS

We used trajectories regression analysis to determine the local and regional components of particle mass and ozone. We applied Poisson generalized models to analyze hospital emergency room visits and admissions adjusted for pollutant levels, humidity, temperature and temporal and seasonal effects.

RESULTS

We found that the sources within 500km of the study area accounted for most of particle mass and ozone concentrations. Sources in Southeast Texas, Baja California and Southwest US were the most important regional contributors. Increases of cardiovascular emergency room visits were estimated for PM10 (3.1% (95% CI: -0.5 to 6.8)) and PM10-2.5 (2.8% (95% CI: -0.2 to 5.9)) for all adults during the warm period (April-September). When high PM10 (>150μg/m(3)) mass concentrations were excluded, strong effects for respiratory emergency room visits for both PM10 (3.2% (95% CI: 0.5-6.0)) and PM2.5 (5.2% (95% CI: -0.5 to 11.3)) were computed.

CONCLUSIONS

Our analysis indicated effects of PM10, PM2.5 and O3 on emergency room visits during the April-September period in a region impacted by windblown dust and wildfires.

Associations between urban air pollution and pediatric asthma control in El Paso, Texas

Exposure to traffic-related pollutants poses a serious health threat to residents of major urban centers around the world. In El Paso, Texas, this problem is exacerbated by the region's arid weather, frequent temperature inversions, heavy border traffic, and an aged, poorly maintained vehicle fleet. The impact of exposure to traffic pollution, particularly on children with asthma, is poorly understood. Tracking the environmental health burden related to traffic pollution in El Paso is difficult, especially within school microenvironments, because of the lack of sensitive environmental health indicator data. The Asthma Control Questionnaire (ACQ) is a survey tool for the measurement of overall asthma control, yet has not previously been considered as an outcome in air pollution health effect research. We conducted a repeated measure panel study to examine weekly associations between ACQ scores and traffic- and non-traffic air pollutants among asthmatic schoolchildren in El Paso. In the main one- and two-pollutant epidemiologic models, we found non-significant, albeit suggestive, positive associations between ACQ scores and respirable particulate matter (PM10), coarse particulate matter (PM10-2.5), fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), benzene, toluene, and ozone (O3). Notably, associations were stronger and significant for some subgroups, in particular among subjects taking daily inhaled corticosteroids. This pattern may indicate heightened immune system response in more severe asthmatics, those with worse asthma "control" and higher ACQ scores at baseline. If the ACQ is appropriately used in the context of air pollution studies, it could reflect clinically measurable and biologically relevant changes in lung function and asthma symptoms that result from poor air quality and may increase our understanding of how air pollution influences asthma exacerbation.

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.

Air pollution and acute respiratory response in a panel of asthmatic children along the U.S.-Mexico border

BACKGROUND

Concerns regarding the health impact of urban air pollution on asthmatic children are pronounced along the U.S.-Mexico border because of rapid population growth near busy border highways and roads.

OBJECTIVES

We conducted the first binational study of the impacts of air pollution on asthmatic children in Ciudad Juarez, Mexico, and El Paso, Texas, USA, and compared different exposure metrics to assess acute respiratory response.

METHODS

We recruited 58 asthmatic children from two schools in Ciudad Juarez and two schools in El Paso. A marker of airway inflammation [exhaled nitric oxide (eNO)], respiratory symptom surveys, and pollutant measurements (indoor and outdoor 48-hr size-fractionated particulate matter, 48-hr black carbon, and 96-hr nitrogen dioxide) were collected at each school for 16 weeks. We examined associations between the pollutants and respiratory response using generalized linear mixed models.

RESULTS

We observed small but consistent associations between eNO and numerous pollutant metrics, with estimated increases in eNO ranging from 1% to 3% per interquartile range increase in pollutant concentrations. Effect estimates from models using school-based concentrations were generally stronger than corresponding estimates based on concentrations from ambient air monitors. Both traffic-related and non-traffic-related particles were typically more robust predictors of eNO than was nitrogen dioxide, for which associations were highly sensitive to model specification. Associations differed significantly across the four school-based cohorts, consistent with heterogeneity in pollutant concentrations and cohort characteristics. Models examining respiratory symptoms were consistent with the null.

CONCLUSIONS

The results indicate adverse effects of air pollution on the subclinical respiratory health of asthmatic children in this region and provide preliminary support for the use of air pollution monitors close to schools to track exposure and potential health risk in this population.

Hospital admissions for asthma and acute bronchitis in El Paso, Texas: do age, sex, and insurance status modify the effects of dust and low wind events?

BACKGROUND

El Paso County (Texas) is prone to still air inversions and is one of the dust "hot spots" in North America. In this context, we examined the sub-lethal effects of airborne dust and low wind events on human respiratory health (i.e., asthma and acute bronchitis) between 2000 and 2003, when 110 dust and 157 low wind events occurred. Because environmental conditions may not affect everyone the same, we explored the effects of dust and low wind within three age groups (children, adults, and the elderly), testing for effect modifications by sex and insurance status, while controlling for weather and air pollutants.

METHODS

We used a case-crossover design using events matched with referent days on the same day-of-the-week, month, and year with conditional logistic regression to estimate the probability of hospital admission, while controlling for apparent temperature (lag 1), nitrogen dioxide, and particulate matter of 2.5μm or less.

RESULTS

Children (aged 1-17) were 1.19 (95% confidence interval: 1.00-1.41) times more likely to be hospitalized for asthma three days after a low wind event, and 1.33 (95% CI: 1.01-1.75) times more likely to be hospitalized for acute bronchitis one day after a dust event than on a clear day. Girls were more sensitive to acute bronchitis hospitalizations after dust events (1.83, 95% CI: 1.09-3.08) than boys, but less sensitive than boys to acute bronchitis hospitalizations after low wind events (0.68, 95% CI: 0.46-1.00). We found general trends with regard to dust and low wind events being associated with increased odds of hospitalization for asthma and bronchitis amongst all ages and adults (aged 18-64). Adults covered by Medicaid and adults without health insurance had higher risks of hospitalization for asthma and acute bronchitis after both low wind and dust events.

CONCLUSIONS

Results suggest that there were respiratory health effects associated with dust and low wind events in El Paso, with stronger impacts among children and poor adults. Girls and boys with acute bronchitis were differentially sensitive to dust and low wind events.

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO(2)) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO(2) appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children's exposures to these pollutants vary based on the location of their school.

Contributors to ozone episodes in three US/Mexico border twin-cities

The Process Analysis tools of the Community Multiscale Air Quality (CMAQ) modeling system together with back-trajectory analysis were used to assess potential contributors to ozone episodes that occurred during June 1-4, 2006, in three populated U.S.-Mexico border twin cities: San Diego/Tijuana, Imperial/Mexicali and El Paso/Ciudad Juárez. Validation of CMAQ output against surface ozone measurements indicates that the predictions are acceptable with regard to commonly recommended statistical standards and comparable to other reported studies. The mean normalized bias test (MNBT) and mean normalized gross error (MNGE) for hourly ozone fall well within the US EPA suggested range of +/-15% and 35%, respectively, except MNBT for El Paso. The MNBTs for maximum 8-h average ozone are larger than those for hourly ozone, but all the simulated maximum 8-h average ozone are within a factor of 2 of those measured in all three regions. The process and back-trajectory analyses indicate that the main sources of daytime ground-level ozone are the local photochemical production and regional transport. By integrating the effects of each process over the depth of the daytime planetary boundary layer (PBL), it is found that in the San Diego area (SD), chemistry and vertical advection contributed about 36%/48% and 64%/52% for June 2 and 3, respectively. This confirms the previous finding that high-altitude regional transport followed by fumigation contributes significantly to ozone in SD. The back-trajectory analysis shows that this ozone was mostly transported from the coastal area of southern California. For the episodes in Imperial Valley and El Paso, respectively, ozone was transported from the coastal areas of southern California and Mexico and from northern Texas and Oklahoma.

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.

The effects of 3 environmental risks on mortality disparities across Mexican communities

The disparities in the burden of ill health caused by environmental risks should be an important consideration beyond their aggregate population effects. We used comparative risk assessment methods to calculate the mortality effects of unsafe water and sanitation, indoor air pollution from household solid fuel use, and ambient urban particulate matter pollution in Mexico. We also estimated the disparities in mortality caused by each risk factor, across municipios (counties) of residence and by municipio socioeconomic status (SES). Data sources for the analysis were the national census, population-representative health surveys, and air quality monitoring for risk factor exposure; systematic reviews and meta-analyses of epidemiological studies for risk factor effects; and vital statistics for disease-specific mortality. During 2001-2005, unsafe water and sanitation, household solid fuel use, and urban particulate matter pollution were responsible for 3,000, 3,600, and 7,600 annual deaths, respectively. Annual child mortality rates would decrease by 0.2, 0.1, and 0.1 per 1,000 children, and life expectancy would increase by 1.0, 1.2, and 2.4 months, respectively, in the absence of these environmental exposures. Together, these risk factors caused 10.6% of child deaths in the lowest-SES communities (0.9 deaths per 1,000 children), but only 4.0% in communities in the highest-SES ones (0.1 per 1,000). In the 50 most-affected municipios, these 3 exposures were responsible for 3.2 deaths per 1,000 children and a 10-month loss of life expectancy. The large disparities in the mortality effects of these 3 environmental risks should form the basis of interventions and environmental monitoring programs.

Determination of PM2.5 sources using time-resolved integrated source and receptor models

Multivariate statistical techniques are applied to particulate matter (PM) and meteorological data to identify the sources responsible for evening PM spikes at Sunland Park, NM (USA). The statistical techniques applied are principal components analysis (PCA), redundancy analysis (RDA), and absolute principal components scores analysis (APCSA), and the data evaluated are 3-h average (6-9 p.m.) PM(2.5) mass and chemical composition and 1-h average PM(2.5) and PM(10) mass and environmental data collected in the winter of 2002. Although the interpretation of the data was complicated by the presence of sources which are likely changing in time (e.g. brick kilns), the multivariate analyses indicate that the evening high PM(2.5) is associated with burning-activities occurring to the south of Sunland Park, and these emissions are characterized by elevated Sb, Cl(-), and elemental carbon; approximately 68% of the PM(2.5) mass can be attributed to this source. The PM(10) evening peaks, on the other hand, are mainly caused by resuspended dust generated by vehicular movements south of the site and transported by the local terrain-induced drainage flow.

Atmospheric concentrations of PM2.5 trace elements in the Seoul urban area of South Korea

Fine particles (PM2.5) were collected during all four seasons, from April 2001 to February 2002, in Seoul, South Korea, using an annular denuder system. Elemental compositions of ambient PM2.5 were analyzed using the proton-induced X-ray emission method. The greatest contributors (> or = 2%) to the PM2.5 mass were sulfur (S), silicon (Si), chlorine (Cl), aluminum (Al), and iron (Fe) in the spring; S in the summer; and S and Cl in the fall. S, Cl, and Si were the major elements in the winter. S was the most abundant species among the elements, ranging from 5.3 to 7.9%, followed by Si and Cl. From analysis of variance, PM2.5 mass, Al, Si, potassium, calcium, and Fe showed significant seasonal differences during the four seasons (p < 0.001). Enrichment factor (EF) analysis was carried out to identify the sources affecting the aerosol in the Seoul area. On the basis of the mean EF values, elemental S, copper, zinc, and lead may be emitted from anthropogenic sources (EF > 50). Elemental Al, Si, titanium, and Fe may be emitted from crustal sources (EF < 3). Additionally, a correlation analysis was carried out for source identification. The results of the correlation analysis were confirmed by the results of the EF analysis.