Selected air quality trends and recent air pollution investigations in the US-Mexico border region

Carcinogenic air pollution along the United States' southern border: Neighborhood inequities in risk

Air pollution poses serious and socially inequitable risks to public health. Social disparities are marked along the US-Mexico border, yet prior research has not assessed inequities in air pollution exposure across the entire US-side of the border region. We apply an intersectional approach to examine contextually relevant sociodemographic variables, including (1) Hispanic/Latinx ethnicity by race and (2) nativity (US vs. Foreign) by citizenship, and cancer risks attributable to air pollution exposures. We pair data from the 2012-2016 American Community Survey with 2014 National Air Toxics Assessment estimates of carcinogenic risks from all sources of hazardous air pollutants at the census tract level (n = 1448) and use a series of generalized estimating equations to assess inequities in risk. Increased concentrations of renter-occupants, Hispanics, mid-to-high socioeconomic status households, and foreign-born citizens were associated with elevated risks. Hispanic ethnicity intersected with non-White racial identification to amplify risks. In contrast, increased concentrations of non-Hispanic Black people and foreign-born non-citizens were not associated with disparate risks. To ameliorate environmental health inequities in this context, research and policy actions must be tailored to the US-Mexico border and consider intersectional positions within the Hispanic population.

Asthma prevalence and school-related hazardous air pollutants in the US-México border area

BACKGROUND

Asthma is the most common chronic disease in children and has been linked to high levels of ambient air pollution and certain hazardous air pollutants (HAPs). Outdoor pollutants such as benzene, released by car emissions, and organic chemicals found in diesel exhaust, as well as particles and irritant gases, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃), contribute to an increased prevalence of respiratory diseases such as asthma.

OBJECTIVES

The objectives of this study were to: 1) conduct a screening survey to identify high risk for asthma among school-age children in Hidalgo County, and, 2) study the potential health impact of school-related exposure to HAPs pertaining to asthma risk.

METHODS

We carried out a quantitative cross-sectional study combining a school-based asthma screening survey across 198 schools in Hidalgo County, Texas, with information on school neighborhood environments, including census tract-level information on hazardous air pollutants (HAPs) and socioeconomic status (SES) in the respective school neighborhoods. HAPs levels were assessed based on the EPA 2011 National-Scale Air Toxics Assessment (NATA) while SES information was assessed using data from the 2010-2014 American Community Survey.

RESULTS

2930 students completed the asthma screening survey and results showed an overall asthma prevalence of 9.4%, slightly higher than the national and state prevalence. Participants in the 14-18 years old age group showed a much higher asthma prevalence of 16.7%. When assessing school-neighborhood characteristics, our results revealed no significant differences in asthma prevalence across census tracts with different SES levels. For HAPs, in the single-pollutant model, chlorine levels showed a significant linear trend for prevalence of asthma (p=0.03) while hydrochloric acid had a marginally significant linear trend (p=0.08). The association with chlorine remained significant in the multi-pollutant model.

CONCLUSIONS

Asthma prevalence among school-age children in Hidalgo County, Texas, is 9.4%, which is slightly higher than the state rate, especially among young adults, ages 14-18 years who had an asthma rate of 16.7%. Results support an association between exposures to school-neighborhood HAPs and risk for pediatric asthma, especially as related to chlorine. No significant effects of school-level SES on asthma risk were observed.

Ozone sensitivity to its precursor emissions in northeastern Mexico for a summer air pollution episode

A summer episode was modeled to address the expected response of ambient air O3 to hypothetical emission control scenarios in northeastern Mexico, and in particular in the Monterrey Metropolitan Area (MMA). This region is of interest because the MMA holds one of the worst air quality problems in the country and levels of air pollutants in the rest of northeastern Mexico are starting to be a concern. The MM5-SMOKE-CMAQ platform was used to conduct the numerical experiments. Twenty-four control scenarios were evaluated, combining the level of emission controls of O3 precursors (NO(x) and volatile organic compounds [VOCs]) from 0% to 50%. For the MMA, VOC-only controls result in the best option to reduce O3 concentrations, though the benefit is limited to the urban core. This same strategy results in negligible benefits for the rest of northeastern Mexico. NO(x) controls result in an increase in O3 concentration within the MMA of up to 20 ppbv and a decrease at downwind locations of up to 11 ppbv, with respect to the base-case scenario. Indicator ratios were also used to probe for NO(x)-sensitive and VOC-sensitive areas. Locations with an important influence of NO(x) point sources (i.e., Monclova and Nava/Acuña) are quite sensitive to changes in NO(x) emissions. Border cities in the Rio Bravo/Grande Valley tend to be marginally NO(x)-sensitive. Overall, the MMA seems to be dominated by a VOC-sensitive regime, while the rest of the region would tend to have a NO(x)-sensitive response. The results obtained serve to expand the current knowledge on the chemical regimes that dominate this region (VOC- or NO(x)-sensitive), and thus could help guide public policies related to emission regional control strategies.

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: a case study in Taiyuan City, China

Primary fine particulate matters with a diameter of less than 10 microm (PM10) are important air emissions causing human health damage. PM10 concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM10 pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM10 yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM10 yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM10 from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM10 pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

IMPLICATIONS

The PM10 (particulate matter with an aerodynamic diameter < or = 10 microm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m3, was higher than the 65 microg/m3 recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM10 yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM10 spatial distribution. The results indicated that the artificial neural network was an effective method for PM10 pollution modeling.

Ambient air quality trends and driving factor analysis in Beijing, 1983-2007

The rapid development in Beijing, the capital of China, has resulted in serious air pollution problems. Meanwhile great efforts have been made to improve the air quality, especially since 1998. The variation in air quality under the interaction of pollution and control in this mega city has attracted much attention. We analyzed the changes in ambient air quality in Beijing since the 1980's using the Daniel trend test based on data from long-term monitoring stations. The results showed that different pollutants displayed three trends: a decreasing trend, an increasing trend and a flat trend. SO2, dustfall, B[a]P, NO2 and PM10 fit decreasing trend pattern, while NOx showed an increasing trend, and CO, ozone pollution, total suspended particulate (TSP), as well as Pb fit the flat trend. The cause of the general air pollution in Beijing has changed from being predominantly related to coal burning to mixed traffic exhaust and coal burning related pollution. Seasonally, the pollution level is typically higher during the heating season from November to the following March. The interaction between pollution sources change and implementation of air pollution control measures was the main driving factor that caused the variation in air quality. Changes of industrial structure and improved energy efficiency, the use of clean energy and preferred use of clean coal, reduction in pollution sources, and implementation of advanced environmental standards have all contributed to the reduction in air pollution, particularly since 1998.

Preliminary environmental monitoring of water quality in the Rio Grande in the Laredo-Nuevo Laredo Region

The international border region of the Rio Grande faces severe environmental and economic challenges. Contamination and degradation of its fragile lotic environments are mainly due to stresses from rapid population growth and unchecked industrial development. This study evaluates the water quality of the Rio Grande in the area of Nuevo Laredo, Mexico and Laredo, Texas, USA, in terms of physical, chemical and bacteriological parameters, as well as total metals, organochlorine pesticides, volatile organic compounds (VOC), semi-volatile organic compounds (SVOC) and radioactivity. Surface water samples were collected at 3 sites along the river. Two additional non-river sites (potable water and residual water) were studied for a better assessment of water quality in the region. Three series of samples were taken every other day during one week (November 3 to November 8, 2005) from the five sampling sites. Levels of oil and grease in all the river samples exceeded the limits established by Mexican regulations. Concentrations of aluminum above the permissible limits for source of drinking water and for quality for protection of freshwater biota were also found in all of the river sites. A number of unregulated elements (Cd, Sr, Mg, Na, Fe, Si, Li and K) appeared in the river samples. The average concentrations of Ba and Na in the potable water samples were below the permissible limits. Ca, Sr, Mg and Si were also found but are not regulated. The majority of the organic compounds studied in both the river and in residual water samples was below detection limits. In all the potable water samples, bromodichloromethane and dibromochloromethane were found above their limit of quantitation (LOQ), but these compounds are not regulated. This preliminary study suggests the need for consistent periodic monitoring to track the environmental status of the Rio Grande.