Impact of 4th of July Fireworks on Spatiotemporal PM2.5 Concentrations in California Based on the PurpleAir Sensor Network: Implications for Policy and Environmental Justice

Bronchiolitis recovery and the use of High Efficiency Particulate Air (HEPA) Filters (The BREATHE Study): study protocol for a multi-center, parallel, double-blind, randomized controlled clinical trial

BACKGROUND

Acute viral bronchiolitis is the most common reason for hospitalization of infants in the USA. Infants hospitalized for bronchiolitis are at high risk for recurrent respiratory symptoms and wheeze in the subsequent year, and longer-term adverse respiratory outcomes such as persistent childhood asthma. There are no effective secondary prevention strategies. Multiple factors, including air pollutant exposure, contribute to risk of adverse respiratory outcomes in these infants. Improvement in indoor air quality following hospitalization for bronchiolitis may be a prevention opportunity to reduce symptom burden. Use of stand-alone high efficiency particulate air (HEPA) filtration units is a simple method to reduce particulate matter ≤ 2.5 µm in diameter (PM2.5), a common component of household air pollution that is strongly linked to health effects.

METHODS

BREATHE is a multi-center, parallel, double-blind, randomized controlled clinical trial. Two hundred twenty-eight children < 12 months of age hospitalized for the first time with bronchiolitis will participate. Children will be randomized 1:1 to receive a 24-week home intervention with filtration units containing HEPA and carbon filters (in the child's sleep space and a common room) or to a control group with units that do not contain HEPA and carbon filters. The primary objective is to determine if use of HEPA filtration units reduces respiratory symptom burden for 24 weeks compared to use of control units. Secondary objectives are to assess the efficacy of the HEPA intervention relative to control on (1) number of unscheduled healthcare visits for respiratory complaints, (2) child quality of life, and (3) average PM2.5 levels in the home.

DISCUSSION

We propose to test the use of HEPA filtration to improve indoor air quality as a strategy to reduce post-bronchiolitis respiratory symptom burden in at-risk infants with severe bronchiolitis. If the intervention proves successful, this trial will support use of HEPA filtration for children with bronchiolitis to reduce respiratory symptom burden following hospitalization.

TRIAL REGISTRATION

NCT05615870. Registered on November 14, 2022.

Methods in Public Health Environmental Justice Research: a Scoping Review from 2018 to 2021

PURPOSE OF REVIEW

The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods.

RECENT FINDINGS

We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods.

Data-Driven Placement of PM2.5 Air Quality Sensors in the United States: An Approach to Target Urban Environmental Injustice

In the United States, citizens and policymakers heavily rely upon Environmental Protection Agency mandated regulatory networks to monitor air pollution; increasingly they also depend on low-cost sensor networks to supplement spatial gaps in regulatory monitor networks coverage. Although these regulatory and low-cost networks in tandem provide enhanced spatiotemporal coverage in urban areas, low-cost sensors are located often in higher income, predominantly White areas. Such disparity in coverage may exacerbate existing inequalities and impact the ability of different communities to respond to the threat of air pollution. Here we present a study using cost-constrained multiresolution dynamic mode decomposition (mrDMDcc) to identify the optimal and equitable placement of fine particulate matter (PM2.5) sensors in four U.S. cities with histories of racial or income segregation: St. Louis, Houston, Boston, and Buffalo. This novel approach incorporates the variation of PM2.5 on timescales ranging from 1 day to over a decade to capture air pollution variability. We also introduce a cost function into the sensor placement optimization that represents the balance between our objectives of capturing PM2.5 extremes and increasing pollution monitoring in low-income and nonwhite areas. We find that the mrDMDcc algorithm places a greater number of sensors in historically low-income and nonwhite neighborhoods with known environmental pollution problems compared to networks using PM2.5 information alone. Our work provides a roadmap for the creation of equitable sensor networks in U.S. cities and offers a guide for democratizing air pollution data through increasing spatial coverage of low-cost sensors in less privileged communities.

Firework smoke: Impacts on urban air quality and deposition in the human respiratory system

Particle number concentrations and size distributions resulting from the firework displays held in Budapest, Hungary every year on St. Stephen's Day were studied over a period of seven years. In the year most impacted, the total particle number concentration reached its peak measured level of 369 × 10³ cm^-3 5 min after the end of the display, and returned to the pre-event state within 45 min. The fireworks increased hourly mean concentrations by a factor of 5-6, whereas the concentrations in the diameter range of 100-1000 nm, in which the magnitude of the increase was the greatest, were elevated by a factor of 20-25. An extra particle size mode at 203 nm was manifested in the size distributions as result of the fireworks. The PM₁₀ mass concentrations at peak firework influence and as 1-h mean increased 123 and 58 times, respectively, relative to the concentration before the display. The smoke was characterised by a relatively short overall atmospheric residence time of 25 min. Spatiotemporal dispersion simulations revealed that there were substantial vertical and horizontal concentration gradients in the firework plume. The affected area made up a large part of the city. Not only the spectators of the display at the venue and nearby areas, but the population located further away downwind of the displays and more distant, large and populous urban quarters were affected by the plume and its fallout. The fireworks increased the deposition rate in the respiratory system of females by a factor of 4, as a conservative estimate. The largest surface density deposition rates were seen in the segmental and sub-segmental bronchi, which represents an excessive risk to health. Compared to adults, children were more susceptible to exposure, with the maximum surface density deposition rates in their case being three times those of adults in the trachea.

Temporal trends in ambient fine particulate matter and the impacts of COVID-19 on this pollutant in Grenada, West Indies

Most Caribbean islands do not have air pollution surveillance programs. Those who live in these countries are exposed to ambient air pollution from a variety of sources including motor vehicles, ocean-going vessels, and Saharan dust. We conducted an air sampling exposure study in Grenada to describe daily changes in fine particulate matter (PM_2.5) pollution, and during Saharan dust episodes. Further, we assessed the impacts of COVID-19 public health interventions on PM_2.5 concentrations in 2020. Four fixed-site PurpleAir monitors were installed throughout Grenada, and one on the neighboring island of Carriacou. PM_2.5 was measured between January 6 and December 31, 2020. We classified each of these days based on whether COVID-19 public health mitigation measures were in place or not. Descriptive analyses were performed to characterize fluctuations in PM_2.5, and we assessed the impacts of public health restrictions on PM_2.5 using multivariate regression. The mean daily PM_2.5 concentration in 2020 was 4.4 μg/m³. During the study period, the minimum daily PM_2.5 concentration was 0.7 μg/m³, and the maximum was 20.4 μg/m³. Daily mean PM_2.5 concentrations more than doubled on Saharan dust days (8.5 vs 3.6 μg/m³; p < 0.05). The daily mean PM_2.5 concentrations were estimated to be 1.2 μg/m³ lower when COVID-19 restrictions were in effect. Ambient PM_2.5 concentrations in Grenada are relatively low compared to other countries; however, Saharan dust episodes represent an important source of exposure. Low-cost sensors provide an opportunity to increase surveillance of air pollution in the Caribbean, however their value could be enhanced with the development of correction algorithms that more closely approximate values from reference-grade monitors.Implications: This study describes daily fluctuations in ambient PM_2.5 concentrations in Grenada in 2020. Overall, concentrations of PM_2.5 were low; however, we found that Saharan dust events cause daily exceedances in PM_2.5 above the current 24-hr limits of the World Health Organization. Moreover, the constructed models suggest that public health interventions to reduce the spread of COVID-19 reduced PM_2.5 concentrations by 27%.

Neighborhood Composition and Air Pollution in Chicago: Monitoring Inequities With a Dense, Low-Cost Sensing Network, 2021

Objectives. To evaluate the efficacy of a novel, real-time sensor network for routine monitoring of racial and economic disparities in fine particulate matter (PM_2.5; particulate matter ≤ 2.5 µm in diameter) exposures at the neighborhood level. Methods. We deployed a dense network of low-cost PM_2.5 sensors in Chicago, Illinois, to evaluate associations between neighborhood-level composition variables (percentage of Black residents, percentage of Hispanic/Latinx residents, and percentage of households below poverty) and interpolated PM_2.5. Relationships were assessed in spatial lag models after adjustment for all composition variables. Models were fit with data both from the overall period and during high-pollution episodes associated with social events (July 4, 2021) and wildfires (July 23, 2021). Results. The spatial lag models showed that racial/ethnic composition variables were associated with higher PM_2.5 levels. Levels were notably higher in neighborhoods with larger compositions of Hispanic/Latinx residents across the entire study period and notably higher in neighborhoods with larger Black populations during the July 4 episode. Conclusions. As a complement to sparse regulatory networks, dense, low-cost sensor networks can capture spatial variations during short-term air pollution episodes and enable monitoring of neighborhood-level inequities in air pollution exposures in real time. (Am J Public Health. 2022;112(12):1765-1773. https://doi.org/10.2105/AJPH.2022.307068).

Neighborhood Composition and Air Pollution in Chicago: Monitoring Inequities With a Dense, Low-Cost Sensing Network, 2021

Objectives. To evaluate the efficacy of a novel, real-time sensor network for routine monitoring of racial and economic disparities in fine particulate matter (PM2.5; particulate matter ≤ 2.5 µm in diameter) exposures at the neighborhood level. Methods. We deployed a dense network of low-cost PM2.5 sensors in Chicago, Illinois, to evaluate associations between neighborhood-level composition variables (percentage of Black residents, percentage of Hispanic/Latinx residents, and percentage of households below poverty) and interpolated PM2.5. Relationships were assessed in spatial lag models after adjustment for all composition variables. Models were fit with data both from the overall period and during high-pollution episodes associated with social events (July 4, 2021) and wildfires (July 23, 2021). Results. The spatial lag models showed that racial/ethnic composition variables were associated with higher PM2.5 levels. Levels were notably higher in neighborhoods with larger compositions of Hispanic/Latinx residents across the entire study period and notably higher in neighborhoods with larger Black populations during the July 4 episode. Conclusions. As a complement to sparse regulatory networks, dense, low-cost sensor networks can capture spatial variations during short-term air pollution episodes and enable monitoring of neighborhood-level inequities in air pollution exposures in real time. (Am J Public Health. 2022;112(12):1765-1773. https://doi.org/10.2105/AJPH.2022.307068).

Unequal airborne exposure to toxic metals associated with race, ethnicity, and segregation in the USA

Persons of color have been exposed to a disproportionate burden of air pollution across the United States for decades. Yet, the inequality in exposure to known toxic elements of air pollution is unclear. Here, we find that populations living in racially segregated communities are exposed to a form of fine particulate matter with over three times higher mass proportions of known toxic and carcinogenic metals. While concentrations of total fine particulate matter are two times higher in racially segregated communities, concentrations of metals from anthropogenic sources are nearly ten times higher. Populations living in racially segregated communities have been disproportionately exposed to these environmental stressors throughout the past decade. We find evidence, however, that these disproportionate exposures may be abated though targeted regulatory action. For example, recent regulations on marine fuel oil not only reduced vanadium concentrations in coastal cities, but also sharply lessened differences in vanadium exposure by segregation.

Fine Particulate Matter Concentrations during Independence Day Fireworks Display in the Lower Rio Grande Valley Region, South Texas, USA

Fireworks are typically discharged as a mark of celebration and joy in many societies spanning various cultures. In the United States of America, 4th July is celebrated as the Independence Day when the nation overthrew the British colonial yoke in 1776. While this day instills a sense of patriotism in every American’s heart, it is also a major PM2.5 air pollution concern. This study is first of its type in the Lower Rio Grande Valley (RGV) Region of South Texas, USA, that characterizes fine particulate matter pollution. Using a low-cost sensor (TSI BlueSky Air Quality Monitor), real-time PM2.5 measurements were assessed at eleven different locations in four different towns and cities of Lower RGV Region: Brownsville, Edinburg, Weslaco, and Port Isabel. Hourly PM2.5 concentrations from July 03–06, 2021 are presented in this research work. Intraurban PM2.5 spatial and temporal variations provide an insight on the general population’s exposure burden during the festive period. Results indicate an increase in fine particulate matter pollution across the region, but the levels do not exceed the U.S. National Ambient Air Quality Standards (NAAQS). Findings from this study would possibly help in the formulation of effective firework policies to minimize the pollution impact.

Use of Low-Cost Particle Counters for Cotton Dust Exposure Assessment in Textile Mills in Low- and Middle-Income Countries

OBJECTIVE

There is a lack of consensus on methods for cotton dust measurement in the textile industry, and techniques vary between countries-relying mostly on cumbersome, traditional approaches. We undertook comparisons of standard, gravimetric methods with low-cost optical particle counters for personal and area dust measurements in textile mills in Pakistan.

METHODS

We included male textile workers from the weaving sections of seven cotton mills in Karachi. We used the Institute of Occupational Medicine (IOM) sampler with a Casella Apex 2 standard pump and the Purple Air (PA-II-SD) for measuring personal exposures to inhalable airborne particles (n = 31). We used the Dylos DC1700 particle counter, in addition to the two above, for area-level measurements (n = 29).

RESULTS

There were no significant correlations between the IOM and PA for personal dust measurements using the original (r = -0.15, P = 0.4) or log-transformed data (r = -0.32, P = 0.07). Similarly, there were no significant correlations when comparing the IOM with either of the particle counters (PA and Dylos) for area dust measurements, using the original (r = -0.07, P = 0.7; r = 0.10, P = 0.6) or log-transformed data (r = -0.09, P = 0.6; r = 0.07, P = 0.7).

CONCLUSION

Our findings show a lack of correlation between the gravimetric method and the use of particle counters in both personal and area measurements of cotton dust, precluding their use for measuring occupational exposures to airborne dust in textile mills. There continues to be a need to develop low-cost instruments to help textile industries in low- and middle-income countries to perform cotton dust exposure assessment.

Evaluation of the Policy Effect of China's Environmental Interview System for Effective Air Quality Governance

The Ministry of Ecology and Environment of the People's Republic of China formally proposed an environmental interview system in May 2014, which applies pressure on local governments to fulfill their responsibility toward environmental protection by conducting face-to-face public interviews with their officials. In this paper, 48 cities that were publicly interviewed from 2014-2020 were considered the experimental group and 48 cities surrounding them were the control group. First, the dynamic panel model is applied to initially determine the effect of the policy. Then, a regression discontinuity method (Sharp RD) is used to analyze the short-term and long-term effects and compare the reasons for the differences observed among the estimates of various types of samples. Finally, a series of robustness tests were also conducted. The results show that the environmental interview system can improve air quality. However, because an emergency short-term local governance system exists at present, the governance effect is not long-term and, therefore, not sustainable. Therefore, it suggests that the government should continue to improve the environmental interview system, establish an optimal environmental protection incentive mechanism, and encourage local governments to implement environmental protection policies effectively in the long term. The results of the research are of great significance to the environmental impact assessment system of the world, especially in countries with similar economic systems, which are facing a trade-off between economic growth and environmental sustainability.