A meta-analysis of selected near-road air pollutants based on concentration decay rates

Assessing environmental injustice in Kansas City by linking paediatric asthma to local sources of pollution: a cross-sectional study

OBJECTIVE

A grassroots environmental-justice organisation in Kansas City has been examining the disproportionate exposure to air pollution experienced by residents living fenceline to the largest classification railyard in the USA. Prior analyses showed limited increased risk for asthma exacerbation for patients with asthma living closer to toxic release inventory (TRI) facilities and railyards. In this study, we assessed geographical asthma and environmental disparities, to further explore community-level disparities.

DESIGN

This is a cross-sectional study of population-level asthma rates, which included rates for all asthma encounters and acute asthma encounters (urgent care, emergency department, inpatient admission). Distances from census-tract centroids to nearest TRI facilities, railyards and highways were calculated. The association between asthma rates and distances was examined using Kendall's τ correlation and multivariable Poisson regression models.

SETTING

We used electronic medical record data from the regional paediatric hospital, census and Environmental Protection Agency (EPA) air monitoring data.

PARTICIPANTS

Patients with 2+ asthma encounters during the EPA study timeframe were identified.

RESULTS

Residential distance from railyards exhibited a significant negative correlation with overall (-0.36 (CI -0.41 to -0.32)) and acute (-0.27 (CI -0.32 to -0.22)) asthma rates. Asthma rates were elevated among tracts north of the closest railyard (incident rate ratio: 1.38; CI 1.35 to 1.41) when compared with southern directionality. An increased distance from the nearest railyard of 3 km was associated with a decrease in overall asthma rates of 26%.

CONCLUSION

Significant negative associations between proximity to all pollution source types and asthma rates were observed. This community-level research has served as a tool for community engagement and will be used to support proposed local policy. Environmental justice work addresses local concerns involving small, limited datasets, if the data exist at all. The academic epidemiological platform may reconsider acceptable approaches to small population research in order to better serve communities with the most need.

Association of midlife air pollution exposures and residential road proximity with incident dementia: The Atherosclerosis Risk in Communities (ARIC) study

BACKGROUND

Increasing evidence links higher air pollution exposures to increased risk of cognitive impairment. While midlife risk factors are often most strongly linked to dementia risk, few studies have considered associations between midlife roadway proximity or ambient air pollution exposure and incident dementia decades later, in late life.

OBJECTIVES

Our objective was to determine if midlife exposures to ambient air pollution or roadway proximity are associated with increased risk of dementia in the Atherosclerosis Risk in Communities (ARIC) study over up to 29 years of follow-up.

METHODS

Our eligible sample included Black and White ARIC participants without dementia at Visit 2 (1990-1992). Participants were followed through Visit 7 (2018-2019), with dementia status and onset date defined based on formal dementia ascertainment at study visits, informant interviews, and surveillance efforts. We used adjusted Weibull survival models to assess the associations of midlife ambient air pollution and road proximity with incident dementia.

RESULTS

The median age at baseline (1990-1992, Visit 2) of the 12,700 eligible ARIC participants was 57.0 years; 56.0% were female, 24.2% were Black, and 78.9% had at least a high school education. Over up to 29 years of follow-up, 2511 (19.8%) persons developed dementia. No associations were found between ambient air pollutants and proximity to major roadways with risk of incident dementia. In exploratory analyses, living closer to roadways in midlife increased dementia risk in individuals younger at baseline and those without midlife hypertension, and there was evidence of increased risk of dementia with increased midlife exposure to NOx, several PM2.5 components, and trace metals among those with diabetes in midlife.

CONCLUSIONS

Midlife exposure to ambient air pollution and midlife roadway proximity was not associated with dementia risk over decades of follow-up. Further investigation to explore potential for greater susceptibility among specific subgroups identified here is needed.

Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore

Introduction

Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ.

Methods

Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns.

Results and Discussion

Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.

Childhood cancer and traffic-related air pollution in Switzerland: A nationwide census-based cohort study

Motor vehicle exhaust is a major contributor to air pollution, and exposure to benzene or other carcinogenic components may increase cancer risks. We aimed to investigate the association between traffic-related air pollution and risk of childhood cancer in a nationwide cohort study in Switzerland. We identified incident cases from the Swiss Childhood Cancer Registry diagnosed < 16 years of age between 1990 and 2015 and linked them probabilistically with the census-based Swiss National Cohort study. We developed land use regression models to estimate annual mean ambient levels of nitrogen dioxide (NO2) and benzene outside 1.4 million children's homes. We used risk-set sampling to facilitate the analysis of time-varying exposure and fitted conditional logistic regression models adjusting for neighborhood socio-economic position, level of urbanization, and background ionizing radiation. We included 2,960 cancer cases in the analyses. The adjusted hazard ratios (HR) and 95% confidence intervals for exposure to NO2 per 10 μg/m3 were 1.00 (95%-CI 0.88-1.13) for acute lymphoblastic leukemia (ALL) and 1.31 (95%-CI 1.00-1.71) for acute myeloid leukemia (AML). Using exposure lagged by 1 to 5 years instead of current exposure attenuated the effect for AML. The adjusted HR for exposure to benzene per 1 μg/m3 was 1.03 (95%-CI 0.86-1.23) for ALL and 1.29 (95%-CI 0.86-1.95) for AML. We also observed increased HRs for other diagnostic groups, notably non-Hodgkin lymphoma. Our study adds to the existing evidence that exposure to traffic-related air pollution is associated with an increased risk of childhood leukemia, particularly AML.

Association of Chemical Aggregates and Fungal Moieties Affecting Native Environmental Films

Fungi are prevalent microorganisms in environmental films. Their impacts on the film chemical environment and morphology remains poorly defined. Here we present microscopic and chemical analyses fungi impacts to environmental films over long- and short-time scales. We report bulk properties of films accumulated for 2 months (February and March 2019) and 12 months to contrast short and longer-term effects. Bright field microscopy results show that fungi and fungal-associated aggregates cover close to 14% of the surface after 12 months and include significant numbers of large (tens to hundreds of μm in diameter) particles aggregated with fungal colonies. Data acquired for films accumulated over shorter times (2 months) suggest mechanisms that contribute to these longer-term effects. This is important because the film's exposed surface will determine what additional material will accumulate over the ensuing weeks or months. A combination of scanning electron microscopy and energy dispersive X-ray spectroscopy provides spatially resolved maps of fugal hypha and nearby elements of interest. We also identify a "nutrient pool" associated with the fungal hypha which extend orthogonally to the growth direction to ca. 50 μm distances. We conclude that fungi have both short-term and long-term effects on the chemistry and morphology of environmental film surfaces. In short, the presence (or absence) of fungi will significantly alter the films' evolution and should be considered when analyzing environmental film impacts on local processes.

Visual Parameter Selection for Spatial Blind Source Separation

Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.

Indoor Air Quality and Human Health Risk Assessment in the Open-Air Classroom

Indoor air quality is associated with academic performance and harmful health effects on students and teachers who participate in the classroom. Outdoor sources always contribute to classroom air quality. This study aims to estimate the amounts of indoor and outdoor pollutants and the influence of outdoor sources on open-air classrooms in a school located in the city. A health risk assessment was applied to assess the non-carcinogenic risk to students and teachers from exposure to the pollutants in the classroom. The concentrations of indoor NO2 ranged between 46.40 and 77.83 µg/m3, which is about 0.8 times that of outdoor NO2. A strong correlation and a high indoor/outdoor (I/O) ratio (>0.5) without a source, indicated that indoor NO2 is significantly influenced by outdoor sources. The range of indoor PM2.5 concentrations was 1.66 to 31.52 µg/m3 which was influenced by meteorological conditions. The indoor PM2.5 concentrations were affected by both indoor and outdoor sources. Although the level of indoor air pollutants met the official standard, the young children were exposed to indoor air pollutants which were above the recommended limits to human health with regard to the hazard index (HI) of 1.12. Instant measures such as regularly cleaning the classrooms, zoning the students, and installation of solid and vegetation barriers are recommended to reduce the daily dose of pollutants affecting students in open-air classrooms.

Spatial extent of road pollution: A national analysis

Roads form vast, pervasive and growing networks across the Earth, causing negative environmental impacts that spill out into a 'road-effect zone'. Previous research has estimated the regional and global extent of these zones using arbitrary distances, ignoring the spatial distribution and distance-dependent attenuation of different forms of road environmental impact. With Great Britain as a study area, we used mapping of roads and realistic estimates of how pollution levels decay with distance to project the spatial distribution of road pollution. We found that 25% of land was less than 79 m from a road, 50% of land was less than 216 m and 75% of land was less than 527 m. Roadless areas were scarce, and confined almost exclusively to the uplands (mean elevation 391 m), with only ca 12% of land in Great Britain more than 1 km from roads and <4% of land more than 2.5 km from roads. Using light, noise, heavy metals, NO₂, and particulate matter PM_2.5 and PM₁₀ as examples, we estimate that roads have a zone of influence that extends across >70% of the land area. Potentially less than 6% of land escapes any impact, resulting in nearly ubiquitously elevated pollution levels. Generalising from this, we find that, whilst the greatest levels of road pollution are relatively localised around the busiest roads, low levels of road pollution (which may be ecologically significant) are pervasive. Our findings demonstrate the importance of incorporating greater realism into road-effect zones and considering the ubiquity of road pollution in global environmental issues. We used Great Britain as a study area, but the findings likely apply to other densely populated regions at present, and to many additional regions in the future due to the predicted rapid expansion of the global road network.

A meta-analysis of Geogebra software decade of assisted mathematics learning: what to learn and where to go?

Today, hundreds of studies on mathematics learning have been found in various literature, supported by the use of GeoGebra software. This meta-analysis aims to determine the overall effect of using GeoGebra software and the extent to which study characteristics moderate the study effect sizes to consider the implications later. This study analyzed 36 effect sizes from 29 primary studies identified from ERIC documents, Sage Publishing, Google Scholar, and repositories from 2010 to 2020, and a total of 2111 students. In order to support calculation accuracy, a Comprehensive Meta-analysis (CMA) software was used. The effect size is determined using the Hedges equation, with an acceptable confidence level of 95%. It is known that the overall effect size of using GeoGebra software on the mathematical abilities of students is 0.96 based on the estimation of the random-effect model, and the standard error is 0.08. These findings indicate that, on average, students exposed to GeoGebra-based learning outperformed math abilities, which was initially equivalent to 82% of students in traditional classrooms. This study considers the five characteristics of the study. It showed that the GeoGebra software used was more effective in sample conditions less than or equal to 30. Providing classrooms with sufficient numbers of computers allowed students to use them individually, which was necessary to achieve a higher level of effectiveness. GeoGebra software is more effective when the treatment duration is set to less than or equal to four weeks. These findings help educators consider the characteristics of studies that moderate effect sizes using the GeoGebra software in the future.

Residential exposure to air pollution and access to neighborhood greenspace in relation to hair cortisol concentrations during the second and third trimester of pregnancy

BACKGROUND

Exposure to air pollution during pregnancy has been associated with adverse pregnancy outcomes in studies worldwide, other studies have described beneficial effects of residential greenspace on pregnancy outcomes. The biological mechanisms that underlie these associations are incompletely understood. A biological stress response, which implies release of cortisol, may underlie associations of air pollution exposure and access to neighborhood greenspaces with health.

METHODS

We explored residential exposure to air pollution and residential access to neighborhood greenspaces in relation to hair cortisol concentrations of participants in a prospective pregnancy cohort study in Flanders, Belgium. Hair samples were collected at the end of the second pregnancy trimester (n = 133) and shortly after delivery (n = 81). Cortisol concentrations were measured in 3-cm scalp-near hair sections, to reflect second and third pregnancy trimester cortisol secretion. We estimated long-term (3 months before sampling) residential exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and black carbon (BC), assessed residential distance to major roads and residential access to neighborhood greenspaces (NHGS). Associations between residential exposures and hair cortisol concentrations were studied using linear regression models while adjusting for season of sampling.

RESULTS

Three-month mean residential NO₂ and BC concentrations were positively associated with third pregnancy trimester hair cortisol concentrations (p = 0.008 and p = 0.017). Access to a large NHGS (10 ha or more within 800 m from residence) was negatively associated with third trimester hair cortisol concentrations (p = 0.019). Access to a large NHGS significantly moderated the association between residential proximity to major roads and second trimester hair cortisol concentrations (p = 0.021). Residential distance to major roads was negatively associated with second trimester hair cortisol concentrations of participants without access to a large NHGS (p = 0.003). The association was not significant for participants with access to a large NHGS. The moderation tended towards significance in the third pregnancy trimester (p < 0.10).

CONCLUSIONS

Our findings suggest a positive association between long-term residential exposure to air pollution and biological stress during pregnancy, residential access to neighborhood greenspaces may moderate the association. Further research is needed to confirm our results.

TRIAL REGISTRATION

The IPANEMA study is registered under number  NCT02592005 at clinicaltrials.gov .