Childhood asthma and exposure to traffic and nitrogen dioxide

The odds of developing asthma and wheeze among children and adolescents exposed to particulate matter: asystematic review and meta-analysis

BACKGROUND

Exposure to air pollution specifically particulate matter causes significant health risk to children which increases their susceptibility to respiratory diseases.

OBJECTIVES

This review aimed to pool the association between particulate matter exposure and childhood asthma and wheeze among children and adolescents.

METHODS

This review included observational study articles retrieved from electronic data bases such as PubMed, Google Scholar, Hinari, Science Direct, and Semantic Scholar from 1996 to June 17, 2024. Data were extracted and analyzed using Microsoft Excel 16 and STATA version 17, respectively. Joanna Briggs Institute evaluation criteria and I2 test statistics were used for quality and heterogeneity assessment, respectively.

RESULTS

Fourty seven studies with a total of 417,874 of children and adolescents met the inclusion criteria. The pooled odd ratio (OR) of the association between Particulate Matter with a diameter of 10 micrometers or less (PM10) and Particulate Matter with a diameter of 2.5 micrometers or less (PM2.5) with asthma were 1.04 (95% CI: 1.03-1.06, p < 0.001) with significant extreme heterogeneity (I² = 82.7%, p < 0.001) and 1.05 (95% CI 1.04-1.07, p < 0.001) with high heterogeneity (I² = 80.6%, p < 0.001) among the included studies, respectively. The overall pooled estimate indicates a statistically significant association between PM10 and wheeze, with OR of 1.06 (95% CI: 1.05, 1.07) and moderate heterogeneity among included studies (I²=57.5%, p < 0.007) where as more association was observed between PM2.5 and wheeze with OR of 1.15. (95% CI: 1.10, 1.20) with an (I² =72.8%, p < 0.001).

CONCLUSION

The findings of this systematic review and meta-analysis demonstrated a statistically significant association between exposure to both PM10 and PM2.5 and the occurrence of asthma and wheezing in children and adolescents. Both PM10 and PM2.5 are associated with increased odds of asthma and wheezing, with PM2.5 showing a stronger relationship. The significant levels of heterogeneity observed suggest variations across studies, which may be due to differences in study designs, exposure level and outcome measurement types. These findings indicate the need for strategies to reduce particle air pollution to mitigate its adverse effects on children's respiratory health.

Long-term Evaluation of Machine Learning Based Methods for Air Emission Monitoring

Machine learning (ML) techniques have been researched and used in various environmental monitoring applications. Few studies have reported the long-term evaluation of such applications. Discussions regarding the risks and regulatory frameworks of ML applications in environmental monitoring have been rare. We monitored the performance of six predictive models developed using ML and statistical methods for 28 months. The six models used to predict NOx emissions were developed using six different algorithms. The model developed with a moderate complexity algorithm, adaptive boosting, had the best performance in long-term monitoring, with a root mean square error (RMSE) of 0.48 kg/hr in the 28-month monitoring period, and passed two of the three relative accuracy test audits. High complexity models based on gradient boosting and neural network algorithms had the best training performance, with a minimum RMSE of 0.23 kg/hr and 0.26 kg/hr, but also had the worst RMSE scores, of 0.51 kg/hr and 0.57 kg/hr, during the monitoring period. In addition, all six models failed all three relative accuracy test audits. The following problems were observed: (1) Complex ML models tended to have overfitting problems, thus indicating the importance of the trade-off between model accuracy and complexity. (2) Model input sensor drift or out of high-frequency ranges from the training data resulted in inaccurate predictions or an accuracy lower than the minimum allowed by regulators. (3) Existing regulatory frameworks must be modernized to keep pace with current machine learning practices. Some statistical tests are unsuitable for applications developed by using ML methods.

Assessment of tropospheric NO2 concentrations over greater Doha using Sentinel-5 TROPOspheric monitoring instrument (TROPOMI) satellite data: Temporal analysis, 2018-2023

This study presents a temporal evaluation of the tropospheric NO2 column densities over Greater Doha using TROPOMI satellite data from May 2018 to December 2023, and an assessment of the impact of the preparations and hosting of the FIFA Football World Cup Qatar 2022, on NO2 levels before, during and after the tournament over Greater Doha. Analysis of annual NO2 levels from 2019 to 2023 showed an increase in 2022 compared to that of the previous three years and a clear decrease in 2023 post the completion of the world cup preparations and hosting. Results also showed an increase in NO2 levels during winter compared to that in summer, with wind speed being an important determining factor. Findings showed that Fridays and Saturdays (both constitute the local weekend in Qatar) were 44% and 13% lower than that of the averaged weekdays, respectively. The annual NO2 levels in the post-world cup year of 2023 were found to be 24% lower than that in 2022 and around 16% lower than that of the previous years. NO2 levels during the World Cup tournament (20 Nov to Dec 18, 2022) were found to be higher than that of the same corresponding periods in all other available years including an increase of 27% compared to that in 2023. Wind speed played an important role in determining the NO2 levels during the world cup period and accounted for >96% of their daily variability, indicating that meteorological factors substantially influenced the NO2 column during the event.

Exploring the correlation between airborne pollen levels and respiratory conditions in Jaipur, India

Airborne pollen, a significant natural pollutant, restricts outdoor activities and impacts quality of life for sensitive individuals with pulmonary disorders. This study examines trends in airborne pollen concentrations and explores whether air pollution, pollen concentration, or both impact patient counts. The annual pollen trend in Jaipur shows peaks in pollen concentration in March (due to trees, 66%), September (due to weeds, 45%), and December (due to grass, 50%). Among the fifteen taxa examined, Holoptelea integrifolia is the largest pollen emitter in Jaipur, followed by Poaceae, among others. The count of patients arriving for clinical consultations in a hospital shows a strong and positive correlation with weed (Asteraceae spp. and Argemone mexicana) and grass pollen. A linear regression equation is developed (R2 value = 0.835) for forecasting consulting patient counts based on Cassia siamea pollen concentration. This can assist hospital administration in resource management, especially during peak allergy seasons.

Neighborhood-Level Nitrogen Dioxide Inequalities Contribute to Surface Ozone Variability in Houston, Texas

In Houston, Texas, nitrogen dioxide (NO2) air pollution disproportionately affects Black, Latinx, and Asian communities, and high ozone (O3) days are frequent. There is limited knowledge of how NO2 inequalities vary in urban air quality contexts, in part from the lack of time-varying neighborhood-level NO2 measurements. First, we demonstrate that daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 tropospheric vertical column densities (TVCDs) resolve a major portion of census tract-scale NO2 inequalities in Houston, comparing NO2 inequalities based on TROPOMI TVCDs and spatiotemporally coincident airborne remote sensing (250 m × 560 m) from the NASA TRacking Aerosol Convection ExpeRiment-Air Quality (TRACER-AQ). We further evaluate the application of daily TROPOMI TVCDs to census tract-scale NO2 inequalities (May 2018-November 2022). This includes explaining differences between mean daily NO2 inequalities and those based on TVCDs oversampled to 0.01° × 0.01° and showing daily NO2 column-surface relationships weaken as a function of observation separation distance. Second, census tract-scale NO2 inequalities, city-wide high O3, and mesoscale airflows are found to covary using principal component and cluster analysis. A generalized additive model of O3 mixing ratios versus NO2 inequalities reproduces established nonlinear relationships between O3 production and NO2 concentrations, providing observational evidence that neighborhood-level NO2 inequalities and O3 are coupled. Consequently, emissions controls specifically in Black, Latinx, and Asian communities will have co-benefits, reducing both NO2 disparities and high O3 days city wide.

Tracing vulnerable communities to ambient air pollution exposure: A geodemographic and remote sensing approach

Most studies analyzing the effects of air pollution on disadvantaged populations use ground air quality measurements. However, ground stations are generally limited, with nearly 40% of countries having no official PM2.5 stations, not allowing air quality analysis for a significantly large share of the world's population. Furthermore, limited studies analyze community data from a geodemographic perspective, in other words, to delineate the sociodemographic profiles and geographically locate the socioeconomic groups more exposed to ambient air pollution. Therefore, a significant question arises: How can we trace vulnerable communities to air pollution in areas lacking air-quality ground data? Here, we propose a novel methodology to respond to this question. We use NO2, SO2, CO, and HCHO tropospheric column air-quality data from Sentinel-5P, a satellite that quantifies concentrations of atmospheric species from space operationally. We integrate them with census and environmental data and apply the local fuzzy geographically weighted clustering spatial machine learning method for segmentation analysis. Our findings for Bali, Indonesia, provide quantitative evidence for the benefits of this methodology in tracing and delineating the profiles of the communities most exposed to air pollution. For example, results show that communities with highly disadvantaged populations, such as unemployed (over 27.8%), low educated (over 27.9%), and children (over 22.1%) (mainly located around Bali's south and north coast touristic areas), exhibit very high values (over the 75th quartile) across the pollutants studied. The proposed method is reproducible easily, quickly, and at low cost, as it is based on freely available satellite data and not on costly ground station measurements. This will hopefully assist decision-makers in tracing the most vulnerable subpopulations, even in areas with inadequate air-quality monitoring networks, thus allowing local governments around the globe (even those that are financially weak) to achieve environmental justice and their sustainable development goals.

Effects of inhaled tier-2 diesel engine exhaust on immunotoxicity in a rat model: A hazard identification study. Part II. Immunotoxicology

Diesel exhaust (DE) is an air pollutant containing gaseous compounds and particulate matter. Diesel engines are common on gas extraction and oil sites, leading to complex DE exposure to a broad range of compounds through occupational settings. The US EPA concluded that short-term exposure to DE leads to allergic inflammatory disorders of the airways. To further evaluate the immunotoxicity of DE, the effects of whole-body inhalation of 0.2 and 1 mg/m3 DE (total carbon; 6 h/d for 4 days) were investigated 1-, 7-, and 27-days post exposure in Sprague-Dawley rats using an occupationally relevant exposure system. DE exposure of 1 mg/m3 increased total cellularity, number of CD4+ and CD8+ T-cells, and B-cells at 1 d post-exposure in the lung lymph nodes. At 7 d post-exposure to 1 mg/m3, cellularity and the number of CD4+ and CD8+ T-cells decreased in the LLNs. In the bronchoalveolar lavage, B-cell number and frequency increased at 1 d post-exposure, Natural Killer cell number and frequency decreased at 7 d post-exposure, and at 27 d post-exposure CD8+ T-cell and CD11b+ cell number and frequency decreased with 0.2 mg/m3 exposure. In the spleen, 0.2 mg/m3 increased CD4+ T-cell frequency at 1 and 7 d post-exposure and at 27 d post-exposure increased CD4+ and CD8+ T-cell number and CD8+ T-cell frequency. B-cells were the only immune cell subset altered in the three tissues (spleen, LLNs, and BALF), suggesting the induction of the adaptive immune response. The increase in lymphocytes in several different organ types also suggests an induction of a systemic inflammatory response occurring following DE exposure. These results show that DE exposure induced modifications of cellularity of phenotypic subsets that may impair immune function and contribute to airway inflammation induced by DE exposure in rats.

The Built Environment and Pediatric Health

Buildings, parks, and roads are all elements of the "built environment," which can be described as the human-made structures that comprise the neighborhoods and communities where people live, work, learn, and recreate (https://www.epa.gov/smm/basic-information-about-built-environment). The design of communities where children and adolescents live, learn, and play has a profound impact on their health. Moreover, the policies and practices that determine community design and the built environment are a root cause of disparities in the social determinants of health that contribute to health inequity. An understanding of the links between the built environment and pediatric health will help to inform pediatricians' and other pediatric health professionals' care for patients and advocacy on their behalf. This technical report describes the range of pediatric physical and mental health conditions influenced by the built environment, as well as historical and persistent effects of the built environment on health disparities. The accompanying policy statement outlines community design solutions that can improve pediatric health and health equity, including opportunities for pediatricians and the health care sector to incorporate this knowledge in patient care, as well as to play a role in advancing a health-promoting built environment for all children and families.

Childhood asthma and household exposures to nitrogen dioxide and fine particles: a triple-crossover randomized intervention trial

OBJECTIVE

Triple-crossover randomized controlled intervention trial to test whether reduced exposure to household NO₂ or fine particles results in reduced symptoms among children with persistent asthma.

METHODS

Children (n = 126) aged 5-11 years with persistent asthma living in homes with gas stoves and levels of NO₂ 15 ppb or greater recruited in Connecticut and Massachusetts (2015-2019) participated in an intervention involving three air cleaners configured for: (1) NO₂ reduction: sham particle filtration and real NO₂ scrubbing; (2) particle filtration: HEPA filter and sham NO₂ scrubbing; (3) control: sham particle filtration and sham NO₂ scrubbing. Air cleaners were randomly assigned for 5-week treatment periods using a three-arm crossover design. Outcome was number of asthma symptom-days during final 14 days of treatment. Treatment effects were assessed using repeated measures, linear mixed models.

RESULTS

Measured NO₂ was lower (by 4 ppb, p < .0001) for NO₂-reducing compared to control or particle-reducing treatments. NO₂-reducing treatment did not reduce asthma morbidity compared to control. In analysis controlling for measured NO₂, there were 1.8 (95% CI -0.3 to 3.9, p = .10) fewer symptom days out of 14 in the particle-reducing treatment compared to control.

CONCLUSIONS

It remains unknown if using an air cleaner alone can achieve levels of NO₂ reduction large enough to observe reductions in asthma symptoms. We observed that in small, urban homes with gas stoves, modest reductions in asthma symptoms occurred using air cleaners that remove fine particles. An intervention targeting exposures to both NO₂ and fine particles is complicated and further research is warranted.

REGISTRATION NUMBER

NCT02258893.

Drive less but exposed more? Exploring social injustice in vehicular air pollution exposure

Despite growing understanding of racial and class injustice in vehicular air pollution exposure, less is known about the relationship between people's exposure to vehicular air pollution and their contribution to it. Taking Los Angeles as a case study, this study examines the injustice in vehicular PM_2.5 exposure by developing an indicator that measures local populations' vehicular PM_2.5 exposure adjusted by their vehicle trip distances. This study applies random forest regression models to assess how travel behavior, demographic, and socioeconomic characteristics affect this indicator. The results indicate that census tracts of the periphery whose residents drive longer distances are exposed to less vehicular PM_2.5 pollution than tracts in the city center whose residents drive shorter distances. Ethnic minority and low-income tracts emit little vehicular PM_2.5 and are particularly exposed to it, while White and high-income tracts generate more vehicular PM_2.5 pollution but are less exposed.

Trajectories of neighborhood environmental factors and their associations with asthma symptom trajectories among children in Australia: evidence from a national birth cohort study

PURPOSE

This study aims to investigate the prospective associations of neighborhood environmental exposure trajectories with asthma symptom trajectories during childhood developmental stages.

METHODS

We considered asthma symptom, neighborhood environmental factors, and socio-demographic data from the "Longitudinal Study of Australian Children (LSAC)". Group-based trajectory modeling was applied to identify the trajectories of asthma symptom, neighborhood traffic conditions, and neighborhood livability scales (considered for safety and facilities). We used multivariable logistic regression models to assess associations between various neighborhood environmental factors and asthma symptom trajectories.

RESULTS

We included 4,174 children from the LSAC cohort in our study. Three distinct trajectories for asthma symptom were the outcome variables of this study. Among the neighborhood environmental factors, we identified two distinct trajectories for the prevalence of heavy traffic on street, and two trajectories of neighborhood liveability scale. Compared to the 'Low/no' asthma symptoms trajectory group, children exposed to a 'persistently high' prevalence of heavy traffic on street was also significantly associated with both 'transient high' [relative risk ratio (RRR):1.40, 95% CI:1.25,1.58) and 'persistent high' (RRR: 1.33, 95% CI:1.17,1.50)] asthma symptom trajectory groups. Trajectory of moderate and static neighborhood liveability score was at increased risk of being classified as 'transient high' (RRR:1.16, 95% CI:1.07,1.25) and 'persistent high' (RRR:1.38, 95% CI:1.27,1.50) trajectories of asthma symptom.

CONCLUSION

Exposure to heavy traffic and poor neighborhood liveability increased the risk of having an unfavourable asthma symptom trajectory in childhood. Reducing neighborhood traffic load and improving neighborhood safety and amenities may facilitate a favorable asthma symptom trajectory among these children.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-022-00824-z.

Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO₂) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO₂ inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO₂ remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO₂ inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO₂ inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO₂ inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km², but are sensitive to low observational coverage. We statistically analyze daily NO₂ inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO₂ inequalities and cumulative NO₂ and urban heat burdens with climate change.

Health effects of exposure to sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide between 1980 and 2019: A systematic review and meta-analysis

The burden of disease attributed to the indoor exposure to sulfur dioxide (SO₂ ), nitrogen dioxide (NO₂ ), ozone (O₃ ), and carbon monoxide (CO) is not clear, and the quantitative concentration-response relationship is a prerequisite. This is a systematic review to summarize the quantitative concentration-response relationships by screening and analyzing the polled effects of population-based epidemiological studies. After collecting literature published between 1980 and 2019, a total of 19 health outcomes in 101 studies with 182 health risk estimates were recruited. By meta-analysis, the leave-one-out sensitivity analysis and Egger's test for publication bias, the robust and reliable effects were found for SO₂ (per 10 μg/m³ ) with chronic obstructive pulmonary diseases (COPD) (pooled relative risks [RRs] 1.016, 95% CI: 1.012-1.021) and cardiovascular diseases (CVD) (RR 1.012, 95%CI: 007-1.018), respectively. NO₂ (per 10 μg/m³ ) had the pooled RRs for childhood asthma, preterm birth, lung cancer, diabetes, and COPD by 1.134 (1.084-1.186), 1.079 (1.007-1.157), 1.055 (1.010-1.101), 1.019 (1.009-1.029), and 1.016 (1.012-1.120), respectively. CO (per 1 mg/m³ ) was significantly associated with Parkinson's disease (RR 1.574, 95% CI: 1.069-2.317) and CVD (RR 1.024, 95% CI: 1.011-1.038). No robust effects were observed for O₃ . This study provided evidence and basis for further estimation of the health burden attributable to the four gaseous pollutants.

The priming effect of diesel exhaust on native pollen exposure at the air-liquid interface

Pollen related allergic diseases have been increasing for decades. The reasons for this increase are unknown, but environmental pollution like diesel exhaust seem to play a role. While previous studies explored the effects of pollen extracts, we studied here for the first time priming effects of diesel exhaust on native pollen exposure using a novel experimental setup.

METHODS

Human bronchial epithelial BEAS-2B cells were exposed to native birch pollen (real life intact pollen, not pollen extracts) at the air-liquid interface (pollen-ALI). BEAS-2B cells were also pre-exposed in a diesel-ALI to diesel CAST for 2 h (a model for diesel exhaust) and then to pollen in the pollen-ALI 24 h later. Effects were analysed by genome wide transcriptome analysis after 2 h 25 min, 6 h 50 min and 24 h. Selected genes were confirmed by qRT-PCR.

RESULTS

Bronchial epithelial cells exposed to native pollen showed the highest transcriptomic changes after about 24 h. About 3157 genes were significantly up- or down-regulated for all time points combined. After pre-exposure to diesel exhaust the maximum reaction to pollen had shifted to about 2.5 h after exposure, plus the reaction to pollen was desensitised as only 560 genes were differentially regulated. Only 97 genes were affected synergistically. Of these, enrichment analysis showed that genes involved in immune and inflammatory response were involved.

CONCLUSION

Diesel exhaust seems to prime cells to react more rapidly to native pollen exposure, especially inflammation related genes, a factor known to facilitate the development of allergic sensitization. The marker genes here detected could guide studies in humans when investigating whether modern and outdoor diesel exhaust exposure is still detrimental for the development of allergic disease.

An Examination of the Intersection of Climate Change, the Physician Specialty Workforce, and Graduate Medical Education in the U.S

Issue: As U.S. healthcare systems plan for future physician workforce needs, the systemic impacts of climate change, a worldwide environmental and health crisis, have not been factored in. The current focus on increasing the number of trained physicians and optimizing efficiencies in healthcare delivery may be insufficient. Graduate medical education (GME) priorities and training should be considered in order to prepare a climate-educated physician workforce. Evidence: We used a holistic lens to explore the available literature regarding the intersection of future physician workforce needs, GME program priorities, and resident education within the larger context of climate change. Our interinstitutional, transdisciplinary team brought perspectives from their own fields, including climate science, climate and health research, and medical education to provide recommendations for building a climate-educated physician workforce. Implications: Acknowledging and preparing for the effects of climate change on the physician workforce will require identification of workforce gaps, changes to GME program priorities, and education of trainees on the health and societal impacts of climate change. Alignment of GME training with workforce considerations and climate action and adaptation initiatives will be critical in ensuring the U.S. has a climate-educated physician workforce capable of addressing health and healthcare system challenges. This article offers a number of recommendations for physician workforce priorities, resident education, and system-level changes to better prepare for the health and health system impacts of climate change.

Dust Climatology of Turkey as a Part of the Eastern Mediterranean Basin via 9-Year CALIPSO-Derived Product

Turkey is located in the heart of complex transition geography between Eurasia and the Middle East. In the grand scheme, the so-called eastern Mediterranean Basin is located almost in the middle of the dusty belt, and is a hot spot of climate change. The downstream location of dust-carrying winds from close desert sources reveals Turkey as an open plane to particulate matter exposure throughout the year. In order to clarify this phenomenon, this paper aims to determine the desert dust climatology of Turkey via CALIPSO onboard Lidar. This prominent instrument enables us to understand clouds, aerosols and their types, and related climatic systems, with its valuable products. In this study, a 9-year CALIPSO-derived pure dust product dataset was formed to explain horizontal and vertical distributions, transport heights and case incidences. The results indicated that the pure dust extinction coefficient increased as the location shifted from west to east. Moreover, in the same direction of west to east, the dominant spring months changed to summer and autumn. Mountain range systems surrounding Anatolia were the main obstacles against lofted and buoyant dust particles travelling to northern latitudes. Even if high ridges accumulated mass load on the southern slopes, they also enabled elevated particles to reach the ground level of the inner cities.

Child serum metabolome and traffic-related air pollution exposure in pregnancy

BACKGROUND

Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates.

METHODS

We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM_2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education.

RESULTS

In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM_2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism.

CONCLUSION

The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

Long-term trends in urban NO2 concentrations and associated paediatric asthma incidence: estimates from global datasets

BACKGROUND

Combustion-related nitrogen dioxide (NO₂) air pollution is associated with paediatric asthma incidence. We aimed to estimate global surface NO₂ concentrations consistent with the Global Burden of Disease study for 1990-2019 at a 1 km resolution, and the concentrations and attributable paediatric asthma incidence trends in 13 189 cities from 2000 to 2019.

METHODS

We scaled an existing annual average NO₂ concentration dataset for 2010-12 from a land use regression model (based on 5220 NO₂ monitors in 58 countries and land use variables) to other years using NO₂ column densities from satellite and reanalysis datasets. We applied these concentrations in an epidemiologically derived concentration-response function with population and baseline asthma rates to estimate NO₂-attributable paediatric asthma incidence.

FINDINGS

We estimated that 1·85 million (95% uncertainty interval [UI] 0·93-2·80 million) new paediatric asthma cases were attributable to NO₂ globally in 2019, two thirds of which occurred in urban areas (1·22 million cases; 95% UI 0·60-1·8 million). The proportion of paediatric asthma incidence that is attributable to NO₂ in urban areas declined from 19·8% (1·22 million attributable cases of 6·14 million total cases) in 2000 to 16·0% (1·24 million attributable cases of 7·73 million total cases) in 2019. Urban attributable fractions dropped in high-income countries (-41%), Latin America and the Caribbean (-16%), central Europe, eastern Europe, and central Asia (-13%), and southeast Asia, east Asia, and Oceania (-6%), and rose in south Asia (+23%), sub-Saharan Africa (+11%), and north Africa and the Middle East (+5%). The contribution of NO₂ concentrations, paediatric population size, and asthma incidence rates to the change in NO₂-attributable paediatric asthma incidence differed regionally.

INTERPRETATION

Despite improvements in some regions, combustion-related NO₂ pollution continues to be an important contributor to paediatric asthma incidence globally, particularly in cities. Mitigating air pollution should be a crucial element of public health strategies for children.

FUNDING

Health Effects Institute, NASA.

Family, neighborhood and psychosocial environmental factors and their associations with asthma in Australia: a systematic review and Meta-analysis

OBJECTIVE

Various associations between different environmental exposures and asthma have been reported in different countries and populations. We aimed to investigate the associations between family, neighborhood and psychosocial environmental factors and asthma-symptoms in Australia by conducting a systematic review and meta-analysis.

DATA SOURCES

We analyzed the primary research studies conducted in Australia across multiple databases, including PubMed, EMBASE and Scopus, published between 2000 and 2020.

STUDY SELECTIONS

The reviews and analyses focused on the overall association of different environmental exposures with the exacerbation of asthma-symptoms or asthma-related hospital visits. Quality-effect meta-analysis was done to estimate the pooled odds ratio for different environmental exposures for asthma-symptoms.

RESULTS

Among the 4799 unique published articles found, 46 were included here for systematic review and 28 for meta-analysis. Our review found that psychosocial factors, including low socioeconomic condition, maternal depression, mental stress, ethnicity, and discrimination, are associated with asthma-symptoms. Pooled analysis was conducted on family and neighborhood environmental factors and revealed that environmental tobacco smoking (ETS) (OR 1·69, 95% CI 1·19-2·38), synthetic bedding (OR 1·91, 95% CI 1·48-2·47) and gas heaters (OR 1·40, 95% CI 1·12-1·76) had significant overall associations with asthma-symptoms in Australia.

CONCLUSION

Although the studies were heterogeneous, both systematic review and meta-analysis found several psychosocial and family environmental exposures significantly associated with asthma-symptoms. Further study to identify their causal relationship and modification may reduce asthma-symptoms in the Australian population.

Using demand mapping to assess the benefits of urban green and blue space in cities from four continents

The benefits of urban green and blue infrastructure (UGI) are widely discussed, but rarely take into account local conditions or contexts. Although assessments increasingly consider the demand for the ecosystem services that UGI provides, they tend to only map the spatial pattern of pressures such as heat, or air pollution, and lack a wider understanding of where the beneficiaries are located and who will benefit most. We assess UGI in five cities from four continents with contrasting climate, socio-political context, and size. For three example services (air pollution removal, heat mitigation, accessible greenspace), we run an assessment that takes into account spatial patterns in the socio-economic demand for ecosystem services and develops metrics that reflect local context, drawing on the principles of vulnerability assessment. Despite similar overall levels of UGI (from 35 to 50% of urban footprint), the amount of service provided differs substantially between cities. Aggregate cooling ranged from 0.44 °C (Leicester) to 0.98 °C (Medellin), while pollution removal ranged from 488 kg PM_2.5/yr (Zomba) to 48,400 kg PM_2.5/yr (Dhaka). Percentage population with access to nearby greenspace ranged from 82% (Dhaka) to 100% (Zomba). The spatial patterns of pressure, of ecosystem service, and of maximum benefit within a city do not necessarily match, and this has implications for planning optimum locations for UGI in cities.

Spatiotemporal analysis of traffic congestion, air pollution, and exposure vulnerability in Tanzania

Using new satellite data from the European Space Agency's Sentinel-5P system, this article investigates the spatial and temporal dynamics of vehicular traffic congestion, air pollution, and the distributional impacts on vulnerable populations in Dar es Salaam, Tanzania. The metro region's rapid growth in vehicle traffic exceeds road network capacity, generating congestion, transport delays, and air pollution from excess fuel use. Dangerously high pollution levels from tailpipe emissions put the health of vulnerable residents at risk, calling for the need to adopt continuous air-quality monitoring and effective pollution control. Our results highlight significant impacts of seasonal weather and wind-speed factors on the spatial distribution and intensity of air pollution from vehicle emissions, which vary widely by area. In seasons when weather factors maximize pollution, the worst exposure occurs along the wind path of high-traffic roadways. The study identifies priority areas for reducing congestion to yield the greatest exposure reduction for young children and the elderly in poor households. This new research direction, based only on the use of free global information sources with the same coverage for all cities, offers metropolitan areas in developing regions the opportunity to benefit from the rigorous analyses traditionally limited to well-endowed cites in developing countries.

Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea

Since April 2018, the TROPOspheric Monitoring Instrument (TROPOMI) has provided data on tropospheric NO2 column concentrations (CTROPOMI) with unprecedented spatial resolution. This study aims to assess the capability of TROPOMI to acquire high spatial resolution data regarding surface NO2 mixing ratios. In general, the instrument effectively detected major and moderate sources of NO2 over South Korea with a clear weekday–weekend distinction. We compared the CTROPOMI with surface NO2 mixing ratio measurements from an extensive ground-based network over South Korea operated by the Korean Ministry of Environment (SKME; more than 570 sites), for 2019. Spatiotemporally collocated CTROPOMI and SKME showed a moderate correlation (correlation coefficient, r = 0.67), whereas their annual mean values at each site showed a higher correlation (r = 0.84). The CTROPOMI and SKME were well correlated around the Seoul metropolitan area, where significant amounts of NO2 prevailed throughout the year, whereas they showed lower correlation at rural sites. We converted the tropospheric NO2 from TROPOMI to the surface mixing ratio (STROPOMI) using the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) profile shape, for quantitative comparison with the SKME. The estimated STROPOMI generally underestimated the in-situ value obtained, SKME (slope = 0.64), as reported in previous studies.

Day time, night time, over time: geographic and temporal uncertainty when linking event and contextual data

BACKGROUND

The growth of geolocated data has opened the door to a wealth of new research opportunities in the health fields. One avenue of particular interest is the relationship between the spaces where people spend time and their health outcomes. This research model typically intersects individual data collected on a specific cohort with publicly available socioeconomic or environmental aggregate data. In spatial terms: individuals are represented as points on map at a particular time, and context is represented as polygons containing aggregated or modeled data from sampled observations. Uncertainty abounds in these kinds of complex representations.

METHODS

We present four sensitivity analysis approaches that interrogate the stability of spatial and temporal relationships between point and polygon data. Positional accuracy assesses the significance of assigning the point to the correct polygon. Neighborhood size investigates how the size of the context assumed to be relevant impacts observed results. Life course considers the impact of variation in contextual effects over time. Time of day recognizes that most people occupy different spaces throughout the day, and that exposure is not simply a function residential location. We use eight years of point data from a longitudinal study of children living in rural Pennsylvania and North Carolina and eight years of air pollution and population data presented at 0.5 mile (0.805 km) grid cells. We first identify the challenges faced for research attempting to match individual outcomes to contextual effects, then present methods for estimating the effect this uncertainty could introduce into an analysis and finally contextualize these measures as part of a larger framework on uncertainty analysis.

RESULTS

Spatial and temporal uncertainty is highly variable across the children within our cohort and the population in general. For our test datasets, we find greater uncertainty over the life course than in positional accuracy and neighborhood size. Time of day uncertainty is relatively low for these children.

CONCLUSIONS

Spatial and temporal uncertainty should be considered for each individual in a study since the magnitude can vary considerably across observations. The underlying assumptions driving the source data play an important role in the level of measured uncertainty.

Proximity to Major Roads and Risks of Childhood Recurrent Wheeze and Asthma in a Severe Bronchiolitis Cohort

Air pollution exposures have been suggested as risk factors for childhood respiratory diseases. We investigated proximity to major roads, an indicator of air pollution exposure, and its associations with childhood recurrent wheeze and asthma. We used data from a multicenter prospective cohort study of 921 infants hospitalized for bronchiolitis and recruited from 14 U.S. states. Primary exposure was residential proximity to the nearest major road at birth through age 3 years. Residential distance from nearest major road was divided into four categories: <100, 100–200, 201–300, and >300 m. Outcomes were parent-reported recurrent wheeze by age 3 years and asthma by age 5 years. Associations between residential proximity to major roads and respiratory outcomes were investigated using multivariable Cox proportional hazards modeling and logistic regression, adjusted for confounders. Out of 920 participants with home address data, pooled estimates identified 241 (26%) participants resided within 300 m of a major road, 296 (32%) developed recurrent wheeze by age 3, and 235 out of 858 participants (27%) developed asthma by 5 years. Participants who resided close to a major road had the highest risk of recurrent wheeze (adjusted hazards ratio for <100 m, 1.59, 95%CI: 1.08–2.33) and asthma (adjusted odds ratio for 201–300 m, 1.62, 95%CI: 1.16–2.25), compared to those residing >300 m from a major road. Proximity to major roads is associated with increased risks of recurrent wheeze and asthma in young children.

A hybrid approach to predict daily NO2 concentrations at city block scale

Estimating the ambient concentration of nitrogen dioxide (NO2) is challenging because NO2 generated by local fossil fuel combustion varies greatly in concentration across space and time. This study demonstrates an integrated hybrid approach combining dispersion modeling and land use regression (LUR) to predict daily NO2 concentrations at a high spatial resolution (e.g., 50 m) in the New York tri-state area. The daily concentration of traffic-related NO2 was estimated at the Environmental Protection Agency's NO2 monitoring sites in the study area for the years 2015-2017, using the Research LINE source (R-LINE) model with inputs of traffic data provided by the Highway Performance and Management System and meteorological data provided by the NOAA Integrated Surface Database. We used the R-LINE-predicted daily concentrations of NO2 to build mixed-effects regression models, including additional variables representing land use features, geographic characteristics, weather, and other predictors. The mixed model was selected by the Elastic Net method. Each model's performance was evaluated using the out-of-sample coefficient of determination (R2) and the square root of mean squared error (RMSE) from ten-fold cross-validation (CV). The mixed model showed a good prediction performance (CV R2: 0.75-0.79, RMSE: 3.9-4.0 ppb). R-LINE outputs improved the overall, spatial, and temporal CV R2 by 10.0%, 18.9% and 7.7% respectively. Given the output of R-LINE is point-based and has a flexible spatial resolution, this hybrid approach allows prediction of daily NO2 at an extremely high spatial resolution such as city blocks.

Gradient-Based Colorimetric Array Sensor for Continuous Monitoring of Multiple Gas Analytes

Colorimetry is widely used in chemical sensing due to its high sensitivity and high selectivity. However, most colorimetric sensors are one-time use because the color-producing reactions or bindings are usually irreversible. In addition, traditional colorimetric sensors like the detection tubes are bulky and packed individually, making parallel sensing of multiple analytes difficult. Here, we demonstrate a gradient-based colorimetric array sensor (GCAS) to overcome these limitations. Different colorimetric sensing elements are inkjet-printed as parallel straight lines on a porous substrate. Lateral transport of analytes across the substrate creates color gradients on the sensing elements. The color gradients shift along the transport direction over time, and GCAS tracks the gradient shifts and converts them into analyte concentrations in real time. Using a low-cost complementary metal-oxide semiconductor imager, we show detection of three air pollutants using a single GCAS chip and 24 h continuous monitoring of ambient ozone.

A Simple Technique Based on Digital Images for Determination of Nitrogen Dioxide in Ambient Air

The lockdown to prevent the coronavirus spread resulted in an immediate reduction in gas concentration worldwide. This fact shows the importance of nitrogen dioxide as a pollutant gas directly associated with human activities. For indoor exposure, NO₂ has been associated with effects on the respiratory system. In outdoor environments, ozone reaches a maximum after NO₂ peaks, and acid rain arises with NO₂ oxidation to forms nitric acid. Therefore, monitoring the NO₂ concentration in atmospheric air can help prevent respiratory diseases and lower the concentration of other atmospheric pollutants. The experiment proposed in this article uses a low-cost passive sampler for the NO₂ collection. An innovative and straightforward technique to determine the gas concentration through a gel-dyed formation and based on digital image analysis RGB colors channel are split by the software ImageJ. Results of digital image analysis and spectrophotometry were statistically agreed at a 95% confidence level. The advantages of the technique include low cost, the ready availability of components, ease of use, and sensitivity. The achievable resolution of nitrogen dioxide concentrations is 9 ppb for 24-h sampling.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11270-021-05031-4.

Measurement of the gross alpha activity of the fine fractions of road dust and near-roadway ambient particle matter

Traffic-related air pollution, including direct exhaust emissions and road dust (RD), impacts individuals living near busy roads. We recently conducted a study to investigate the sources and composition of tailpipe and non-tailpipe traffic emissions, where we collected and analyzed samples of ambient air fine particulate matter (PM_2.5) and fine RD (RD_2.5) at different distances from major roadways. We analyzed a subset of the samples, including those collected at the roadside and local background, for their alpha activity level. Subsequently, we investigated whether there is a distance-related decay in the alpha activity in RD_2.5 or PM_2.5 similar to those observed for traffic-related species in PM_2.5 and RD_2.5. We found that the alpha activity of ambient air PM_2.5 (Bq/mg) was more than an order of magnitude higher than the activity level of the corresponding RD_2.5 sample, suggesting that PM_2.5 may be more toxic than RD_2.5. Using mixed-effects regression models, we found that ambient PM_2.5 alpha activity was significantly higher during the cold months than during warm months, and that the background was higher than the roadside (though not significantly). In contrast, the RD_2.5 alpha activity was significantly higher at the background site compared to the roadside but was not significantly affected by season. In addition to sampling position, both Zn and elemental carbon (EC) were significant predictors of RD_2.5 alpha activity. In addition, the roadside RD_2.5 activity levels were found to be higher at highways as compared to secondary roads. While traffic-related emissions do not appear to be significant sources of either ambient PM_2.5 or RD_2.5 alpha activity, the RD_2.5 results suggest that traffic-related particles may contribute to RD_2.5 alpha-activity. Implications: Many studies have reported the effects of traffic-related particulate matter (PM) on human health, and there is growing interest in the health effects of exposure to environmental PM alpha activity. This is the first study to report on the alpha activity of road dust (RD) or near-roadway ambient PM. We found that the alpha activity of ambient PM is twenty times higher than RD, suggesting that ambient PM may be more toxic. In PM and RD, the alpha activities were higher at background sites than at the roadside, indicating that traffic-related emissions are not a significant source of particulate radioactivity.

Contribution of tailpipe and non-tailpipe traffic sources to quasi-ultrafine, fine and coarse particulate matter in southern California

Exposure to traffic-related air pollution (TRAP) in the near-roadway environment is associated with multiple adverse health effects. To characterize the relative contribution of tailpipe and non-tailpipe TRAP sources to particulate matter (PM) in the quasi-ultrafine (PM_0.2), fine (PM_2.5) and coarse (PM_2.5-10) size fractions and identify their spatial determinants in southern California (CA). Month-long integrated PM_0.2, PM_2.5 and PM_2.5-10 samples (n = 461, 265 and 298, respectively) were collected across cool and warm seasons in 8 southern CA communities (2008-9). Concentrations of PM mass, elements, carbons and major ions were obtained. Enrichment ratios (ER) in PM_0.2 and PM₁₀ relative to PM_2.5 were calculated for each element. The Positive Matrix Factorization model was used to resolve and estimate the relative contribution of TRAP sources to PM in three size fractions. Generalized additive models (GAMs) with bivariate loess smooths were used to understand the geographic variation of TRAP sources and identify their spatial determinants. EC, OC, and B had the highest median ER in PM_0.2 relative to PM_2.5. Six, seven and five sources (with characteristic species) were resolved in PM_0.2, PM_2.5 and PM_2.5-10, respectively. Combined tailpipe and non-tailpipe traffic sources contributed 66%, 32% and 18% of PM_0.2, PM_2.5 and PM_2.5-10 mass, respectively. Tailpipe traffic emissions (EC, OC, B) were the largest contributor to PM_0.2 mass (58%). Distinct gasoline and diesel tailpipe traffic sources were resolved in PM_2.5. Others included fuel oil, biomass burning, secondary inorganic aerosol, sea salt, and crustal/soil. CALINE4 dispersion model nitrogen oxides, trucks and intersections were most correlated with TRAP sources. The influence of smaller roadways and intersections became more apparent once Long Beach was excluded. Non-tailpipe emissions constituted ~8%, 11% and 18% of PM_0.2, PM_2.5 and PM_2.5-10, respectively, with important exposure and health implications. Future efforts should consider non-linear relationships amongst predictors when modeling exposures. Implications: Vehicle emissions result in a complex mix of air pollutants with both tailpipe and non-tailpipe components. As mobile source regulations lead to decreased tailpipe emissions, the relative contribution of non-tailpipe traffic emissions to near-roadway exposures is increasing. This study documents the presence of non-tailpipe abrasive vehicular emissions (AVE) from brake and tire wear, catalyst degradation and resuspended road dust in the quasi-ultrafine (PM_0.2), fine and coarse particulate matter size fractions, with contributions reaching up to 30% in PM_0.2 in some southern California communities. These findings have important exposure and policy implications given the high metal content of AVE and the efficiency of PM_0.2 at reaching the alveolar region of the lungs and other organ systems once inhaled. This work also highlights important considerations for building models that can accurately predict tailpipe and non-tailpipe exposures for population health studies.

Reported Neighborhood Traffic and the Odds of Asthma/Asthma-Like Symptoms: A Cross-Sectional Analysis of a Multi-Racial Cohort of Children

Asthma in children poses a significant clinical and public health burden. We examined the association between reported neighborhood traffic (a proxy for traffic-related air pollution) and asthma among 855 multi-racial children aged 4-8 years old who participated in the Environmental Influences on Child Health Outcomes (ECHO) cohort. We hypothesized that high neighborhood traffic density would be associated with the prevalence of asthma. Asthma/asthma-like symptoms (defined as current and/or past physician diagnosed asthma, past wheezing, or nighttime cough or wheezing in the past 12 months) was assessed by parental report. The relationship between neighborhood traffic and asthma/asthma-like symptoms was assessed using logistic regression. The prevalence of asthma/asthma-like symptoms among study participants was 23%, and 15% had high neighborhood traffic. Children with significant neighborhood traffic had a higher odds of having asthma/asthma-like symptoms than children without neighborhood traffic [adjusted OR = 2.01 (95% CI: 1.12, 3.62)] after controlling for child's race-ethnicity, age, sex, maternal education, family history of asthma, play equipment in the home environment, public parks, obesity and prescribed asthma medication. Further characterization of neighborhood traffic is needed since many children live near high traffic zones and significant racial/ethnic disparities exist.

Evaluation of associations between asthma exacerbations and distance to roadways using geocoded electronic health records data

Background

Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and ozone, which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether proximity to highways increases risk of asthma exacerbations.

Methods

To evaluate the impact of highway proximity, we assessed the association between asthma exacerbations and the distance of child’s primary residence to two types of roadways in Durham County, North Carolina, accounting for other patient-level factors. We abstracted data from the Duke University Health System electronic health record (EHR), identifying 6208 children with asthma between 2014 and 2019. We geocoded each child’s distance to roadways (both 35 MPH+ and 55 MPH+). We classified asthma exacerbation severity into four tiers and fitted a recurrent event survival model to account for multiple exacerbations.

Results

There was a no observed effect of residential distance from 55+ MPH highway (Hazard Ratio: 0.98 (95% confidence interval: 0.94, 1.01)) and distance to 35+ MPH roadway (Hazard Ratio: 0.98 (95% confidence interval: 0.83, 1.15)) and any asthma exacerbation. Even those children living closest to highways (less 0.25 miles) had no increased risk of exacerbation. These results were consistent across different demographic strata.

Conclusions

While the results were non-significant, the characteristics of the study sample – namely farther distance to roadways and generally good ambient environmental pollution may contribute to the lack of effect. Compared to previous studies, which often relied on self-reported measures, we were able to obtain a more objective assessment of outcomes. Overall, this work highlights the opportunity to use EHR data to study environmental impacts on disease.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s12889-020-09731-0.

Diesel exhaust particle exposure reduces expression of the epithelial tight junction protein Tricellulin

BACKGROUND

While exposure to diesel exhaust particles has been linked to aberrant immune responses in allergic diseases such as asthma, little attention has been paid to their effects on the airway epithelial barrier. In this study, we sought to determine the effect of diesel exhaust exposure on airway epithelial barrier function and composition using in vitro and in vivo model systems.

METHODS

16HBE14o- human bronchial epithelial cells were grown on collagen coated Transwell inserts and exposed to 5 to 50 μg/cm2 SRM 2975 diesel particulate matter (DEP) suspended in cell culture medium or vehicle controls. Changes in barrier function were assessed by measuring transepithelial electrical resistance (TEER) and permeability to 4 kDa FITC Dextran. Neonatal BALB/c mice were exposed to aerosolized DEP (255 ± 89 μg/m3; 2 h per day for 5 days) and changes in the tight junction protein Tricellulin were assessed 2 weeks post exposure.

RESULTS

A six-hour incubation of epithelial cells with diesel exhaust particles caused a significant concentration-dependent reduction in epithelial barrier integrity as measured by decreased TEER and increased permeability to 4 kDa FITC-Dextran. This reduction in epithelial barrier integrity corresponded to a significant reduction in expression of the tight junction protein Tricellulin. siRNA mediated knockdown of Tricellulin recapitulated changes in barrier function caused by DEP exposure. Neonatal exposure to aerosolized DEP caused a significant reduction in lung Tricellulin 2 weeks post exposure at both the protein and mRNA level.

CONCLUSION

Short term exposure to DEP causes a significant reduction in epithelial barrier integrity through a reduction in the tight junction protein Tricellulin. Neonatal exposure to aerosolized DEP caused a significant and sustained reduction in Tricellulin protein and mRNA in the lung, suggesting that early life exposure to inhaled DEP may cause lasting changes in airway epithelial barrier function.

Residence proximity to traffic-related facilities is associated with childhood asthma and rhinitis in Shandong, China

Associations of asthma and rhinitis with residential traffic proximity were investigated in several studies, but conclusions were inconsistent. From January to April in 2015, a cross-sectional study was conducted in two cities of Shandong, China. Parents-reported questionnaires were collected from 69 kindergartens for 3-6-year-olds preschoolers. Here we investigated associations of four traffic-related facilities (main traffic road, automobile 4S shop, filling station, and ground car park) close to residence with childhood asthma and rhinitis under considering individual and residential characteristics. In the two-level (kindergarten-child) mixed-effect logistic regression analyses among 5640 children who did not change residences since birth, filling station close to residence within 100 m (reference: >200 m) was significantly associated with lifetime-ever asthma (adjusted odds ratio, 95% confidence interval: 2.63, 1.28-5.40), wheeze (2.06, 1.35-3.15), rhinitis (1.69, 1.08-2.64) and current (past 12 months prior to the survey) wheeze (2.11, 1.34-3.34) and rhinitis (1.65, 1.05-2.59). Numbers of the facilities close to residence had dose-response relationships with odds of asthma, wheeze and rhinitis symptoms. These dose-response relationships were generally stronger in children whose bedrooms were in the 1st-3rd floors, and in children with low ventilation in bedroom and kitchen, and in children from families who did not using natural gas for cooking. The similar associations were found in the sensitive analyses among all surveyed 9597 children. Our results indicate that residence close to the traffic-related facilities likely is a risk factor for the occurrence of asthma and rhinitis among preschool children. The studied associations could be modified by household ventilation and air pollutants.

Observing Nitrogen Dioxide Air Pollution Inequality Using High-Spatial-Resolution Remote Sensing Measurements in Houston, Texas

Houston, Texas is a major U.S. urban and industrial area where poor air quality is unevenly distributed and a disproportionate share is located in low-income, non-white, and Hispanic neighborhoods. We have traditionally lacked city-wide observations to fully describe these spatial heterogeneities in Houston and in cities globally, especially for reactive gases like nitrogen dioxide (NO₂). Here, we analyze novel high-spatial-resolution (250 m × 500 m) NO₂ vertical columns measured by the NASA GCAS airborne spectrometer as part of the September-2013 NASA DISCOVER-AQ mission and discuss differences in population-weighted NO₂ at the census-tract level. Based on the average of 35 repeated flight circuits, we find 37 ± 6% higher NO₂ for non-whites and Hispanics living in low-income tracts (LIN) compared to whites living in high-income tracts (HIW) and report NO₂ disparities separately by race ethnicity (11-32%) and poverty status (15-28%). We observe substantial time-of-day and day-to-day variability in LIN-HIW NO₂ differences (and in other metrics) driven by the greater prevalence of NO_x (≡NO + NO₂) emission sources in low-income, non-white, and Hispanic neighborhoods. We evaluate measurements from the recently launched satellite sensor TROPOMI (3.5 km × 7 km at nadir), averaged to 0.01° × 0.01° using physics-based oversampling, and demonstrate that TROPOMI resolves similar relative, but not absolute, tract-level differences compared to GCAS. We utilize the high-resolution FIVE and NEI NO_x inventories, plus one year of TROPOMI weekday-weekend variability, to attribute tract-level NO₂ disparities to industrial sources and heavy-duty diesel trucking. We show that GCAS and TROPOMI spatial patterns correspond to the surface patterns measured using aircraft profiling and surface monitors. We discuss opportunities for satellite remote sensing to inform decision making in cities generally.

Effect of Lockdown Measures on Atmospheric Nitrogen Dioxide during SARS-CoV-2 in Spain

The disease caused by SARS-CoV-2 has affected many countries and regions. In order to contain the spread of infection, many countries have adopted lockdown measures. As a result, SARS-CoV-2 has negatively influenced economies on a global scale and has caused a significant impact on the environment. In this study, changes in the concentration of the pollutant Nitrogen Dioxide (NO2) within the lockdown period were examined as well as how these changes relate to the Spanish population. NO2 is one of the reactive nitrogen oxides gases resulting from both anthropogenic and natural processes. One major source in urban areas is the combustion of fossil fuels from vehicles and industrial plants, both of which significantly contribute to air pollution. The long-term exposure to NO2 can also cause severe health problems. Remote sensing is a useful tool to analyze spatial variability of air quality. For this purpose, Sentinel-5P images registered from January to April of 2019 and 2020 were used to analyze spatial distribution of NO2 and its evolution under the lockdown measures in Spain. The results indicate a significant correlation between the population’s activity level and the reduction of NO2 values.

Exposure Measurement Error in Air Pollution Studies: The Impact of Shared, Multiplicative Measurement Error on Epidemiological Health Risk Estimates

Spatiotemporal air pollution models are increasingly being used to estimate health effects in epidemiological studies. Although such exposure prediction models typically result in improved spatial and temporal resolution of air pollution predictions, they remain subject to shared measurement error, a type of measurement error common in spatiotemporal exposure models which occurs when measurement error is not independent of exposures. A fundamental challenge of exposure measurement error in air pollution assessment is the strong correlation and sometimes identical (shared) error of exposure estimates across geographic space and time. When exposure estimates with shared measurement error are used to estimate health risk in epidemiological analyses, complex errors are potentially introduced, resulting in biased epidemiological conclusions. We demonstrate the influence of using a three-stage spatiotemporal exposure prediction model and introduce formal methods of shared, multiplicative measurement error (SMME) correction of epidemiological health risk estimates. Using our three-stage, ensemble learning based nitrogen oxides (NOx) exposure prediction model, we quantified SMME. We conducted an epidemiological analysis of wheeze risk in relation to NOx exposure among school-aged children. To demonstrate the incremental influence of exposure modeling stage, we iteratively estimated the health risk using assigned exposure predictions from each stage of the NOx model. We then determined the impact of SMME on the variance of the health risk estimates under various scenarios. Depending on the stage of the spatiotemporal exposure model used, we found that wheeze odds ratio ranged from 1.16 to 1.28 for an interquartile range increase in NOx. With each additional stage of exposure modeling, the health effect estimate moved further away from the null (OR=1). When corrected for observed SMME, the health effects confidence intervals slightly lengthened, but our epidemiological conclusions were not altered. When the variance estimate was corrected for the potential "worst case scenario" of SMME, the standard error further increased, having a meaningful influence on epidemiological conclusions. Our framework can be expanded and used to understand the implications of using exposure predictions subject to shared measurement error in future health investigations.

Urban Form, Air Quality, and Cardiorespiratory Mortality: A Path Analysis

With the unprecedented urbanization during the past three decades, air quality in many Chinese cities has been a serious issue which poses great challenges for urban sustainability. This study examines the health consequences of development patterns in China by establishing the linkage between urban form, air pollution level, and cardiorespiratory mortality rate. We assembled a dataset by compiling a series of variables from multiple sources, including China's Disease Surveillance Points (DSP) system, which forms a nationally representative sample of mortality for the year 2005, Chinese census, satellite imagery, and the Chinese National Land Use Database. After controlling for local climate, demography, socioeconomics, and other pollution factors, this study finds that urban form elements (e.g., urban density, fragmentation level, forest/green space ratio) have significant influences on PM_2.5 (atmospheric particulate matter with a diameter of less than 2.5 micrometers) concentration, thus influencing the incidence of cardiorespiratory mortality at the county level. These results may help explain how the type and pattern of development shape public health by influencing air quality and form an evidence-based land use policy to improve environmental quality and public health.

Proximity to major roadways and asthma symptoms in the School Inner-City Asthma Study

BACKGROUND

Traffic proximity has been associated with adverse respiratory health outcomes. Less is known about the combined impact of residential and school exposures on pediatric asthma.

OBJECTIVE

We sought to use spatial analysis methodology to analyze residential and school proximity to major roadways and pediatric asthma morbidity.

METHODS

The School Inner-City Asthma Study (n = 350) recruited school-aged children with asthma. Each participant's school and home addresses were geocoded, and distances from major roadways were measured to calculate a composite measure accounting for both home and school traffic exposure. Generalized estimating equation models were clustered by subject and adjusted for age, race/ethnicity, sex, income, environmental tobacco smoke, controller medication, upper respiratory tract infections, and seasonality.

RESULTS

The majority of participants (62%) attended schools within 100 m from major roadways, and 40% also resided within 100 m of major roadways. In multivariate analyses major roadway proximity was independently associated with increased asthma symptom days. At greater than the threshold of 100 m, children had 29% less odds of a symptom day over the past 2 weeks for each 100-m increase in distance from a major roadway (odds ratio, 0.71; 95% CI, 0.58-0.87; P < .01). Children farther from a major roadway also had significantly less reported health care use (odds ratio, 0.63; 95% CI, 0.47-0.85; P < .01) and were significantly less likely to have poor asthma control (odds ratio, 0.80; 95% CI, 0.69-0.94; P < .01). There was not a meaningful association between distance to a major roadway and lung function outcomes.

CONCLUSIONS

Proximity to a major roadway, a composite measure of home and school exposure but primarily driven by home exposure, was associated with greater asthma morbidity. More studies are needed to evaluate the independent effect of school distance to a roadway on asthma morbidity.

Air pollution, noise exposure, and metabolic syndrome - A cohort study in elderly Mexican-Americans in Sacramento area

BACKGROUND

Previous studies suggested that air pollutants may increase the incidence of metabolic syndrome, but the potential impact from traffic sources is not well-understood. This study aimed to investigate associations between traffic-related nitrogen oxides (NOx) or noise pollution and risk of incident metabolic syndrome and its components in an elderly Mexican-American population.

METHODS

A total of 1,554 Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) cohort were followed from 1998 to 2007. We used anthropometric measures and biomarkers to define metabolic syndrome according to the recommendations of the Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP ATP III). Based on participants' residential addresses at baseline, estimates of local traffic-related NOx were generated using the California Line Source Dispersion Model version 4 (CALINE4), and of noise employing the SoundPLAN software package. We used Cox regression models with calendar time as the underlying time scale to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of air pollution or noise with metabolic syndrome or its components.

RESULTS

Each per unit increase of traffic-related NOx (2.29 parts per billion (ppb)) was associated with a 15% (HR = 1.15, 95% CI: 1.04-1.28) lower level of high-density lipoprotein cholesterol (HDL-cholesterol), and each 11.6 decibels (dB) increase in noise increased the risk of developing metabolic syndrome by 17% (HR = 1.17, 95% CI: 1.01-1.35).

CONCLUSION

Policies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

The impact of air pollutants on ambulance dispatches: A systematic review and meta-analysis of acute effects

A number of systematic reviews have investigated the association between air pollutants and health impacts, these mostly focus on morbidity and mortality from hospital data. Previously, no reviews focused solely on ambulance dispatch data. These data sets have excellent potential for environmental health research. For this review, publications up to April 2019 were identified using three main search categories covering: ambulance services including dispatches; air pollutants; and health outcomes. From 308 studies initially identified, 275 were excluded as they did not relate to ambulance service dispatches, did not report the air pollutant association, and/or did not study ambient air pollution. The main health outcomes in the remaining 33 studies were cardiac arrest (n = 14), cardiovascular (n = 11) and respiratory (n = 10) dispatches. Meta-analyses were performed to summarise pooled relative risk (RR) of pollutants: particulate matter less than 2.5 and 10 μm (PM_2.5, PM₁₀), the fraction between PM₁₀ and PM_2.5 (coarse) and suspended particulate matter (SPM) per 10 μg/m³ increase, carbon monoxide (CO) per 1 ppm increase and of sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) per 10 ppb increment and ambulance dispatches. Statistically significant associations were found for ambulance dispatch data for all-respiratory and PM_2.5 at 1.03 (95% CI:1.02-1.04) and at 1.10 (95% CI:1.00-1.21) for asthma and NO₂ associations. For dispatches with subsequent paramedic assessment for cardiac arrest with PM_2.5, CO and coarse dispatches at 1.05 (95% CI:1.03-1.08), 1.10 (95% CI:1.02-1.18) and 1.04 (95% CI:1.01-1.06) respectively. For dispatches with subsequent physician diagnosis for all-respiratory and PM_2.5 at 1.02 (95% CI:1.01-1.03). In conclusion, air pollution was significantly associated with an increase in ambulance dispatch data, including those for cardiac arrest, all-respiratory, and asthma dispatches. Ambulance services should plan accordingly during pollution events. Furthermore, efforts to improve air quality should lead to decreases in ambulance dispatches.

National NO2 exposure models for measuring its impact on vulnerable people in the US metropolitan areas

Epidemiological research requires accurate prediction of the concentrations of air pollutants. In this study, satellite-based estimates (OMI NO₂), distance-weighted models (DWMs), and universal kriging (UK) are applied to land use regression (LUR) to predict annually and monthly averaged NO₂ concentrations in the continental United States. In addition, to assess environmental risk, the relationship between NO₂ concentrations and people potentially exposed to NO₂ within urban areas is explored in 377 metropolitan statistical areas (MSAs). The results of this study show that the application of a combination of OMI NO₂, UK, and DWMs to LUR yielded the highest cross-validated (CV) R² values and the lowest root mean square error of prediction (RMSEP): 82.9% and 0.392 on a square root scale of ppb in the annual model and 70.4-83.5% and 0.408-0.518 on square root scale of ppb in the monthly models, respectively. Moreover, the model presented a spatially unbiased distribution of CV error terms. Models based on LUR provided more accurate NO₂ predictions with lower RMSEP in urban areas than in rural areas. In addition, this study finds that the people living in the urban areas of MSAs, with larger populations and a higher percentage of children under 18 years of age, are likely to be exposed to higher NO₂ concentrations. By contrast, people living in the urban areas of MSAs with a higher percentage of the elderly over 65 years of age are likely to be exposed to lower NO₂ concentrations.

Exploring the effects of ventilation practices in mitigating in-vehicle exposure to traffic-related air pollutants in China

In most major cities of China, commuters inevitably spend a considerable amount of time in vehicle cabins due to the escalation of traffic congestion and a rapidly increasing vehicle population. The in-vehicle microenvironment that is in close proximity to traffic emission sources is at particular risk of increased exposure to traffic-related air pollutants (TRAPs). In this study, a mobile measurement campaign was carried out to investigate in-vehicle exposure to TRAPs in China where the elevated level of TRAPs has drawn worldwide attention in recent years. Our analysis demonstrates that vehicle ventilation mode (i.e., mechanical ventilation, natural ventilation, hybrid ventilation, and infiltration) played a critical role in determining the level of in-vehicle exposure. Although the outside air (OA) mode of mechanical ventilation provided adequate air exchange to passengers, the average in-vehicle PM_2.5 and UFP concentrations (119 μg/m³ and 97,227 cm^-3 on freeway, and 93 μg/m³ and 42,829 cm^-3 on local roadway) during a 20-min sampling period were observed at the level that are markedly greater than those from studies conducted in the U.S., posing a serious health threat to vehicle occupants. We elaborated how our results collected in China with a significantly more polluted on-road environment differ from existing studies in terms of ventilation and driving conditions. In addition, we made the first effort to examine in-vehicle exposure under hybrid ventilation that is a common ventilation practice in everyday commute to potentially reduce symptoms similar to sick building syndrome (SBS). Our data indicate that vehicle occupants under hybrid ventilation are at much greater risk of TRAPs exposure if operating in a polluted on-road environment, and we call for future research on automated ventilation system with advanced window control especially for vans and buses with a large cabin volume.

Study Design, Protocol and Profile of the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) Pregnancy Cohort: a Prospective Cohort Study in Predominantly Low-Income Hispanic Women in Urban Los Angeles

BACKGROUND

The burden of childhood and adult obesity disproportionally affects Hispanic and African-American populations in the US, and these groups as well as populations with lower income and education levels are disproportionately affected by environmental pollution. Pregnancy is a critical developmental period where maternal exposures may have significant impacts on infant and childhood growth as well as the future health of the mother. We initiated the "Maternal And Developmental Risks from Environmental and Social Stressors (MADRES)" cohort study to address critical gaps in understanding the increased risk for childhood obesity and maternal obesity outcomes among minority and low-income women in urban Los Angeles.

METHODS

The MADRES cohort is specifically examining whether pre- and postpartum environmental exposures, in addition to exposures to psychosocial and built environment stressors, lead to excessive gestational weight gain and postpartum weight retention in women and to perturbed infant growth trajectories and increased childhood obesity risk through altered psychological, behavioral and/or metabolic responses. The ongoing MADRES study is a prospective pregnancy cohort of 1000 predominantly lower-income, Hispanic women in Los Angeles, CA. Enrollment in the MADRES cohort is initiated prior to 30 weeks gestation from partner community health clinics in Los Angeles. Cohort participants are followed through their pregnancies, at birth, and during the infant's first year of life through a series of in-person visits with interviewer-administered questionnaires, anthropometric measurements and biospecimen collection as well as telephone interviews conducted with the mother.

DISCUSSION

In this paper, we outline the study rationale and data collection protocol for the MADRES cohort, and we present a profile of demographic, health and exposure characteristics for 291 participants who have delivered their infants, out of 523 participants enrolled in the study from November 2015 to October 2018 from four community health clinics in Los Angeles. Results from the MADRES cohort could provide a powerful rationale for regulation of targeted chemical environmental components, better transportation and urban design policies, and clinical recommendations for stress-coping strategies and behavior to reduce lifelong obesity risk.

Fine-scale spatial structure of air pollutant concentrations along bus routes

Air pollution measurements were made at 5 s intervals along a bus route in Hong Kong, chosen to avoid frequent intersections or traffic jams. This allowed periodic pollutant concentration patterns in bus-derived pollutants to be explored using Fourier analysis. The analysis showed the defining role of the bus stops in terms of NO_X and PM_2.5 concentrations, which have profiles with a sawtooth form. Early in inter-stop segments, concentrations are high, followed by a decline. This arises from high emissions during the acceleration away from the bus stop, then lower emissions during cruise and de-acceleration. This pattern can be enhanced on sections of the route where buses are frequent as pollutants accumulate from the larger number of buses. The high concentrations just beyond bus stops may have implications for planning bus routes and the positioning of bus stops.

Childhood respiratory allergies and symptoms in highly polluted area of Central Europe

The study investigated the associations between the prevalence of the childhood respiratory diseases and the long-term exposure to air pollution in the burdened area of Moravian-Silesian Region in the Czech Republic. The health data were collected during 2014 in 7,239 children 5, 9, 13 and 17 years of age. Exposure to PM₁₀ and NO₂ in the residence addresses was based on dispersion models and GIS based traffic-related indicators. PM₁₀ levels were positively associated with both lifetime (OR 1.35; 95%CI 1.09-1.67) and current (OR 1.32; 95%CI 1.05-1.67) allergic rhinitis; current asthma was associated negatively. The associations between traffic indicator and respiratory health were not found. On the other hand, marked positive associations were found between the respiratory diseases and symptom severity structured into ordinal variables, and PM₁₀ and NO₂. Modelled long-term exposure to air pollution was associated with childhood allergic rhinitis and deterioration of the respiratory symptoms.

Regional and traffic-related air pollutants are associated with higher consumption of fast food and trans fat among adolescents

Background

Air pollution exposures are novel contributors to the growing childhood obesity epidemic. One possible mechanism linking air pollution exposures and obesity is through changes in food consumption patterns.

Objective

The aim of this study was to examine the longitudinal association between childhood exposure to air pollutants and changes in diet among adolescents.

Design

School-age children were enrolled in the Southern California Children's Health Study during 1993-1994 (n = 3100) and were followed for 4-8 y. Community-level regional air pollutants [e.g., nitrogen dioxide (NO2), elemental carbon (EC), and fine particles with aerodynamic diameter <2.5 µm (PM2.5)] were measured at central monitoring stations. Line dispersion modeling was used to estimate concentrations of traffic-related air pollutants based on nitrogen oxides (NOx) at participants' residential addresses. In addition, self-reported diet information was collected annually using a structured youth/adolescent food-frequency questionnaire during 1997-2001. Generalized linear mixed-effects models were used in the association analyses.

Results

Higher exposures to regional and traffic-related air pollutants were associated with intake of a high-trans-fat diet, after adjusting for confounders including socioeconomic status and access to fast food in the community. A 2-SD (12.2 parts per billion) increase in regional NO2 exposure was associated with a 34% increased risk of consuming a high-trans-fat diet compared with a low-trans-fat diet (OR: 1.34; 95% CI: 1.05, 1.72). In addition, higher exposures to acid vapor, EC, PM2.5, and non-freeway NOx were all associated with higher consumption of dietary trans fat (all P < 0.04). Notably, higher exposures to regional NO2, acid vapor, and EC were also associated with a higher consumption of fast food (all P < 0.05).

Conclusions

Childhood exposures to regional and traffic-related air pollutants were associated with increased consumption by adolescents of trans fat and fast foods. Our results indicate that air pollution exposures may contribute to obesogenic behaviors. This study was registered at clinicaltrials.gov as NCT03379298.

The effect of short-term particular matter2.5 exposure on asthma attacks in asthma children in Fukuoka, Japan

We investigated whether asthma attacks in asthmatic children were caused by short-term exposure to particulate matter(PM)2.5. Methods Subjects were 411 patients who received inhalation therapy in National Fukuoka Hospital, from March to May 2013. All subjects were outpatients. We surveyed the air quality measurement results in the stations closest to the address of the patients. Data were used from the City of Fukuoka website data on air pollution. We carried out a case-crossover study and compared PM2.5 concentration between 7 days after asthma attack occurred and the day asthma attack occurred and 1, 2 and 3 days before asthma attack occurred. Results Highest hourly concentration of the day (OR 1.013, 95%CI 1.000-1.025) showed a significant association with 1 day before PM2.5 concentration statistically. And 0-1 year-old infants were more vulnerable to the highest concentration of 1 day before PM2.5 concentration(P &lt; 0.05). Average concentration of NO2 and O3 and asthma attack also showed a significant association. Conclusions Maximal daily PM2.5 concentrations within 24 hours prior to the attack affect asthma exacerbation. 0-1 year-old infants are particularly vulnerable to PM2.5 concentration. Asthma exacerbation is aggravated by NO2 and O3 concentration on the day of the asthma attack.

The Exposome and Asthma

This article on exposome and asthma focuses on the interaction of patients and their environments in various parts of their growth, development, and stages of life. Indoor and outdoor environments play a role in pathogenesis via levels and duration of exposure, with genetic susceptibility as a crucial factor that alters the initiation and trajectory of common conditions such as asthma. Knowledge of environmental exposures globally and changes that are occurring is necessary to function effectively as medical professionals and health advocates.

Road proximity influences indoor exposures to ambient fine particle mass and components

Exposure to traffic-related PM_2.5 mass and its components can affect human health. Meanwhile, indoor concentrations are better exposure predictors as compared to outdoor concentrations because individuals spend the majority of their time indoors. We estimated the impact of traffic emissions on indoor PM_2.5 mass and its species as a function of road proximity in Massachusetts. A linear regression model was built using 662 indoor samples and 580 ambient samples. Analysis shows that indoor exposures to traffic-related particles increased dramatically with road proximity. We defined relative concentration decrease, R(α), as the ratio of the indoor concentration at perpendicular distance α in meters from the closest major road to the indoor concentration at 1800 m from the major road. R(13) values for PM_2.5 mass and Black Carbon (BC) were 1.3 (95%CI: 1.4, 1.6) and 2.1 (95%CI: 1.3, 2.8) for A12 roads, and 1.3 (95%CI: 1.2, 1.4) and 1.2 (95%CI: 1.1, 1.3) for A3 roads. R(α) values were also estimated for Fe, Mn, Mo, Sr and Ti for A12 roads, and Ca, Cu, Fe, Mn, Mo, Ni, Si, Sr, V and Zn for A3 roads. R(α) values for species associated mainly with brakes, tires or road dust (e.g., Mn, Mo and Sr) were higher than others. For A12 roads, R(13) values for Mn and Mo were 10.9 (95%CI: 0.9, 20.9) and 6.5 (95%CI: 1.4, 11.5), and ranged from 1.3 to 2.1 for other species; for A3 roads, R(13) values for Mn, Mo and Sr were 1.9 (95%CI: 1.1, 2.9), 1.8 (95%CI: 1.1, 2.4), and 8.5 (95%CI: 5.9, 10.9), and ranged from 1.2 to 1.6 for others. Our results indicate a significant impact of local traffic emissions on indoor air, which depends on road proximity. Thus road proximity which has been used in many epidemiological studies is a reasonable exposure metric.