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Material design is increasingly used to realize desired functional properties, and the perovskite structure family is one of the richest and most diverse: perovskites are employed in many applications due to their structural flexibility and compositional diversity. Hexagonal, layered perovskite structures with chains of face-sharing transition metal oxide octahedra have attracted great interest as quantum materials due to their magnetic and electronic properties. Ba4MMn3O12, a member of the "12R" class of hexagonal, layered perovskites, contains trimers of face-sharing MnO6 octahedra that are linked by a corner-sharing, bridging MO6 octahedron. Here, we investigate cluster magnetism in the Mn3O12 trimers and the role of this bridging octahedron on the magnetic properties of two isostructural 12R materials by systematically changing the M4+ cation from nonmagnetic Ce4+ (f0) to magnetic Pr4+ (f1). We synthesized 12R-Ba4MMn3O12 (M= Ce, Pr) with high phase purity and characterized their low-temperature crystal structures and magnetic properties. Using substantially higher purity samples than previously reported, we confirm the frustrated antiferromagnetic ground state of 12R-Ba4PrMn3O12 below TN ≈ 7.75 K and explore the cluster magnetism of its Mn3O12 trimers. Despite being atomically isostructural with 12R-Ba4CeMn3O12, the f1 electron associated with Pr4+ causes much more complex magnetic properties in 12R-Ba4PrMn3O12. In 12R-Ba4PrMn3O12, we observe a sharp, likely antiferromagnetic transition at T2 ≈ 12.15 K and an additional transition at T1 ≈ 200 K, likely in canted antiferromagnetic order. These results suggest that careful variation of composition within the family of hexagonal, layered perovskites can be used to tune material properties using the complex role of the Pr4+ ion in magnetism.
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With the growing climate change crisis, public health agencies and practitioners must increasingly develop guidance documents addressing the public health risks and protective measures associated with multi-hazard events. Our Policy and Practice Review aims to assess current public health guidance and related messaging about co-exposure to wildfire smoke and extreme heat and recommend strengthened messaging to better protect people from these climate-sensitive hazards. We reviewed public health messaging published by governmental agencies between January 2013 and May 2023 in Canada and the United States. Publicly available resources were eligible if they discussed the co-occurrence of wildfire smoke and extreme heat and mentioned personal interventions (protective measures) to prevent exposure to either hazard. We reviewed local, regional, and national governmental agency messaging resources, such as online fact sheets and guidance documents. We assessed these resources according to four public health messaging themes, including (1) discussions around vulnerable groups and risk factors, (2) symptoms associated with these exposures, (3) health risks of each exposure individually, and (4) health risks from combined exposure. Additionally, we conducted a detailed assessment of current messaging about measures to mitigate exposure. We found 15 online public-facing resources that provided health messaging about co-exposure; however, only one discussed all four themes. We identified 21 distinct protective measures mentioned across the 15 resources. There is considerable variability and inconsistency regarding the types and level of detail across described protective measures. Of the identified 21 protective measures, nine may protect against both hazards simultaneously, suggesting opportunities to emphasize these particular messages to address both hazards together. More precise, complete, and coordinated public health messaging would protect against climate-sensitive health outcomes attributable to wildfire smoke and extreme heat co-exposures.
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Calor Extremo , Incendios Forestales , Humanos , Estados Unidos , Humo/efectos adversos , Cambio Climático , Salud Pública , Exposición a Riesgos Ambientales/efectos adversos , NicotianaRESUMEN
[This corrects the article DOI: 10.1021/acsomega.3c02630.].
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BACKGROUND: Preterm birth (PTB), defined as birth before 37 wk gestation, is associated with hypertension, diabetes, inadequate prenatal care, unemployment or poverty, and metal exposure. Indigenous individuals are more likely to have maternal risk factors associated with PTB compared with other populations in the United States; however, the role of environmental metals on PTB among pregnant Indigenous women remains uncertain. Previous research identified associations between PTB and individual metals, but there is limited investigation on metal mixtures and this birth outcome. OBJECTIVES: We used a mixtures analysis framework to investigate the association between metal mixtures and PTB among pregnant Indigenous women from the Navajo Birth Cohort Study (NBCS). METHODS: Maternal urine and blood samples were collected at the time of study enrollment and analyzed for metals by inductively coupled plasma dynamic reaction cell mass spectrometry. Bayesian Profile Regression was used to identify subgroups (clusters) of individuals with similar patterns of coexposure and to model association with PTB. RESULTS: Results indicated six subgroups of maternal participants with distinct exposure profiles, including one group with low exposure to all metals and one group with total arsenic, cadmium, lead, and uranium concentrations exceeding representative concentrations calculated from the National Health and Nutrition Examination Survey (NHANES). Compared with the reference group (i.e., the lowest exposure subgroup), the subgroup with the highest overall exposure had a relative risk of PTB of 2.9 times (95% credible interval: 1.1, 6.1). Exposures in this subgroup were also higher overall than NHANES median values for women 14-45 years of age. DISCUSSION: Given the wide range of exposures and elevated PTB risk for the most exposed subgroups in a relatively small study, follow-up investigation is recommended to evaluate associations between metal mixture profiles and other birth outcomes and to test hypothesized mechanisms of action for PTB and oxidative stress caused by environmental metals. https://doi.org/10.1289/EHP10361.
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Nacimiento Prematuro , Uranio , Recién Nacido , Humanos , Femenino , Embarazo , Mujeres Embarazadas , Encuestas Nutricionales , Teorema de Bayes , Estudios de Cohortes , Nacimiento Prematuro/inducido químicamente , Nacimiento Prematuro/epidemiologíaRESUMEN
Continued dependence on crude oil and natural gas resources for fossil fuels has caused global atmospheric carbon dioxide (CO2) emissions to increase to record-setting proportions. There is an urgent need for efficient and inexpensive carbon sequestration systems to mitigate large-scale emissions of CO2 from industrial flue gas. Carbonic anhydrase (CA) has shown high potential for enhanced CO2 capture applications compared to conventional absorption-based methods currently utilized in various industrial settings. This study aims to understand structural aspects that contribute to the stability of CA enzymes critical for their applications in industrial processes, which require the ability to withstand conditions different from those in their native environments. Here, we evaluated the thermostability and enzyme activity of mesophilic and thermophilic CA variants at different temperature conditions and in the presence of atmospheric gas pollutants like nitrogen oxides and sulfur oxides. Based on our enzyme activity assays and molecular dynamics simulations, we see increased conformational stability and CA activity levels in thermostable CA variants incubated week-long at different temperature conditions. The thermostable CA variants also retained high levels of CA activity despite changes in solution pH due to increasing NO and SO2 concentrations. A loss of CA activity was observed only at high concentrations of NO/SO2 that possibly can be minimized with the appropriate buffered solutions.
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Owing to their uniform and tunable particle size, pore size, and shape, along with their modular surface chemistry and biocompatibility, mesoporous silica nanoparticles (MSNs) have found extensive applications as nanocarriers to deliver therapeutic, diagnostic and combined "theranostic" cargos to cells and tissues. Although thoroughly investigated, MSN have garnered FDA approval for only one MSN system via oral administration. One possible reason is that there is no recognized, reproducible, and widely adopted MSN synthetic protocol, meaning not all MSNs are created equal in the laboratory nor in the eyes of the FDA. This manuscript provides the sol-gel and MSN research communities a reproducible, fully characterized synthetic protocol to synthesize MSNs and corresponding lipid-coated MSN delivery vehicles with predetermined particle size, pore size, and drug loading and release characteristics. By carefully articulating the step-by-step synthetic procedures and highlighting critical points and troubleshooting, augmented with videos and schematics, this Article will help researchers entering this rapidly expanding field to yield reliable results.
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Nanomedicina , Nanopartículas , ARN Interferente Pequeño , ARN Mensajero , LípidosRESUMEN
The resurgence of inter-est in hydrogen-related technologies has stimulated new studies aimed at advancing lesser-developed water-splitting processes, such as solar thermochemical hydrogen production (STCH). Progress in STCH has been largely hindered by a lack of new materials able to efficiently split water at a rate comparable to ceria under identical experimental conditions. BaCe0.25Mn0.75O3 (BCM) recently demonstrated enhanced hydrogen production over ceria and has the potential to further our understanding of two-step thermochemical cycles. A significant feature of the 12R hexa-gonal perovskite structure of BCM is the tendency to, in part, form a 6H polytype at high temperatures and reducing environments (i.e., during the first step of the thermochemical cycle), which may serve to mitigate degradation of the complex oxide. An analogous compound, namely BaNb0.25Mn0.75O3 (BNM) with a 12R structure was synthesized and displays nearly complete conversion to the 6H structure under identical reaction conditions as BCM. The structure of the BNM-6H polytype was determined from Rietveld refinement of synchrotron powder X-ray diffraction data and is presented within the context of the previously established BCM-6H structure.
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Implications: Non-tailpipe emissions driven by springtime road dust in northern latitude communities is increasing in importance for air pollution control and improving our understanding of the health effects of chemical mixtures from particulate matter exposure. High-volume samples from a near-road site indicated that days affected by springtime road dust are substantively different from other days with respect to particulate matter mixture composition and meteorological drivers. The high load of trace elements in PM10 on high road dust days has important implications for the acute toxicity of inhaled air and subsequent health effects. The complex relationships between road dust and weather identified in this study may facilitate further research on the health effects of chemical mixtures related to road dust while also highlighting potential changes in this unique form of air pollution as the climate changes.
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Contaminantes Atmosféricos , Contaminación del Aire , Polvo/análisis , Contaminantes Atmosféricos/análisis , Colombia Británica , Monitoreo del Ambiente/métodos , Contaminación del Aire/análisis , Material Particulado/análisis , Emisiones de Vehículos/análisisRESUMEN
Many countries, including Italy, have experienced significant social and spatial inequalities in mortality during the Covid-19 pandemic. This study applies a multiple exposures framework to investigate how joint place-based factors influence spatial inequalities of excess mortality during the first year of the Covid -19 pandemic in the Lombardy region of Italy. For the Lombardy region, we integrated municipality-level data on all-cause mortality between 2015 and 2020 with 13 spatial covariates, including 5-year average concentrations of six air pollutants, the average temperature in 2020, and multiple socio-demographic factors, and health facilities per capita. Using the clustering algorithm Bayesian profile regression, we fit spatial covariates jointly to identify clusters of municipalities with similar exposure profiles and estimated associations between clusters and excess mortality in 2020. Cluster analysis resulted in 13 clusters. Controlling for spatial autocorrelation of excess mortality and health-protective agency, two clusters had significantly elevated excess mortality than the rest of Lombardy. Municipalities in these highest-risk clusters are in Bergamo, Brescia, and Cremona provinces. The highest risk cluster (C11) had the highest long-term particulate matter air pollution levels (PM2.5 and PM10) and significantly elevated NO2 and CO air pollutants, temperature, proportion ≤18 years, and male-to-female ratio. This cluster is significantly lower for income and ≥65 years. The other high-risk cluster, Cluster 10 (C10), is elevated significantly for ozone but significantly lower for other air pollutants. Covariates with elevated levels for C10 include proportion 65 years or older and a male-to-female ratio. Cluster 10 is significantly lower for income, temperature, per capita health facilities, ≤18 years, and population density. Our results suggest that joint built, natural, and socio-demographic factors influenced spatial inequalities of excess mortality in Lombardy in 2020. Studies must apply a multiple exposures framework to guide policy decisions addressing the complex and multi-dimensional nature of spatial inequalities of Covid-19-related mortality.
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Contaminantes Atmosféricos , Contaminación del Aire , COVID-19 , Masculino , Femenino , Humanos , Pandemias , Teorema de Bayes , Contaminación del Aire/análisis , Exposición a Riesgos Ambientales/análisis , Contaminantes Atmosféricos/toxicidad , Contaminantes Atmosféricos/análisis , Material Particulado/análisis , MortalidadRESUMEN
Wastewater-based epidemiology (WBE) has emerged as a valuable epidemiologic tool to detect the presence of pathogens and track disease trends within a community. WBE overcomes some limitations of traditional clinical disease surveillance as it uses pooled samples from the entire community, irrespective of health-seeking behaviors and symptomatic status of infected individuals. WBE has the potential to estimate the number of infections within a community by using a mass balance equation, however, it has yet to be assessed for accuracy. We hypothesized that the mass balance equation-based approach using measured SARS-CoV-2 wastewater concentrations can generate accurate prevalence estimates of COVID-19 within a community. This study encompassed wastewater sampling over a 53-week period during the COVID-19 pandemic in Gainesville, Florida, to assess the ability of the mass balance equation to generate accurate COVID-19 prevalence estimates. The SARS-CoV-2 wastewater concentration showed a significant linear association (Parameter estimate = 39.43, P value < 0.0001) with clinically reported COVID-19 cases. Overall, the mass balance equation produced accurate COVID-19 prevalence estimates with a median absolute error of 1.28%, as compared to the clinical reference group. Therefore, the mass balance equation applied to WBE is an effective tool for generating accurate community-level prevalence estimates of COVID-19 to improve community surveillance.
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COVID-19 , Monitoreo Epidemiológico Basado en Aguas Residuales , Humanos , COVID-19/epidemiología , SARS-CoV-2 , Pandemias , Aguas Residuales , Prevalencia , ARN ViralRESUMEN
Height for age is an important and widely used population-level indicator of children's health. Morbidity trends show that stunting in young children is a significant public health concern. Recent studies point to environmental factors as an understudied area of child growth failure in Africa. Data on child measurements of height-for-age and confounders were obtained from fifteen waves of the Demographic and Health Surveys (DHS) for six countries in East Africa. Monthly ambient PM2.5 concentration data was retrieved from the Atmospheric Composition Analysis Group (ACAG) global surface PM2.5 estimates and spatially integrated with DHS data. Generalized additive models with linear and logistic regression were used to estimate the exposure-response relationship between prenatal PM2.5 and height-for-age and stunting among children under five in East Africa (EA). Fully adjusted models showed that for each 10 µg/m3 increase in PM2.5 concentration there is a 0.069 (CI: 0.097, 0.041) standard deviation decrease in height-for-age and 9% higher odds of being stunted. Our study identified ambient PM2.5 as an environmental risk factor for lower height-for-age among young children in EA. This underscores the need to address emissions of harmful air pollutants in EA as adverse health effects are attributable to ambient PM2.5 air pollution.
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BACKGROUND: Children with congenital heart defects have an increased risk of neurodevelopmental disability. The impact of environmental chemical exposures during daily life on neurodevelopmental outcomes in toddlers with congenital heart defects is unknown. METHODS: This prospective study investigated the impacts of early childhood exposure to mixtures of environmental chemicals on neurodevelopmental outcomes after cardiac surgery. Outcomes were assessed at 18 months of age using The Bayley Scales of Infant and Toddler Development-III. Urinary concentrations of exposure biomarkers of pesticides, phenols, parabens, and phthalates, and blood levels of lead, mercury, and nicotine were measured at the same time point. Bayesian profile regression and weighted quantile sum regression were utilized to assess associations between mixtures of biomarkers and neurodevelopmental scores. RESULTS: One-hundred and forty infants were enrolled, and 110 (79%) returned at 18 months of age. Six biomarker exposure clusters were identified from the Bayesian profile regression analysis; and the pattern was driven by 15 of the 30 biomarkers, most notably 13 phthalate biomarkers. Children in the highest exposure cluster had significantly lower adjusted language scores by -9.41 points (95%CI: -17.2, -1.7) and adjusted motor scores by -4.9 points (-9.5, -0.4) compared to the lowest exposure. Weighted quantile sum regression modeling for the overall exposure-response relationship showed a significantly lower adjusted motor score (ß = -2.8 points [2.5th and 97.5th percentile: -6.0, -0.6]). The weighted quantile sum regression index weights for several phthalates, one paraben, and one phenol suggest their relevance for poorer neurodevelopmental outcomes. CONCLUSIONS: Like other children, infants with congenital heart defects are exposed to complex mixtures of environmental chemicals in daily life. Higher exposure biomarker concentrations were associated with significantly worse performance for language and motor skills in this population.
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Cardiopatías Congénitas , Lactante , Humanos , Preescolar , Estudios Prospectivos , Teorema de Bayes , Cardiopatías Congénitas/inducido químicamente , Cardiopatías Congénitas/cirugía , Parabenos , Fenoles , BiomarcadoresRESUMEN
Additive manufacturing can enable the fabrication of batteries in nonconventional form factors, enabling higher practical energy density due to improved material packing efficiency of power sources in devices. Furthermore, energy density can be improved by transitioning from conventional Li-ion battery materials to lithium metal anodes and conversion cathodes. Iron disulfide (FeS2) is a prominent conversion cathode of commercial interest; however, the direct-ink-write (DIW) printing of FeS2 inks for custom-form battery applications has yet to be demonstrated or optimized. In this work, DIW printing of FeS2 inks is used to systematically investigate the impact of ink solid concentration on rheology, film shape retention on arbitrary surfaces, cathode morphology, and electrochemical cell performance. We find that cathodes with a ridged interface, produced from the filamentary extrusion of highly concentrated FeS2 inks (60-70% solids w/w%), exhibit optimal power, uniformity, and stability when cycled at higher rates (in excess of C/10). Meanwhile, cells with custom-form, wave-shaped electrodes (printed FeS2 cathodes and pressed lithium anodes) are demonstrated and shown to exhibit similar performance to comparable cells in planar configurations, demonstrating the feasibility of printing onto complex geometries. Overall, the DIW printing of FeS2 inks is shown to be a viable path toward the making of custom-form conversion lithium batteries. More broadly, ridging is found to optimize rate capability, a finding that may have a broad impact beyond FeS2 and syringe extrusion.
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BACKGROUND: Poor indoor air quality (IAQ) is a leading cause of respiratory and cardiopulmonary illnesses. Particulate matter (PM2.5) and carbon monoxide (CO) are critical indicators of IAQ, yet there is limited evidence of their concentrations in informal urban settlements in low-income countries. OBJECTIVE: This study assessed household characteristics that predict the concentrations of PM2.5 and CO within households in an informal settlement in Fort Portal City, Uganda. METHODOLOGY: A cross-sectional study was conducted in 374 households. Concentrations of PM2.5 and CO were measured using a multi-purpose laser particle detector and a carbon monoxide IAQ meter, respectively. Data on household characteristics were collected using a structured questionnaire and an observational checklist. Data were analysed using STATA version 14.0. Linear regression was used to establish the relationship between PM2.5, CO concentrations and household cooking characteristics. RESULTS: The majority (89%, 332/374) of the households used charcoal for cooking. More than half (52%, 194/374) cooked outdoors. Cooking areas had significantly higher PM2.5 and CO concentrations (t = 18.14, p ≤ 0.05) and (t = 5.77 p ≤ 0.05), respectively. Cooking outdoors was associated with a 0.112 increase in the PM2.5 concentrations in the cooking area (0.112 [95% CI: -0.069, 1.614; p = 0.033]). Cooking with moderately polluting fuel was associated with a 0.718 increase in CO concentrations (0.718 [95% CI: 0.084, 1.352; p = 0.027]) in the living area. CONCLUSIONS: The cooking and the living areas had high concentrations of PM2.5 and CO during the cooking time. Cooking with charcoal resulted in higher CO in the living area. Furthermore, cooking outdoors did not have a protective effect against PM2.5, and ambient PM2.5 exceeded the WHO Air quality limits. Interventions to improve the indoor air quality in informal settlements should promote a switch to cleaner cooking energy and improvement in the ambient air quality.
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Monóxido de Carbono , Material Particulado , Biomasa , Monóxido de Carbono/análisis , Carbón Orgánico , Estudios Transversales , Humanos , Material Particulado/análisis , Uganda/epidemiologíaRESUMEN
Sub-Saharan Africa (SSA) has a significant proportion of populations living in urban slum conditions, where exposure to multiple environmental stressors and social inequalities is ubiquitous. This commentary synthesizes commonalities in recent environmental health studies from urban cities in East and West Africa, presented during a symposium sponsored by the Africa Chapter of the International Society of Environmental Epidemiology (ISEE) in August 2020. A key takeaway from this symposium is the need for harmonization of epidemiologic and exposure data collection in three domains tailored to the SSA context: (1) improvements in socioeconomic status (SES) measurement through harmonization in the conceptualization and operationalization of SES indicators; (2) improvements in air pollution exposure assessment in resource-constrained contexts by better integration, validation, and harmonization of exposure data of air pollution and mitigating factors; and (3) harmonization in the assessment of health outcomes and biomonitoring of contaminants. Focusing on these three domains would galvanize environmental epidemiologists in SSA around shared data collection instruments and shared data platforms and facilitate the pooling of data across the continent. Fostering this collaborative research will enable researchers and decision-makers to glean new insights and develop robust environmental health interventions and policies for SSA urban slums and for improved population health.
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Contaminación del Aire , Áreas de Pobreza , África del Sur del Sahara , Determinantes Sociales de la Salud , Salud UrbanaRESUMEN
BACKGROUND: Respiratory infections such as influenza account for significant global mortality each year. Generating lipid profiles is a novel and emerging research approach that may provide new insights regarding the development and progression of priority respiratory infections. We hypothesized that select clusters of lipids in human sputum would be associated with specific viral infections (Influenza (H1N1, H3N2) or Rhinovirus). METHODS: Lipid identification and semi-quantitation was determined with liquid chromatography and high-resolution mass spectrometry in induced sputum from individuals with confirmed respiratory infections (influenza (H1N1, H3N2) or rhinovirus). Clusters of lipid species and associations between lipid profiles and the type of respiratory viral agent was determined using Bayesian profile regression and multinomial logistic regression. RESULTS: More than 600 lipid compounds were identified across the sputum samples with the most abundant lipid classes identified as triglycerides (TG), phosphatidylethanolamines (PE), phosphatidylcholines (PC), Sphingomyelins (SM), ether-PC, and ether-PE. A total of 12 lipid species were significantly different when stratified by infection type and included acylcarnitine (AcCar) (10:1, 16:1, 18:2), diacylglycerols (DG) (16:0_18:0, 18:0_18:0), Lysophosphatidylcholine (LPC) (12:0, 20:5), PE (18:0_18:0), and TG (14:1_16:0_18:2, 15:0_17:0_19:0, 16:0_17:0_18:0, 19:0_19:0_19:0). Cluster analysis yielded three clusters of lipid profiles that were driven by just 10 lipid species (TGs and DGs). Cluster 1 had the highest levels of each lipid species and the highest prevalence of influenza A H3 infection (56%, n = 5) whereas cluster 3 had lower levels of each lipid species and the highest prevalence of rhinovirus (60%; n = 6). Using cluster 3 as the reference group, the crude odds of influenza A H3 infection compared to rhinovirus in cluster 1 was significantly (p = 0.047) higher (OR = 15.00 [95% CI: 1.03, 218.29]). After adjustment for confounders (smoking status and pulmonary comorbidities), the odds ratio (OR) became only marginally significant (p = 0.099), but the magnitude of the effect estimate was similar (OR = 16.00 [0.59, 433.03]). CONCLUSIONS: In this study, human sputum lipid profiles were shown to be associated with distinct types of viral infection. Better understanding the relationship between respiratory infections of global importance and lipids contributes to advancing knowledge of pathogenesis of infections including identifying populations with increased susceptibility and developing effective therapeutics and biomarkers of health status.
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Subtipo H1N1 del Virus de la Influenza A , Gripe Humana , Neumonía , Infecciones del Sistema Respiratorio , Virosis , Teorema de Bayes , Humanos , Subtipo H3N2 del Virus de la Influenza A , Lisofosfatidilcolinas , Fosfatidilcolinas , Infecciones del Sistema Respiratorio/diagnóstico , Infecciones del Sistema Respiratorio/epidemiología , Rhinovirus , Esputo , Virosis/diagnóstico , Virosis/epidemiologíaRESUMEN
BACKGROUND: There is currently a scarcity of air pollution epidemiologic data from low- and middle-income countries (LMICs) due to the lack of air quality monitoring in these countries. Additionally, there is limited capacity to assess the health effects of wildfire smoke events in wildfire-prone regions like Brazil's Amazon Basin. Emerging low-cost air quality sensors may have the potential to address these gaps. OBJECTIVES: We investigated the potential of PurpleAir PM2.5 sensors for conducting air pollution epidemiologic research leveraging the United States Environmental Protection Agency's United States-wide correction formula for ambient PM2.5. METHODS: We obtained raw (uncorrected) PM2.5 concentration and humidity data from a PurpleAir sensor in Rio Branco, Brazil, between 2018 and 2019. Humidity measurements from the PurpleAir sensor were used to correct the PM2.5 concentrations. We established the relationship between ambient PM2.5 (corrected and uncorrected) and daily all-cause respiratory hospitalization in Rio Branco, Brazil, using generalized additive models (GAM) and distributed lag non-linear models (DLNM). We used linear regression to assess the relationship between daily PM2.5 concentrations and wildfire reports in Rio Branco during the wildfire seasons of 2018 and 2019. RESULTS: We observed increases in daily respiratory hospitalizations of 5.4% (95%CI: 0.8%, 10.1%) for a 2-day lag and 5.8% (1.5%, 10.2%) for 3-day lag, per 10 µg/m3 PM2.5 (corrected values). The effect estimates were attenuated when the uncorrected PM2.5 data was used. The number of reported wildfires explained 10% of daily PM2.5 concentrations during the wildfire season. DISCUSSION: Exposure-response relationships estimated using corrected low-cost air quality sensor data were comparable with relationships estimated using a validated air quality modeling approach. This suggests that correcting low-cost PM2.5 sensor data may mitigate bias attenuation in air pollution epidemiologic studies. Low-cost sensor PM2.5 data could also predict the air quality impacts of wildfires in Brazil's Amazon Basin.
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Contaminantes Atmosféricos , Contaminación del Aire , Brasil , Estudios Epidemiológicos , Hospitalización , Humanos , Material Particulado , Estados UnidosRESUMEN
Per- and polyfluoroalkyl substances (PFAS) constitute a class of highly stable and extensively manufactured anthropogenic chemicals that have been linked to a variety of adverse health effects in humans and wildlife. These compounds are ubiquitously distributed in the environment and have been measured in aquatic systems globally. However, there are limited data on longitudinal comprehensive assessments of PFAS profiles within sensitive aquatic ecosystems. Surface water samples were collected from the Indian River Lagoon (IRL) and the Atlantic coast within Brevard County (BC), FL in December of 2019 (n = 57) and again from corresponding locations in February of 2021 (n = 40). Samples were analyzed by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) to determine the occurrence, concentration, and distribution of 92 PFAS. No significant difference in total PFAS concentrations were identified between samples collected in 2019 (87 ng/L) and those collected in 2021 (77 ng/L). However, comparisons of PFAS among four natural sub-regions within Brevard County revealed site- and regional-specific differences. The Banana River exhibited the greatest concentration of total PFAS, followed by the southern Indian River, the northern Indian River, and then the Atlantic coast. Six distinct PFAS profiles were identified with the novel application of multivariate statistical cluster analysis, which may be useful for identifying potential sources of PFAS. Elevated total PFAS and unique compound mixtures identified in the Banana River are most likely a result of industrial discharge and extensive historical use of aqueous film-forming foams (AFFF). The environmental persistence of PFAS threatens key ecosystem services and the ecological homeostasis of the Indian River Lagoon - the most biologically diverse estuary in North America. Brevard County offers a unique model site that may be used to investigate potential exposure and health implications for wildlife and adjacent coastal communities, which could be extrapolated to better understand and manage other critical coastal systems.
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Fluorocarburos , Contaminantes Químicos del Agua , Ecosistema , Fluorocarburos/análisis , Humanos , Ríos , Espectrometría de Masas en Tándem , Contaminantes Químicos del Agua/análisisRESUMEN
The resurgence of interest in a hydrogen economy and the development of hydrogen-related technologies has initiated numerous research and development efforts aimed at making the generation, storage, and transportation of hydrogen more efficient and affordable. Solar thermochemical hydrogen production (STCH) is a process that potentially exhibits numerous benefits such as high reaction efficiencies, tunable thermodynamics, and continued performance over extended cycling. Although CeO2 has been the de facto standard STCH material for many years, more recently 12R-Ba4CeMn3O12 (BCM) has demonstrated enhanced hydrogen production at intermediate H2/H2O conditions compared to CeO2, making it a contender for large-scale hydrogen production. However, the thermo-reduction stability of 12R-BCM dictates the oxygen partial pressure (pO2) and temperature conditions optimal for cycling. In this study, we identify the formation of a 6H-BCM polytype at high temperature and reducing conditions, experimentally and computationally, as a mechanism and pathway for 12R-BCM decomposition. 12R-BCM was synthesized with high purity and then controllably reduced using thermogravimetric analysis (TGA). Synchrotron X-ray diffraction (XRD) data is used to identify the formation of a 6H-Ba3Ce0.75Mn2.25O9 (6H-BCM) polytype that is formed at 1350 °C under strongly reducing pO2. Density functional theory (DFT) total energy and defect calculations show a window of thermodynamic stability for the 6H-polytype consistent with the XRD results. These data provide the first evidence of the 6H-BCM polytype and could provide a mechanistic explanation for the superior water-splitting behaviors of 12R-BCM.