Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom.

Exposure to outdoor air pollution may affect incidence and severity of coronavirus disease 2019 (COVID-19). In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020 and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Long-term exposure was estimated using mean annual concentrations of particulate matter with diameter ≤2.5 µm (PM2.5), ≤10 µm (PM10), nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2) and benzene (C6H6) in 2019 using a validated air pollution model developed by the Department for Environment, Food and Rural Affairs (DEFRA). The association of long-term exposure to air pollution with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal and spatial confounders. Significant positive associations were observed between PM2.5, PM10, NO2, SO2, benzene and COVID-19 hospital admissions with odds ratios (95% Confidence Intervals [CI]) of 1.27 (1.25-1.30), 1.15 (1.13-1.17), 1.12 (1.10-1.14), 1.16 (1.14-1.18), and 1.39 (1.36-1.42), (per interquartile range [IQR]), respectively. Significant positive associations were also observed between PM2.5, PM10, SO2, or benzene and COVID-19 mortality with odds ratios (95% CI) of 1.39 (1.31-1.48), 1.23 (1.17-1.30), 1.18 (1.12-1.24), and 1.62 (1.52-1.72), per IQR, respectively. Individuals who were older, overweight or obese, current smokers, or had underlying comorbidities showed greater associations between all pollutants of interest and hospital admission, compared to the corresponding groups. Long-term exposure to air pollution is associated with developing severe COVID-19 after a positive SARS-CoV-2 infection, resulting in hospitalization or death.

A comparison of experience sampled hay fever symptom severity across rural and urban areas of the UK.

Hay fever affects people differently and can change over a lifetime, but data is lacking on how environmental factors may influence this. This study is the first to combine atmospheric sensor data with real-time, geo-positioned hay fever symptom reports to examine the relationship between symptom severity and air quality, weather and land use. We study 36145 symptom reports submitted over 5 years by over 700 UK residents using a mobile application. Scores were recorded for nose, eyes and breathing. Symptom reports are labelled as urban or rural using land-use data from the UK's Office for National Statistics. Reports are compared with AURN network pollution measurements and pollen and meteorological data taken from the UK Met Office. Our analysis suggests urban areas record significantly higher symptom severity for all years except 2017. Rural areas do not record significantly higher symptom severity in any year. Additionally, symptom severity correlates with more air quality markers in urban areas than rural areas, indicating that differences in allergy symptoms may be due to variations in the levels of pollutants, pollen counts and seasonality across land-use types. The results suggest that a relationship exists between urban surroundings and hay fever symptoms.

UK daily meteorology, air quality, and pollen measurements for 2016-2019, with estimates for missing data.

In recent years, quantifying the impacts of detrimental air quality has become a global priority for researchers and policy makers. At present, the systems and methodologies supporting the collection and manipulation of this data are difficult to access. To support studies quantifying the interplay between common gaseous and particulate pollutants with meteorology and biological particles, this paper presents a comprehensive data-set containing daily air quality readings from the Automatic Urban and Rural Network, and pollen and weather data from Met Office monitoring stations, in the years 2016 to 2019 inclusive, for the United Kingdom. We describe (1) the sources from which the data were collected, (2) the methods used for the data cleaning process and (3) how issues related to missing values and sparse regional coverage were addressed. The resulting data-set is designed to be used 'as is' by those using air quality data for research; we also describe and provide open access to the methods used for curating the data to allow modification of or addition to the data-set.

Experimental reductions in subdaily flow fluctuations increased gross primary productivity for 425 river kilometers downstream.

Aquatic primary production is the foundation of many river food webs. Dams change the physical template of rivers, often driving food webs toward greater reliance on aquatic primary production. Nonetheless, the effects of regulated flow regimes on primary production are poorly understood. Load following is a common dam flow management strategy that involves subdaily changes in water releases proportional to fluctuations in electrical power demand. This flow regime causes an artificial tide, wetting and drying channel margins and altering river depth and water clarity, all processes that are likely to affect primary production. In collaboration with dam operators, we designed an experimental flow regime whose goal was to mitigate negative effects of load following on ecosystem processes. The experimental flow contrasted steady-low flows on weekends with load following flows on weekdays. Here, we quantify the effect of this experimental flow on springtime gross primary production (GPP) 90-to-425 km downstream of Glen Canyon Dam on the Colorado River, AZ, USA. GPP during steady-low flows was 41% higher than during load following flows, mostly owing to nonlinear reductions in sediment-driven turbidity. The experimental flow increased weekly GPP even after controlling for variation in weekly mean discharge, demonstrating a negative effect of load following on GPP. We estimate that this environmental flow increased springtime carbon fixation by 0.27 g C m-2 d-1, which is ecologically meaningful considering median C fixation in 356 US rivers of 0.44 g C m-2 d-1 and the fact that native fish populations in this river are food-limited.

Accurate Prediction of Organic Aerosol Evaporation Using Kinetic Multilayer Modeling and the Stokes-Einstein Equation.

Organic aerosol can adopt a wide range of viscosities, from liquid to glass, depending on the local humidity. In highly viscous droplets, the evaporation rates of organic components are suppressed to varying degrees, yet water evaporation remains fast. Here, we examine the coevaporation of semivolatile organic compounds (SVOCs), along with their solvating water, from aerosol particles levitated in a humidity-controlled environment. To better replicate the composition of secondary aerosol, nonvolatile organics were also present, creating a three-component diffusion problem. Kinetic modeling reproduced the evaporation accurately when the SVOCs were assumed to obey the Stokes-Einstein relation, and water was not. Crucially, our methodology uses previously collected data to constrain the time-dependent viscosity, as well as water diffusion coefficients, allowing it to be predictive rather than postdictive. Throughout the study, evaporation rates were found to decrease as SVOCs deplete from the particle, suggesting path function type behavior.

New Approach Combining Molecular Fingerprints and Machine Learning to Estimate Relative Ionization Efficiency in Electrospray Ionization.

Electrospray ionization (ESI) is widely used as an ionization source for the analysis of complex mixtures by mass spectrometry. However, different compounds ionize more or less effectively in the ESI source, meaning instrument responses can vary by orders of magnitude, often in hard-to-predict ways. This precludes the use of ESI for quantitative analysis where authentic standards are not available. Relative ionization efficiency (RIE) scales have been proposed as a route to predict the response of compounds in ESI. In this work, a scale of RIEs was constructed for 51 carboxylic acids, spanning a wide range of additional functionalities, to produce a model for predicting the RIE of unknown compounds. While using a limited number of compounds, we explore the usefulness of building a predictor using popular supervised regression techniques, encoding the compounds as combinations of different structural features using a range of common "fingerprints". It was found that Bayesian ridge regression gives the best predictive model, encoding compounds using features designed for activity coefficient models. This produced a predictive model with an R 2 score of 0.62 and a root-mean-square error (RMSE) of 0.362. Such scores are comparable to those obtained in previous studies but without the requirement to first measure or predict the physical properties of the compounds, potentially reducing the time required to make predictions.

Maternal carriage of Prevotella during pregnancy associates with protection against food allergy in the offspring.

In mice, the maternal microbiome influences fetal immune development and postnatal allergic outcomes. Westernized populations have high rates of allergic disease and low rates of gastrointestinal carriage of Prevotella, a commensal bacterial genus that produces short chain fatty acids and endotoxins, each of which may promote the development of fetal immune tolerance. In this study, we use a prebirth cohort (n = 1064 mothers) to conduct a nested case-cohort study comparing 58 mothers of babies with clinically proven food IgE mediated food allergy with 258 randomly selected mothers. Analysis of the V4 region of the 16S rRNA gene in fecal samples shows maternal carriage of Prevotella copri during pregnancy strongly predicts the absence of food allergy in the offspring. This association was confirmed using targeted qPCR and was independent of infant carriage of P. copri. Larger household size, which is a well-established protective factor for allergic disease, strongly predicts maternal carriage of P. copri.

Transient cavity dynamics and divergence from the Stokes-Einstein equation in organic aerosol.

The diffusion of small molecules through viscous matrices formed by large organic molecules is important across a range of domains, including pharmaceutical science, materials chemistry, and atmospheric science, impacting on, for example, the formation of amorphous and crystalline phases. Here we report significant breakdowns in the Stokes-Einstein (SE) equation from measurements of the diffusion of water (spanning 5 decades) and viscosity (spanning 12 decades) in saccharide aerosol droplets. Molecular dynamics simulations show water diffusion is not continuous, but proceeds by discrete hops between transient cavities that arise and dissipate as a result of dynamical fluctuations within the saccharide lattice. The ratio of transient cavity volume to solvent volume increases with size of molecules making up the lattice, increasing divergence from SE predictions. This improved mechanistic understanding of diffusion in viscous matrices explains, for example, why organic compounds equilibrate according to SE predictions and water equilibrates more rapidly in aerosols.

Comparison of Approaches for Measuring and Predicting the Viscosity of Ternary Component Aerosol Particles.

Measurements of the water activity-dependent viscosity of aerosol particles from two techniques are compared, specifically from the coalescence of two droplets in holographic optical tweezers (HOT) and poke-and-flow experiments on particles deposited onto a glass substrate. These new data are also compared with the fitting of dimer coagulation, isolation, and coalescence (DCIC) measurements. The aerosol system considered in this work are ternary mixtures of sucrose-citric acid-water and sucrose-NaNO3-water, at varying solute mass ratios. Results from HOT and poke-and-flow are in excellent agreement over their overlapping range of applicability (∼103-107 Pa s); fitted curves from DCIC data show variable agreement with the other two techniques because of the sensitivity of the applied modeling framework to the representation of water content in the particles. Further, two modeling approaches for the predictions of the water activity-dependent viscosity of these ternary systems are evaluated. We show that it is possible to represent their viscosity with relatively simple mixing rules applied to the subcooled viscosity values of each component or to the viscosity of the corresponding binary mixtures.

Secondary organic aerosol reduced by mixture of atmospheric vapours.

Secondary organic aerosol contributes to the atmospheric particle burden with implications for air quality and climate. Biogenic volatile organic compounds such as terpenoids emitted from plants are important secondary organic aerosol precursors with isoprene dominating the emissions of biogenic volatile organic compounds globally. However, the particle mass from isoprene oxidation is generally modest compared to that of other terpenoids. Here we show that isoprene, carbon monoxide and methane can each suppress the instantaneous mass and the overall mass yield derived from monoterpenes in mixtures of atmospheric vapours. We find that isoprene 'scavenges' hydroxyl radicals, preventing their reaction with monoterpenes, and the resulting isoprene peroxy radicals scavenge highly oxygenated monoterpene products. These effects reduce the yield of low-volatility products that would otherwise form secondary organic aerosol. Global model calculations indicate that oxidant and product scavenging can operate effectively in the real atmosphere. Thus highly reactive compounds (such as isoprene) that produce a modest amount of aerosol are not necessarily net producers of secondary organic particle mass and their oxidation in mixtures of atmospheric vapours can suppress both particle number and mass of secondary organic aerosol. We suggest that formation mechanisms of secondary organic aerosol in the atmosphere need to be considered more realistically, accounting for mechanistic interactions between the products of oxidizing precursor molecules (as is recognized to be necessary when modelling ozone production).

The viscosity of atmospherically relevant organic particles.

The importance of organic aerosol particles in the environment has been long established, influencing cloud formation and lifetime, absorbing and scattering sunlight, affecting atmospheric composition and impacting on human health. Conventionally, ambient organic particles were considered to exist as liquids. Recent observations in field measurements and studies in the laboratory suggest that they may instead exist as highly viscous semi-solids or amorphous glassy solids under certain conditions, with important implications for atmospheric chemistry, climate and air quality. This review explores our understanding of aerosol particle phase, particularly as identified by measurements of the viscosity of organic particles, and the atmospheric implications of phase state.

Characterising the evaporation kinetics of water and semi-volatile organic compounds from viscous multicomponent organic aerosol particles.

The physicochemical changes experienced by organic aerosol particles undergoing dehydration into the surrounding gas phase can be drastic, forcing rapid vitrification of the particle and suppressing internal diffusion. Until recently, experimental studies have concentrated on quantifying diffusional mixing of either water or non-volatile components, while relatively little attention has been paid to the role of semivolatile organic component (SVOC) diffusion and volatilisation in maintaining the equilibrium between the gas and particle phases. Here we present methods to simultaneously investigate diffusivities and volatilities in studies of evolving single ternary aerosol particle size and composition. Analysing particles of ternary composition must account for the multiple chemical species that volatilise in response to a step change in gas phase water activity. In addition, treatments of diffusion in multicomponent mixtures are necessary to represent evolving heterogeneities in particle composition. We find that the contributions to observed size behaviour from volatilisation of water and a SVOC can be decoupled and treated separately. Employing Fickian diffusion modelling, we extract the compositional dependence of the diffusion constant of water and compare the results to recently published parametrisations in binary aerosol particles. The treatment of ideality and activity in each case is discussed, with reference to use in multicomponent core shell models. Meanwhile, the evaporation of an SVOC into an unsaturated gas flow may be treated by Maxwell's equation, with slow diffusional transport manifesting as a suppression in the extracted vapour pressure.

Erratum: Gut microbial metabolites limit the frequency of autoimmune T cells and protect against type 1 diabetes.

This corrects the article DOI: 10.1038/ni.3713.

Development of lithium attachment mass spectrometry - knudsen effusion and chemical ionisation mass spectrometry (KEMS, CIMS).

Lithium ion attachment mass spectrometry provides a non-specific, non-fragmenting, sensitive and robust method for the detection of volatile species in the gas phase. The design, manufacture and results of lithium based ion attachment ionisation sources for two different mass spectrometry systems are presented. In this study trace gas analysis is investigated using a modified Chemical Ionization Mass Spectrometer (CIMS) and vapour pressure measurements are made using a modified Knudsen Effusion Mass Spectrometer (KEMS). In the Li+ CIMS, where the Li+ ionization acts a soft and unselective ionization source, limits of detection of 0.2 ppt for formic acid, 15 ppt for nitric acid and 120 ppt for ammonia were achieved, allowing for ambient measurements of such species at atmospherically relevant concentrations. In the first application of Lithium ion attachment in ultra-high vacuum (UHV), vapor pressures of various atmospherically relevant species were measured with the adapted KEMS, giving measured values equivalent to previous results from electron impact KEMS. In the Li+ KEMS vapour pressures <10-3 mbar can be measured without any fragmentation, as is seen with the initial electron impact (EI) set up, allowing the vapor pressure of individual components within mixtures to be determined.

Dietary Propolis Ameliorates Dextran Sulfate Sodium-Induced Colitis and Modulates the Gut Microbiota in Rats Fed a Western Diet.

Propolis is an important hive product and considered beneficial to health. However, evidence of its potential for improving gut health is still lacking. Here we use rats to examine whether dietary supplementation with propolis could be used as a therapy for ulcerative colitis. Rats were fed with a Western style diet alone (controls) or supplemented with different amounts of Chinese propolis (0.1%, 0.2%, and 0.3%) to examine effects on acute colitis induced by 3% dextran sulphate sodium (DSS) in drinking water. Propolis at 0.3%, but not lower levels, significantly improved colitis symptoms compared with the control group, with a less pronounced disease activity index (DAI) (p < 0.001), a significant increase in colon length/weight ratio (p < 0.05) and an improved distal colon tissue structure as assessed by histology. Although short chain fatty acid levels in digesta were not altered by propolis supplementation, 16S rRNA phylogenetic sequencing revealed a significant increase in gut microbial diversity after 21 days of 0.3% propolis supplementation compared with controls including a significant increase in bacteria belonging to the Proteobacteria and Acidobacteria phyla. This is the first study to demonstrate that propolis can attenuate DSS-induced colitis and provides new insight into diet-microbiota interactions during inflammatory bowel disease.

Accurate representations of the physicochemical properties of atmospheric aerosols: when are laboratory measurements of value?

Laboratory studies can provide important insights into the processes that occur at the scale of individual particles in ambient aerosol. We examine the accuracies of measurements of core physicochemical properties of aerosols that can be made in single particle studies and explore the impact of these properties on the microscopic processes that occur in ambient aerosol. Presenting new measurements, we examine here the refinements in our understanding of aerosol hygroscopicity, surface tension, viscosity and optical properties that can be gained from detailed laboratory measurements for complex mixtures through to surrogates for secondary organic atmospheric aerosols.

Measured Saturation Vapor Pressures of Phenolic and Nitro-aromatic Compounds.

Phenolic and nitro-aromatic compounds are extremely toxic components of atmospheric aerosol that are currently not well understood. In this Article, solid and subcooled-liquid-state saturation vapor pressures of phenolic and nitro-aromatic compounds are measured using Knudsen Effusion Mass Spectrometry (KEMS) over a range of temperatures (298-318 K). Vapor pressure estimation methods, assessed in this study, do not replicate the observed dependency on the relative positions of functional groups. With a few exceptions, the estimates are biased toward predicting saturation vapor pressures that are too high, by 5-6 orders of magnitude in some cases. Basic partitioning theory comparisons indicate that overestimation of vapor pressures in such cases would cause us to expect these compounds to be present in the gas state, whereas measurements in this study suggest these phenolic and nitro-aromatic will partition into the condensed state for a wide range of ambient conditions if absorptive partitioning plays a dominant role. While these techniques might have both structural and parametric uncertainties, the new data presented here should support studies trying to ascertain the role of nitrogen containing organics on aerosol growth and human health impacts.

Gut microbial metabolites limit the frequency of autoimmune T cells and protect against type 1 diabetes.

Gut dysbiosis might underlie the pathogenesis of type 1 diabetes. In mice of the non-obese diabetic (NOD) strain, we found that key features of disease correlated inversely with blood and fecal concentrations of the microbial metabolites acetate and butyrate. We therefore fed NOD mice specialized diets designed to release large amounts of acetate or butyrate after bacterial fermentation in the colon. Each diet provided a high degree of protection from diabetes, even when administered after breakdown of immunotolerance. Feeding mice a combined acetate- and butyrate-yielding diet provided complete protection, which suggested that acetate and butyrate might operate through distinct mechanisms. Acetate markedly decreased the frequency of autoreactive T cells in lymphoid tissues, through effects on B cells and their ability to expand populations of autoreactive T cells. A diet containing butyrate boosted the number and function of regulatory T cells, whereas acetate- and butyrate-yielding diets enhanced gut integrity and decreased serum concentration of diabetogenic cytokines such as IL-21. Medicinal foods or metabolites might represent an effective and natural approach for countering the numerous immunological defects that contribute to T cell-dependent autoimmune diseases.