"I have to stay inside ": Experiences of air pollution for people with asthma.

Asthma, characterized by airway inflammation, sensitization and constriction, and leading to symptoms including cough and dyspnoea, affects millions of people globally. Air pollution is a known asthma trigger, yet how it is experienced is understudied and how individuals with asthma interact with air quality information and manage exacerbation risks is unclear. This study aimed to explore how people living with asthma in Scotland, UK, experienced and managed their asthma in relation to air pollution. We explored these issues with 36 participants using semi-structured interviews. We found that self-protection measures were influenced by place and sense of control (with the home being a "safe space"), and that the perception of clean(er) air had a liberating effect on outdoor activities. We discuss how these insights could shape air quality-related health advice in future.

Personal exposure to fine particulate matter (PM2.5) and self-reported asthma-related health.

PM2.5 (fine particulate matter ≤2.5 µm in diameter) is a key pollutant that can produce acute asthma exacerbations and longer-term deterioration of respiratory health. Individual exposure to PM2.5 is unique and varies across microenvironments. Low-cost sensors (LCS) can collect data at a spatiotemporal resolution previously unattainable, allowing the study of exposures across microenvironments. The aim of this study is to investigate the acute effects of personal exposure to PM2.5 on self-reported asthma-related health. Twenty-eight non-smoking adults with asthma living in Scotland collected PM2.5 personal exposure data using LCS. Measurements were made at a 2-min time resolution for a period of 7 days as participants conducted their typical daily routines. Concurrently, participants were asked to keep a detailed time-activity diary, logging their activities and microenvironments, along with hourly information on their respiratory health and medication use. Health outcomes were modelled as a function of hourly PM2.5 concentration (plus 1- and 2-h lag) using generalized mixed-effects models adjusted for temperature and relative humidity. Personal exposures to PM2.5 varied across microenvironments, with the largest average microenvironmental exposure observed in private residences (11.5 ± 48.6 µg/m3) and lowest in the work microenvironment (2.9 ± 11.3 µg/m3). The most frequently reported asthma symptoms, wheezing, chest tightness and cough, were reported on 3.4%, 1.6% and 1.6% of participant-hours, respectively. The odds of reporting asthma symptoms increased per interquartile range (IQR) in PM2.5 exposure (odds ratio (OR) 1.29, 95% CI 1.07-1.54) for same-hour exposure. Despite this, no association was observed between reliever inhaler use (non-routine, non-exercise related) and PM2.5 exposure (OR 1.02, 95% CI 0.71-1.48). Current air quality monitoring practices are inadequate to detect acute asthma symptom prevalence resulting from PM2.5 exposure; to detect these requires high-resolution air quality data and health information collected in situ. Personal exposure monitoring could have significant implications for asthma self-management and clinical practice.

Public engagement with air quality data: using health behaviour change theory to support exposure-minimising behaviours.

Exposure to air pollution prematurely kills 7 million people globally every year. Policy measures designed to reduce emissions of pollutants, improve ambient air and consequently reduce health impacts, can be effective, but are generally slow to generate change. Individual actions can therefore supplement policy measures and more immediately reduce people's exposure to air pollution. Air quality indices (AQI) are used globally (though not universally) to translate complex air quality data into a single unitless metric, which can be paired with advice to encourage behaviour change. Here we explore, with reference to health behaviour theories, why these are frequently insufficient to instigate individual change. We examine the health behaviour theoretical steps linking air quality data with reduced air pollution exposure and (consequently) improved public health, arguing that a combination of more 'personalised' air quality data and greater public engagement with these data will together better support individual action. Based on this, we present a novel framework, which, when used to shape air quality interventions, has the potential to yield more effective and sustainable interventions to reduce individual exposures and thus reduce the global public health burden of air pollution.

Alkaline air: changing perspectives on nitrogen and air pollution in an ammonia-rich world.

Ammonia and ammonium have received less attention than other forms of air pollution, with limited progress in controlling emissions at UK, European and global scales. By contrast, these compounds have been of significant past interest to science and society, the recollection of which can inform future strategies. Sal ammoniac (nushadir, nao sha) is found to have been extremely valuable in long-distance trade (ca AD 600-1150) from Egypt and China, where 6-8 kg N could purchase a human life, while air pollution associated with nushadir collection was attributed to this nitrogen form. Ammonia was one of the keys to alchemy-seen as an early experimental mesocosm to understand the world-and later became of interest as 'alkaline air' within the eighteenth century development of pneumatic chemistry. The same economic, chemical and environmental properties are found to make ammonia and ammonium of huge relevance today. Successful control of acidifying SO2 and NOx emissions leaves atmospheric NH3 in excess in many areas, contributing to particulate matter (PM2.5) formation, while leading to a new significance of alkaline air, with adverse impacts on natural ecosystems. Investigations of epiphytic lichens and bog ecosystems show how the alkalinity effect of NH3 may explain its having three to five times the adverse effect of ammonium and nitrate, respectively. It is concluded that future air pollution policy should no longer neglect ammonia. Progress is likely to be mobilized by emphasizing the lost economic value of global N emissions ($200 billion yr-1), as part of developing the circular economy for sustainable nitrogen management. This article is part of a discussion meeting issue 'Air quality, past present and future'.

The contributions to long-term health-relevant particulate matter at the UK EMEP supersites between 2010 and 2013: Quantifying the mitigation challenge.

Human health burdens associated with long-term exposure to particulate matter (PM) are substantial. The metrics currently recommended by the World Health Organization for quantification of long-term health-relevant PM are the annual average PM10 and PM2.5 mass concentrations, with no low concentration threshold. However, within an annual average, there is substantial variation in the composition of PM associated with different sources. To inform effective mitigation strategies, therefore, it is necessary to quantify the conditions that contribute to annual average PM10 and PM2.5 (rather than just short-term episodic concentrations). PM10, PM2.5, and speciated water-soluble inorganic, carbonaceous, heavy metal and polycyclic aromatic hydrocarbon components are concurrently measured at the two UK European Monitoring and Evaluation Programme (EMEP) 'supersites' at Harwell (SE England) and Auchencorth Moss (SE Scotland). In this work, statistical analyses of these measurements are integrated with air-mass back trajectory data to characterise the 'chemical climate' associated with the long-term health-relevant PM metrics at these sites. Specifically, the contributions from different PM concentrations, months, components and geographic regions are detailed. The analyses at these sites provide policy-relevant conclusions on mitigation of (i) long-term health-relevant PM in the spatial domain for which these sites are representative, and (ii) the contribution of regional background PM to long-term health-relevant PM. At Harwell the mean (±1 sd) 2010-2013 annual average concentrations were PM10=16.4±1.4µgm(-3) and PM2.5=11.9±1.1µgm(-3) and at Auchencorth PM10=7.4±0.4µgm(-3) and PM2.5=4.1±0.2µgm(-3). The chemical climate state at each site showed that frequent, moderate hourly PM10 and PM2.5 concentrations (defined as approximately 5-15µgm(-3) for PM10 and PM2.5 at Harwell and 5-10µgm(-3) for PM10 at Auchencorth) determined the magnitude of annual average PM10 and PM2.5 to a greater extent than the relatively infrequent high, episodic PM10 and PM2.5 concentrations. These moderate PM10 and PM2.5 concentrations were derived across the range of chemical components, seasons and air-mass pathways, in contrast to the highest PM concentrations which tended to associate with specific conditions. For example, the largest contribution to moderate PM10 and PM2.5 concentrations - the secondary inorganic aerosol components, specifically NO3(-) - were accumulated during the arrival of trajectories traversing the spectrum of marine, UK, and continental Europe areas. Mitigation of the long-term health-relevant PM impact in the regions characterised by these two sites requires multilateral action, across species (and hence source sectors), both nationally and internationally; there is no dominant determinant of the long-term PM metrics to target.

Ammonia emissions from an anaerobic digestion plant estimated using atmospheric measurements and dispersion modelling.

Anaerobic digestion (AD) is becoming increasingly implemented within organic waste treatment operations. The storage and processing of large volumes of organic wastes through AD has been identified as a significant source of ammonia (NH3) emissions, however the totality of ammonia emissions from an AD plant have not been previously quantified. The emissions from an AD plant processing food waste were estimated through integrating ambient NH3 concentration measurements, atmospheric dispersion modelling, and comparison with published emission factors (EFs). Two dispersion models (ADMS and a backwards Lagrangian stochastic (bLS) model) were applied to calculate emission estimates. The bLS model (WindTrax) was used to back-calculate a total (top-down) emission rate for the AD plant from a point of continuous NH3 measurement downwind from the plant. The back-calculated emission rates were then input to the ADMS forward dispersion model to make predictions of air NH3 concentrations around the site, and evaluated against weekly passive sampler NH3 measurements. As an alternative approach emission rates from individual sources within the plant were initially estimated by applying literature EFs to the available site parameters concerning the chemical composition of waste materials, room air concentrations, ventilation rates, etc. The individual emission rates were input to ADMS and later tuned by fitting the simulated ambient concentrations to the observed (passive sampler) concentration field, which gave an excellent match to measurements after an iterative process. The total emission from the AD plant thus estimated by a bottom-up approach was 16.8±1.8mgs(-1), which was significantly higher than the back-calculated top-down estimate (7.4±0.78mgs(-1)). The bottom-up approach offered a more realistic treatment of the source distribution within the plant area, while the complexity of the site was not ideally suited to the bLS method, thus the bottom-up method is believed to give a better estimate of emissions. The storage of solid digestate and the aerobic treatment of liquid effluents at the site were the greatest sources of NH3 emissions.

Personal exposure monitoring of PM2.5 in indoor and outdoor microenvironments.

Adverse health effects from exposure to air pollution are a global challenge and of widespread concern. Recent high ambient concentration episodes of air pollutants in European cities highlighted the dynamic nature of human exposure and the gaps in data and knowledge about exposure patterns. In order to support health impact assessment it is essential to develop a better understanding of individual exposure pathways in people's everyday lives by taking account of all environments in which people spend time. Here we describe the development, validation and results of an exposure method applied in a study conducted in Scotland. A low-cost particle counter based on light-scattering technology - the Dylos 1700 was used. Its performance was validated in comparison with equivalent instruments (TEOM-FDMS) at two national monitoring network sites (R(2)=0.9 at a rural background site, R(2)=0.7 at an urban background site). This validation also provided two functions to convert measured PNCs into calculated particle mass concentrations for direct comparison of concentrations with equivalent monitoring instruments and air quality limit values. This study also used contextual and time-based activity data to define six microenvironments (MEs) to assess everyday exposure of individuals to short-term PM2.5 concentrations. The Dylos was combined with a GPS receiver to track movement and exposure of individuals across the MEs. Seventeen volunteers collected 35 profiles. Profiles may have a different overall duration and structure with respect to times spent in different MEs and activities undertaken. Results indicate that due to the substantial variability across and between MEs, it is essential to measure near-complete exposure pathways to allow for a comprehensive assessment of the exposure risk a person encounters on a daily basis. Taking into account the information gained through personal exposure measurements, this work demonstrates the added value of data generated by the application of low-cost monitors.

Heterogeneity of atmospheric ammonia at the landscape scale and consequences for environmental impact assessment.

We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

Towards a climate-dependent paradigm of ammonia emission and deposition.

Existing descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.

Uptake of gaseous hydrogen peroxide by submicrometer titanium dioxide aerosol as a function of relative humidity.

Hydrogen peroxide (H(2)O(2)) is an important atmospheric oxidant that can serve as a sensitive indicator for HO(x) (OH + HO(2)) chemistry. We report the first direct experimental determination of the uptake coefficient for the heterogeneous reaction of gas-phase hydrogen peroxide (H(2)O(2)) with titanium dioxide (TiO(2)), an important component of atmospheric mineral dust aerosol particles. The kinetics of H(2)O(2) uptake on TiO(2) surfaces were investigated using an entrained aerosol flow tube (AFT) coupled with a chemical ionization mass spectrometer (CIMS). Uptake coefficients (gamma(H(2)O(2))) were measured as a function of relative humidity (RH) and ranged from 1.53 x 10(-3) at 15% RH to 5.04 x 10(-4) at 70% RH. The observed negative correlation of RH with gamma(H(2)O(2)) suggests that gaseous water competes with gaseous H(2)O(2) for adsorption sites on the TiO(2) surface. These results imply that water vapor plays a major role in the heterogeneous loss of H(2)O(2) to submicrometer TiO(2) aerosol. The results are compared with related experimental observations and assessed in terms of their potential impact on atmospheric modeling studies of mineral dust and its effect on the heterogeneous chemistry in the atmosphere.