Modelling inhalation exposure to combustion-related air pollutants in residential buildings: Application to health impact assessment

Simulating the impact of particulate matter exposure on health-related behaviour: A comparative study of stochastic modelling and personal monitoring data

Epidemiological and exposure studies concerning particulate matter (PM) often rely on data from sparse governmental stations. While low-cost personal monitors have some drawbacks, recent developments have shown that they can provide fairly accurate and fit-for-purpose data. Comparing a stochastic, i.e., agent-based model (ABM), with environmental, biometric and activity data, collected with personal monitors, could provide insight into how the two approaches assess PM exposure and dose. An ABM was constructed, simulating a PM exposure/dose assessment of 100 agents. Their actions were governed by inherent probabilities of performing an activity, based on population data. Each activity was associated with an intensity level, and a PM pollution level. The ABM results were compared with real-world results. Both approaches had comparable results, showing similar trends and a mean dose. Discrepancies were seen in the activities with the highest mean dose values. A stochastic model, based on population data, does not capture well some specifics of a local population. Combined, personal sensors could provide input for calibration, and an ABM approach can help offset a low number of participants. Implementing a function of agents influencing others transport choice, increased the importance of cycling/walking in the overall dose estimate. Activists, agents with an increased transport influence, did not play an important role at low PM levels. As concentrations rose, higher shares of activists (and their influence) caused the dose to increase. Simulating a person's PM exposure/dose in different scenarios and activities in a virtual environment provides researchers and policymakers with a valuable tool.

Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication

People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM_2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.

Model development and validation of personal exposure to PM2.5 among urban elders

Indirect measurements through a combination of microenvironment concentrations and personal activity diaries provide a potentially useful alternative for PM_2.5 exposure estimates. This study was to optimize a personal exposure model based on spatiotemporal model predictions for PM_2.5 exposure in a sub-cohort study. Personal, home indoor, home outdoor, and ambient monitoring data of PM_2.5 were conducted for an elderly population in the Taipei city of Taiwan. The proposed microenvironment exposure (ME) models incorporate PM_2.5 measurements and individual time-activity information with a generalized estimating equation (GEE) analysis. We evaluated model performance with daily personal PM_2.5 exposure based on the coefficient of determination, accuracy, and mean bias error. Ambient and home outdoor measures as exposure surrogates are likely to under- and overestimate personal exposure to PM_2.5 in our study population, respectively. Measured and predicted indoor exposures were highly correlated with personal PM_2.5 exposure. The awareness of peculiar smells is an important factor that significantly increases personal PM_2.5 exposure by 46-70%. The model incorporating home indoor PM_2.5 can achieve the highest agreement (R² = 0.790) with personal exposure and the lowest measurement error. The ME model with the GEE analysis combining home outdoor PM_2.5 determined by LUR model with a machine learning technique can improve the prediction (R² = 0.592) of personal PM_2.5 exposure, compared with the prediction of the traditional LUR model (R² = 0.385).

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

Phase state of organic aerosols may limit temperature-driven thermodynamic repartitioning following outdoor-to-indoor transport

Ambient aerosols often experience temperature and humidity gradients following outdoor-to-indoor transport, causing organic aerosols (OA) to either gain or lose mass via gas-particle repartitioning. Recent models have sought to quantify these effects using equilibrium partitioning thermodynamics. However, evidence suggests some indoor OA may possess glassy or semisolid phase states with higher viscosities than liquid OA. Characteristic partitioning timescales of higher-viscosity particles are significantly longer than for liquid particles, which may either fully or partially inhibit repartitioning. For outdoor OA experiencing a temperature change during transport indoors, the ultimate repartitioning state depends on the relationship between the gas-particle partitioning rate coefficient (k_gp) of semivolatile organics and the indoor particle loss rate coefficient (l_p). That is, thermodynamic equilibrium partitioning may occur when semivolatile k_gp ≫ l_p, no repartitioning when semivolatile k_gp ≪ l_p, and partial repartitioning when their magnitudes are similar. Longer indoor particle lifetimes, higher particle number, and larger particle sizes all raise k_gp (driving repartitioning towards equilibrium). For simulated U.S. residences, equilibrium condensation was likely reached in humid climate zones during warm meteorological conditions. In colder regions, the degree of evaporative repartitioning depended on whether organics could repartition before the particle phase state adjusts to indoor conditions, which is uncertain. When an appreciable temperature gradient exists, this study not only confirmed that all outdoor-originating OA that is liquid indoors will reach thermodynamic equilibrium, but also concluded that a plurality (46% for this domain) of such OA that is semisolid may also achieve thermodynamic equilibrium during its indoor lifetime.

Challenges of a Healthy Built Environment: Air Pollution in Construction Industry

Air pollution is a global concern, especially in cities and urban areas, and has many implications for human health and for the environment. In common with other industrial sectors, the construction industry emits air pollutants. In scientific literature, the contribution the construction industry makes to air pollution is underexposed. This systematic literature review (SLR) paper gives an overview of the current literature regarding air pollution within the construction industry. Air pollution is discussed focusing mainly on three levels: (i) buildings and their building life cycle stages, (ii) construction processes and components, and (iii) building material and interior. The final sample of the SLR comprises 161 scientific articles addressing different aspects of the construction industry. The results show that most articles address the use stage of a building. Particulate matter in different sizes is the most frequently examined air pollutant within the SLR. Moreover, about a third of the articles refer to indoor air pollution, which shows the relevance of the topic. The construction industry can help to develop a healthier built environment and support the achievement of cleaner air within various life cycle stages, e.g., with optimized construction processes and healthier materials. International agreements and policies such as the Sustainable Development Goals (SDGs) can support the sustainable development of the construction industry.

Improving Predictions of Indoor Aerosol Concentrations of Outdoor Origin by Considering the Phase Change of Semivolatile Material Driven by Temperature and Mass-Loading Gradients

Outdoor aerosols experience environmental changes as they are transported indoors, including outdoor-to-indoor temperature and mass-loading gradients, which can reduce or enhance their indoor concentrations due to repartitioning driven by changes in thermodynamic equilibrium states. However, the complexity required to model repartitioning typically hinders its inclusion in studies predicting indoor exposure to ambient aerosols. To facilitate exposure predictions, this work used an explicit thermodynamic indoor aerosol model to simulate outdoor-to-indoor aerosol repartitioning typical for residential and office buildings across the 16 U.S. climate zones over an annual time horizon. Results demonstrate that neglecting repartitioning when predicting indoor concentrations can produce errors of up to 80-100% for hydrocarbon-like organic aerosol, 40-60% for total organic aerosol, 400% for ammonium nitrate, and 60% (typically 3 μg/m³) for the total PM_2.5 aerosol. Underpredictions were more likely for buildings in hotter than colder regions, and for residences than offices, since both cooler indoor air and more meaningful residential organic aerosol concentrations encourage condensation of semivolatile organics. Furthermore, a method for computing correction factors to more easily account for thermodynamic repartitioning is provided. Applying these correction factors to mechanical-only aerosol predictions significantly reduced errors to <0.5 μg/m³ for the total indoor PM_2.5 while bypassing explicit thermodynamic simulations.

Spatial Uncertainty in Modeling Inhalation Exposure to Volatile Organic Compounds in Response to the Application of Consumer Spray Products

(1) Background: Mathematical exposure modeling of volatile organic compounds (VOCs) in consumer spray products mostly assumes instantaneous mixing in a room. This well-mixed assumption may result in the uncertainty of exposure estimation in terms of spatial resolution. As the inhalation exposure to chemicals from consumer spray products may depend on the spatial heterogeneity, the degree of uncertainty of a well-mixed assumption should be evaluated under specific exposure scenarios. (2) Methods: A room for simulation was divided into eight compartments to simulate inhalation exposure to an ethanol trigger and a propellant product. Real-time measurements of the atmospheric concentration in a room-sized chamber by proton transfer reaction mass spectrometry were compared with mathematical modeling to evaluate the non-homogeneous distribution of chemicals after their application. (3) Results: The well-mixed model overestimated short-term exposure, particularly under the trigger spray scenario. The uncertainty regarding the different chemical proportions in the trigger did not significantly vary in this study. (4) Conclusions: Inhalation exposure to aerosol generating sprays should consider the spatial uncertainty in terms of the estimation of short-term exposure.

Systemic inequalities in indoor air pollution exposure in London, UK

Deprived communities in many cities are exposed to higher levels of outdoor air pollution, and there is increasing evidence of similar disparities for indoor air pollution exposure. There is a need to understand the drivers for this exposure disparity in order to develop effective interventions aimed at improving population health and reducing health inequities. With a focus on London, UK, this paper assembles evidence to examine why indoor exposure to PM2.5, NOx and CO may disproportionately impact low-income groups. In particular, five factors are explored, namely: housing location and ambient outdoor levels of pollution; housing characteristics, including ventilation properties and internal sources of pollution; occupant behaviours; time spent indoors; and underlying health conditions. Evidence is drawn from various sources, including building physics models, modelled outdoor air pollution levels, time-activity surveys, housing stock surveys, geographical data, and peer-reviewed research. A systems framework is then proposed to integrate these factors, highlighting how exposure to high levels of indoor air pollution in low-income homes is in large part due to factors beyond the control of occupants, and is therefore an area of systemic inequality.

POLICY RELEVANCE

There is increasing public and political awareness of the impact of air pollution on public health. Strong scientific evidence links exposure to air pollution with morbidity and mortality. Deprived communities may be more affected, however, with limited evidence on how deprivation may influence their personal exposure to air pollution, both outdoors and indoors. This paper describes different factors that may lead to low-income households being exposed to higher levels of indoor air pollution than the general population, using available data and models for London (i.e. living in areas of higher outdoor air pollution, in poor-quality housing, undertaking more pollution-generating activities indoors and spending more time indoors). A systems approach is used to show how these factors lead to systemic exposure inequalities, with low-income households having limited opportunities to improve their indoor air quality. This paper can inform actions and public policies to reduce environmental health inequalities, considering both indoor and outdoor air.

Low-Cost Air Quality Sensing towards Smart Homes

The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping of indoor air quality (IAQ) possible in real-time but the availability of a diverse set of LCSs make their selection challenging. Converting individual sensors into a sensing network requires the knowledge of diverse research disciplines, which we aim to bring together by making IAQ an advanced feature of smart homes. The aim of this review is to discuss the advanced home automation technologies for the monitoring and control of IAQ through networked air pollution LCSs. The key steps that can allow transforming conventional homes into smart homes are sensor selection, deployment strategies, data processing, and development of predictive models. A detailed synthesis of air pollution LCSs allowed us to summarise their advantages and drawbacks for spatio-temporal mapping of IAQ. We concluded that the performance evaluation of LCSs under controlled laboratory conditions prior to deployment is recommended for quality assurance/control (QA/QC), however, routine calibration or implementing statistical techniques during operational times, especially during long-term monitoring, is required for a network of sensors. The deployment height of sensors could vary purposefully as per location and exposure height of the occupants inside home environments for a spatio-temporal mapping. Appropriate data processing tools are needed to handle a huge amount of multivariate data to automate pre-/post-processing tasks, leading to more scalable, reliable and adaptable solutions. The review also showed the potential of using machine learning technique for predicting spatio-temporal IAQ in LCS networked-systems.

An air distribution optimization of hospital wards for minimizing cross-infection

Currently, the "2019-CoV-2" has been raging across the world for months, causing massive death, huge panic, chaos, and immeasurable economic loss. Such emerging epidemic viruses come again and again over years, leading to similar destructive consequences. Air-borne transmission among humans is the main reason for the rapid spreading of the virus. Blocking the air-borne transmission should be a significant measure to suppress the spreading of the pandemic. Considering the hospital is the most probable place to occur massive cross-infection among patients as emerging virus usually comes in a disguised way, an air distribution optimization of a general three-bed hospital ward in China is carried out in this paper. Using the Eulerian-Lagrangian method, sneeze process from patients who are assumed to be the virus carrier, which is responsible for a common event to trigger cross-infection, is simulated. The trajectory of the released toxic particle and the probability of approaching others in the same ward are calculated. Two evaluation parameter, total maximum time (TMT) and overall particle concentration (OPC) to reflect the particle mobility and probability to cause cross-infection respectively, are developed to evaluate the proposed ten air distributions in this paper. A relatively optimized air distribution proposal with the lowest TMT and OPC is distinguished through a three-stage analysis. Results show that a bottom-in and top-out air distribution proposal is recommended to minimize cross-infections.

Indoor Exposure to Selected Air Pollutants in the Home Environment: A Systematic Review

(1) Background: There is increasing awareness that the quality of the indoor environment affects our health and well-being. Indoor air quality (IAQ) in particular has an impact on multiple health outcomes, including respiratory and cardiovascular illness, allergic symptoms, cancers, and premature mortality. (2) Methods: We carried out a global systematic literature review on indoor exposure to selected air pollutants associated with adverse health effects, and related household characteristics, seasonal influences and occupancy patterns. We screened records from six bibliographic databases: ABI/INFORM, Environment Abstracts, Pollution Abstracts, PubMed, ProQuest Biological and Health Professional, and Scopus. (3) Results: Information on indoor exposure levels and determinants, emission sources, and associated health effects was extracted from 141 studies from 29 countries. The most-studied pollutants were particulate matter (PM_2.5 and PM₁₀); nitrogen dioxide (NO₂); volatile organic compounds (VOCs) including benzene, toluene, xylenes and formaldehyde; and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Identified indoor PM_2.5 sources include smoking, cooking, heating, use of incense, candles, and insecticides, while cleaning, housework, presence of pets and movement of people were the main sources of coarse particles. Outdoor air is a major PM_2.5 source in rooms with natural ventilation in roadside households. Major sources of NO₂ indoors are unvented gas heaters and cookers. Predictors of indoor NO₂ are ventilation, season, and outdoor NO₂ levels. VOCs are emitted from a wide range of indoor and outdoor sources, including smoking, solvent use, renovations, and household products. Formaldehyde levels are higher in newer houses and in the presence of new furniture, while PAH levels are higher in smoking households. High indoor particulate matter, NO₂ and VOC levels were typically associated with respiratory symptoms, particularly asthma symptoms in children. (4) Conclusions: Household characteristics and occupant activities play a large role in indoor exposure, particularly cigarette smoking for PM_2.5, gas appliances for NO₂, and household products for VOCs and PAHs. Home location near high-traffic-density roads, redecoration, and small house size contribute to high indoor air pollution. In most studies, air exchange rates are negatively associated with indoor air pollution. These findings can inform interventions aiming to improve IAQ in residential properties in a variety of settings.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

Healthy buildings for a healthy city: Is the public health evidence base informing current building policies?

Research has demonstrated that housing quality is a key urban intervention in reducing health risks and improving climate resilience, addressing a key ambition of the United Nations Sustainable Development Goals. Yet housing quality remains a problem even in high income countries such as England. In particular, hazards such as excess cold, excess heat and lack of ventilation leading to damp and mould have been identified as a major issue in homes. Research shows that these hazards can lead to a range of health conditions, such as respiratory and cardiovascular disease, infections and mental health problems. This article explores the use of public health research and evidence in policy to regulate new buildings in England to deliver improved public health, climate resilience and a reduced carbon footprint, in particular exploring the policy drivers and awareness of the public health evidence. Findings show that public health evidence is hardly referenced in policy and that the focus on other evidence bases such as on climate mitigation in building regulations results in both positive and negative impacts on health. This reflects a lack of a systems approach around urban interventions leading to weaknesses in standards regulating the private development sector. In conclusion, this paper recommends: 1. the consideration of health impact in future building regulations; 2. the integration and coordination of key policies covering various scales and phases of the development processes and 3. the better education of residents to understand advances in new energy performance technologies.

Application of an indoor air pollution metamodel to a spatially-distributed housing stock

Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM_2.5 and NO₂ for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM_2.5 and 0.41 (99%CIs; 0.34-0.59) for outdoor NO₂; Pearson correlation analysis indicates a greater spatial modification of PM_2.5 exposure by housing (ρ = 0.81) than NO₂ (ρ = 0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9 ppm (99%CIs)(median = 3.0 ppm) in kitchens and 0.3-25.6 ppm (median = 6.4 ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.

A multipollutant evaluation of APEX using microenvironmental ozone, carbon monoxide, and particulate matter (PM2.5) concentrations measured in Los Angeles by the exposure classification project

This paper describes an operational evaluation of the US Environmental Protection Agency's (EPA) Air Pollution Exposure Model (APEX). APEX simulations for a multipollutant ambient air mixture, i.e. ozone (O₃), carbon monoxide (CO), and particulate matter 2.5 microns in diameter or less (PM_2.5), were performed for two seasons in three study areas in central Los Angeles. APEX predicted microenvironmental concentrations were compared with concentrations of these three pollutants monitored in the Exposure Classification Project (ECP) study during the same periods. The ECP was designed expressly for evaluating exposure models and measured concentrations inside and outside 40 microenvironments. This evaluation study identifies important uncertainties in APEX inputs and model predictions useful for guiding further exposure model input data and algorithm development efforts. This paper also presents summaries of the concentrations in the different microenvironments.

Developing a predictive model for fine particulate matter concentrations in low socio-economic households in Durban, South Africa

In low-resource settings, there is a need to develop models that can address contributions of household and outdoor sources to population exposures. The aim of the study was to model indoor PM_2.5 using household characteristics, activities, and outdoor sources. Households belonging to participants in the Mother and Child in the Environment (MACE) birth cohort, in Durban, South Africa, were randomly selected. A structured walk-through identified variables likely to generate PM_2.5 . MiniVol samplers were used to monitor PM_2.5 for a period of 24 hours, followed by a post-activity questionnaire. Factor analysis was used as a variable reduction tool. Levels of PM_2.5 in the south were higher than in the north of the city (P < .05); crowding and dwelling type, household emissions (incense, candles, cooking), and household smoking practices were factors associated with an increase in PM_2.5 levels (P < .05), while room magnitude and natural ventilation factors were associated with a decrease in the PM_2.5 levels (P < .05). A reasonably robust PM_2.5 predictive model was obtained with model R² of 50%. Recognizing the challenges in characterizing exposure in environmental epidemiological studies, particularly in resource-constrained settings, modeling provides an opportunity to reasonably estimate indoor pollutant levels in unmeasured homes.

Characterizing Aggregated Exposure to Primary Particulate Matter: Recommended Intake Fractions for Indoor and Outdoor Sources

Exposure to fine particulate matter (PM_2.5) from indoor and outdoor sources is a leading environmental contributor to global disease burden. In response, we established under the auspices of the UNEP/SETAC Life Cycle Initiative a coupled indoor-outdoor emission-to-exposure framework to provide a set of consistent primary PM_2.5 aggregated exposure factors. We followed a matrix-based mass balance approach for quantifying exposure from indoor and ground-level urban and rural outdoor sources using an effective indoor-outdoor population intake fraction and a system of archetypes to represent different levels of spatial detail. Emission-to-exposure archetypes range from global indoor and outdoor averages, via archetypal urban and indoor settings, to 3646 real-world cities in 16 parametrized subcontinental regions. Population intake fractions from urban and rural outdoor sources are lowest in Northern regions and Oceania and highest in Southeast Asia with population-weighted means across 3646 cities and 16 subcontinental regions of, respectively, 39 ppm (95% confidence interval: 4.3-160 ppm) and 2 ppm (95% confidence interval: 0.2-6.3 ppm). Intake fractions from residential and occupational indoor sources range from 470 ppm to 62 000 ppm, mainly as a function of air exchange rate and occupancy. Indoor exposure typically contributes 80-90% to overall exposure from outdoor sources. Our framework facilitates improvements in air pollution reduction strategies and life cycle impact assessments.

Impact of climate change on the domestic indoor environment and associated health risks in the UK

There is growing evidence that projected climate change has the potential to significantly affect public health. In the UK, much of this impact is likely to arise by amplifying existing risks related to heat exposure, flooding, and chemical and biological contamination in buildings. Identifying the health effects of climate change on the indoor environment, and risks and opportunities related to climate change adaptation and mitigation, can help protect public health. We explored a range of health risks in the domestic indoor environment related to climate change, as well as the potential health benefits and unintended harmful effects of climate change mitigation and adaptation policies in the UK housing sector. We reviewed relevant scientific literature, focusing on housing-related health effects in the UK likely to arise through either direct or indirect mechanisms of climate change or mitigation and adaptation measures in the built environment. We considered the following categories of effect: (i) indoor temperatures, (ii) indoor air quality, (iii) indoor allergens and infections, and (iv) flood damage and water contamination. Climate change may exacerbate health risks and inequalities across these categories and in a variety of ways, if adequate adaptation measures are not taken. Certain changes to the indoor environment can affect indoor air quality or promote the growth and propagation of pathogenic organisms. Measures aimed at reducing greenhouse gas emissions have the potential for ancillary public health benefits including reductions in health burdens related heat and cold, indoor exposure to air pollution derived from outdoor sources, and mould growth. However, increasing airtightness of dwellings in pursuit of energy efficiency could also have negative effects by increasing concentrations of pollutants (such as PM2.5, CO and radon) derived from indoor or ground sources, and biological contamination. These effects can largely be ameliorated by mechanical ventilation with heat recovery (MVHR) and air filtration, where such solution is feasible and when the system is properly installed, operated and maintained. Groups at high risk of these adverse health effects include the elderly (especially those living on their own), individuals with pre-existing illnesses, people living in overcrowded accommodation, and the socioeconomically deprived. A better understanding of how current and emerging building infrastructure design, construction, and materials may affect health in the context of climate change and mitigation and adaptation measures is needed in the UK and other high income countries. Long-term, energy efficient building design interventions, ensuring adequate ventilation, need to be promoted.

Housing interventions and health: Quantifying the impact of indoor particles on mortality and morbidity with disease recovery

Housing interventions for energy efficiency and greenhouse gas emission reduction have the potential to reduce exposure to indoor air pollution if they are implemented correctly. This work assessed the health impacts of home energy efficiency measures in England and Wales resulting in a reduction in average indoor PM2.5 exposures of 3 μg m(-3). The assessment was performed using a new multistate life table model which allows transition into and between multiple morbid states, including recovery to disease-free status and relapse, with transition rates informed by age- and cause-specific disease prevalence, incidence and mortality data. Such models have not previously included disease recovery. The results demonstrate that incorporation of recovery in the model is necessary for conditions such as asthma which have high incidence in early life but likelihood of recovery in adulthood. The impact assessment of the home energy efficiency intervention showed that the reduction in PM2.5 exposure would be associated with substantial benefits for mortality and morbidity from asthma, coronary heart disease and lung cancer. The overall impact would be an increase in life expectancy of two to three months and approximately 13 million QALYs gained over the 90 year follow-up period. Substantial quality-of-life benefits were also observed, with a decrease in asthma over all age groups and larger benefits due to reduced coronary heart disease and lung cancer, particularly in older age groups. The multistate model with recovery provides important additional information for assessing the impact on health of environmental policies and interventions compared with mortality-only life tables, allowing more realistic representation of diseases with substantial non-mortality burdens.

A new agent for derivatizing carbonyl species used to investigate limonene ozonolysis

A new method for derivatizing carbonyl compounds is presented. The conversion of a series of dicarbonyls to oximes in aqueous solution and from gas-phase sampling was achieved using O-tert-butyl-hydroxylamine hydrochloride (TBOX). Some advantages of using this derivatization agent include: aqueous reactions, lower molecular weight oximes, and shortened oxime-formation reaction time. Additionally, the TBOX derivatization technique was used to investigate the carbonyl reaction products from limonene ozonolysis. With ozone (O3) as the limiting reagent, four carbonyl compounds were detected: 7-hydroxy-6-oxo-3-(prop-1-en-2-yl)heptanal; 3-Isopropenyl-6-oxoheptanal (IPOH), 3-acetyl-6-oxoheptanal (3A6O) and one carbonyl of unknown structure. Using cyclohexane as a hydroxyl (OH•) radical scavenger, the relative yields (peak area) of the unknown carbonyl, IPOH, and 3A6O were reduced indicating the influence secondary OH radicals have on limonene ozonolysis products. The relative yield of the hydroxy-dicarbonyl based on the chromatogram was unchanged suggesting it is only made by the limonene + O3 reaction. The detection of 3A6O using TBOX highlights the advantages of a smaller molecular weight derivatization agent for the detection of multi-carbonyl compounds. The use of TBOX derivatization if combined with other derivatization agents may address a recurring need to simply and accurately detect multi-functional oxygenated species in air.

The modifying effect of the building envelope on population exposure to PM2.5 from outdoor sources

A number of studies have estimated population exposure to PM2.5 by examining modeled or measured outdoor PM2.5 levels. However, few have taken into account the mediating effects of building characteristics on the ingress of PM2.5 from outdoor sources and its impact on population exposure in the indoor domestic environment. This study describes how building simulation can be used to determine the indoor concentration of outdoor-sourced pollution for different housing typologies and how the results can be mapped using building stock models and Geographical Information Systems software to demonstrate the modifying effect of dwellings on occupant exposure to PM2.5 across London. Building archetypes broadly representative of those in the Greater London Authority were simulated for pollution infiltration using EnergyPlus. In addition, the influence of occupant behavior on indoor levels of PM2.5 from outdoor sources was examined using a temperature-dependent window-opening scenario. Results demonstrate a range of I/O ratios of PM2.5 , with detached and semi-detached dwellings most vulnerable to high levels of infiltration. When the results are mapped, central London shows lower I/O ratios of PM2.5 compared with outer London, an apparent inversion of exposure most likely caused by the prevalence of flats rather than detached or semi-detached properties.

PRACTICAL IMPLICATIONS

Population exposure to air pollution is typically evaluated using the outdoor concentration of pollutants and does not account for the fact that people in London spend over 80% of their time indoors. In this article, building simulation is used to model the infiltration of outdoor PM2.5 into the domestic indoor environment for dwellings in a London building stock model, and the results mapped. The results show the variation in relative vulnerability of dwellings to pollution infiltration, as well as an estimated absolute indoor concentration across the Greater London Authority (GLA) scaled by local outdoor levels. The practical application of this work is a better understanding of the modifying effect of the building geometry and envelope design on pollution exposure, and how the London building stock may alter exposure. The results will be used to inform population exposure to PM2.5 in future environmental epidemiological studies.

The microenvironmental modelling approach to assess children's exposure to air pollution - A review

Exposures to a wide spectrum of air pollutants were associated to several effects on children's health. Exposure assessment can be used to establish where and how air pollutants' exposures occur. However, a realistic estimation of children's exposures to air pollution is usually a great ethics challenge, especially for young children, because they cannot intentionally be exposed to contaminants and according to Helsinki declaration, they are not old enough to make a decision on their participation. Additionally, using adult surrogates introduces bias, since time-space-activity patterns are different from those of children. From all the different available approaches for exposure assessment, the microenvironmental (ME) modelling (indirect approach, where personal exposures are estimated or predicted from microenvironment measurements combined with time-activity data) seemed to be the best to assess children's exposure to air pollution as it takes into account the varying levels of pollution to which an individual is exposed during the course of the day, it is faster and less expensive. Thus, this review aimed to explore the use of the ME modelling approach methodology to assess children's exposure to air pollution. To meet this goal, a total of 152 articles, published since 2002, were identified and titles and abstracts were scanned for relevance. After exclusions, 26 articles were fully reviewed and main characteristics were detailed, namely: (i) study design and outcomes, including location, study population, calendar time, pollutants analysed and purpose; and (ii) data collection, including time-activity patterns (methods of collection, record time and key elements) and pollution measurements (microenvironments, methods of collection and duration and time resolution). The reviewed studies were from different parts of the world, confirming the worldwide application, and mostly cross-sectional. Longitudinal studies were also found enhancing the applicability of this approach. The application of this methodology on children is different from that on adults because of data collection, namely the methods used for collecting time-activity patterns must be different and the time-activity patterns are itself different, which leads to select different microenvironments to the data collection of pollutants' concentrations. The most used methods to gather information on time-activity patterns were questionnaires and diaries, and the main microenvironments considered were home and school (indoors and outdoors). Although the ME modelling approach in studies to assess children's exposure to air pollution is highly encouraged, a validation process is needed, due to the uncertainties associated with the application of this approach.

Surface emission determination of volatile organic compounds (VOC) from a closed industrial waste landfill using a self-designed static flux chamber

Closed landfills can be a source of VOC and odorous nuisances to their atmospheric surroundings. A self-designed cylindrical air flux chamber was used to measure VOC surface emissions in a closed industrial landfill located in Cerdanyola del Vallès, Catalonia, Spain. The two main objectives of the study were the evaluation of the performance of the chamber setup in typical measurement conditions and the determination of the emission rates of 60 different VOC from that industrial landfill, generating a valuable database that can be useful in future studies related to industrial landfill management. Triplicate samples were taken in five selected sampling points. VOC were sampled dynamically using multi-sorbent bed tubes (Carbotrap, Carbopack X, Carboxen 569) connected to SKC AirCheck 2000 pumps. The analysis was performed by automatic thermal desorption coupled with a capillary gas chromatograph/mass spectrometry detector. The emission rates of sixty VOC were calculated for each sampling point in an effort to characterize surface emissions. To calculate average, minimum and maximum emission values for each VOC, the results were analyzed by three different methods: Global, Kriging and Tributary area. Global and Tributary area methodologies presented similar values, with total VOC emissions of 237 ± 48 and 222 ± 46 g day(-1), respectively; however, Kriging values were lower, 77 ± 17 gd ay(-1). The main contributors to the total emission rate were aldehydes (nonanal and decanal), acetic acid, ketones (acetone), aromatic hydrocarbons and alcohols. Most aromatic hydrocarbon (except benzene, naphthalene and methylnaphthalenes) and aldehyde emission rates exhibited strong correlations with the rest of VOC of their family, indicating a possible common source of these compounds. B:T ratio obtained from the emission rates of the studied landfill suggested that the factors that regulate aromatic hydrocarbon distributions in the landfill emissions are different from the ones from urban areas. Environmental conditions (atmospheric pressure, temperature and relative humidity) did not alter the pollutant emission fluxes.