Particulate matter (PM) air pollution has been identified as one cause of human health impact with the estimated global 8.8 million attributable deaths. Thailand experiences haze episode every year, which can lead to high ambient concentrations of particulate matter in ambient air. This study aims to investigate the relationship of indoor and outdoor air quality in both haze and non-haze period in two cities in Thailand: namely Bangkok and Chiang Mai. We conducted the air quality sampling in various styles of house, with 17 houses in both urban and rural areas, between April to October 2019. The results indicated that the concentration of PM2.5 in indoor air in Bangkok were 19.85 and 11.40 μg/m3 for haze and non-haze period, respectively, whereas the PM10 concentrations were 32.124 and 17.49 μg/m3 for haze and non-haze period, respectively. The corresponding average of outdoor air concentrations were 26.26 and 16.68 μg/m3 for haze and non-haze, respectively. While the PM10 concentrations were 46.36 and 23.86 μg/m3 for haze and non-haze period, respectively. In Chiang Mai, it was observed that the mean concentration of PM2.5 in indoor was 106.80 μg/m3 and 5.52 μg/m3 for haze and non-haze periods, respectively. Regarding PM10, it was observed that the mean concentration in indoor was 118.54 μg/m3 and 9.74 μg/m3 for haze and non-haze periods, respectively. Indoor/Outdoor (I/O) ratios of PM2.5 varied in Bangkok average was 0.76 for haze and 0.68 for non-haze period. The I/O ratio in Chiang Mai was 0.91 and 1.16 for haze and non-haze episode, respectively. Indoor/Outdoor (I/O) ratios of PM10 varied in Bangkok average was 0.70 for haze and 0.73 for non-haze period. The I/O ratio in Chiang Mai was 0.92 and 0.96 for haze and non-haze episode, respectively Our findings indicated the influences of outdoor air quality on indoor air quality during both haze and non-haze episode. The intrusion of outdoor air in Chiang Mai to the houses caused a higher I/O ratio than Bangkok due to the characteristics of house and culture. The indoor air quality in terms of particulate matter were dominated by outdoor air quality. Thus, people should close doors/windows during the haze as well as non-haze episode to avoiding the pollutant accumulation.

Introduction Characterizing the external exposome requires a combination of different measurement methods for multiple exposures. Objectives We describe the development of an external exposome assessment system for the EPHOR study, which focuses on cohorts for assessing working life exposures, particularly one case study on shift work and one on respiratory health. The system will be implemented in a weeklong intensive nested study. Methods A system of measurement using low-cost sensors, passive sampling methods, and a mobile phone app was developed and trialed. The low-cost sensor measures light, UV, noise, particulate matter, temperature and humidity in a high temporal resolution. Additionally, separate activity and heart rate monitors are added to the data stream. Passive sampling is used for a wide spectrum of chemical and biological agents. The phone app is used for asking a set of questions related to health and exposure factors on a daily basis. The low-cost sensor performance was compared to reference monitors in both a controlled laboratory setting (static) and in a free living setting (personal). Results Initial tests of the low-cost sensor system indicates that correlations with reference monitors are high for controlled laboratory tests but more variable when used in personal monitoring. Additional calibration may be necessary throughout the project, especially for particulate matter, with the possibility of using the raw sensor data (particle numbers of various sizes) calculating mass concentration. Conclusion A comprehensive protocol to measure the external exposome has been developed. Next steps include the development of external exposome profiles based on the collected data for use in exposure response analysis for various outcomes. It can be challenging to develop a one-size-fits-all external exposome system for exposome studies with different objectives. A flexible platform that can incorporate different sensors or measurement methods is an important feature of external exposome measurement systems.

Particulate air pollution causes a spectrum of adverse health effects affecting the respiratory, cardiovascular, neurological, and metabolic systems that are hypothesised to be driven by inflammation and oxidative stress. Millions of premature deaths each year are attributed to exposure to ambient particulate matter (PM). We quantified health and economic impacts from long-term exposure to ambient PM 2.5 in the population of Thailand for 2016. We collected data on ambient PM 2.5 concentrations from automatic monitoring stations across Thailand over 1996–2016. We used historic exposure to PM 2.5 to estimate the mortality in each province from lower respiratory infections (LRIs), stroke, chronic obstructive pulmonary disease, lung cancer, and ischaemic heart disease, and also assessed diabetes mortality, as well as incident cases of dementia and Parkinson’s disease, in supplementary analyses. We applied risk estimates from the Global Exposure Mortality Model to calculate attributable mortality and quantify disability-adjusted life years (DALYs); we based economic costs on the value of a statistical life (VSL). We calculated 50 019 (95% confidence interval [CI]: 42 189–57 849) deaths and 508 918 (95% CI: 438 345–579 492) DALYs in 2016 attributed to long-term PM 2.5 exposure in Thailand. Population attributable fractions ranged from 20% (95% CI: 10% to 29%) for stroke to 48% (95% CI: 27% to 63%) for LRIs. Based on the VSL, we calculated a cost of US$ 60.9 billion (95% CI: US$ 51.3–70.4 billion), which represents nearly 15% of Thailand’s gross domestic product in 2016. While progress has been made to reduce exposure to ambient PM 2.5 in Thailand, continued reductions based on stricter regulatory limits for PM 2.5 and other air pollutants would help prolong life, and delay, or prevent, onset of cardiorespiratory and other diseases.

Background Greenspace has been associated with health benefits in many contexts. An important pathway may be through outdoor physical activity. We use a novel approach to examine the link between greenspace microenvironments and outdoor physical activity levels in the HEALS study conducted in Edinburgh (UK), the Netherlands, and Athens and Thessaloniki (Greece). Methods Using physical activity tracker recordings, 118 HEALS participants with young children were classified with regard to daily minutes of moderate to vigorous physical activity (MVPA); 60 were classified with regard to the metabolic equivalent task (MET)-minutes for each of the 1014 active trips they made. Greenspace indicators were generated for Normalised Difference Vegetation Index (NDVI), tree cover density (TCD), and green land use (GLU). We employed linear mixed-effects models to analyse (1) daily MVPA in relation to greenspace within 300 m and 1000 m of residential addresses and (2) trip MET-minutes in relation to average greenspace within a 50 m buffer of walking/cycling routes. Models were adjusted for activity, walkability, bluespace, age, sex, car ownership, dog ownership, season, weekday/weekend day, and local meteorology. Results There was no clear association between MVPA-minutes and any residential greenspace measure. For example, in fully adjusted models, a 10 percentage point increase in NDVI within 300 m of home was associated with a daily increase of 1.14 (95% CI − 0.41 to 2.70) minutes of MVPA. However, we did find evidence to indicate greenspace markers were positively linked to intensity and duration of activity: in fully adjusted models, 10 percentage point increases in trip NDVI, TCD, and GLU were associated with increases of 10.4 (95% CI: 4.43 to 16.4), 10.6 (95% CI: 4.96 to 16.3), and 3.36 (95% CI: 0.00 to 6.72) MET-minutes, respectively. The magnitude of associations with greenspace tended to be greater for cycling. Conclusions More strenuous or longer walking and cycling trips occurred in environments with more greenspace, but levels of residential greenspace did not have a clear link with outdoor MVPA. To build on our research, we suggest future work examine larger, more diverse populations and investigate the influence of greenspace for trip purpose and route preference.

Background There is a growing evidence that exposure to ambient particulate air pollution during pregnancy is associated with adverse birth outcomes, including reduced birth weight (BW). The objective of this study was to quantify associations between BW and exposure to particulate matter (PM) and biomass burning during pregnancy in Thailand. Methods We collected hourly ambient air pollutant data from ground-based monitors (PM with diameter of <10 µm [PM 10 ], Ozone [O 3 ], and nitrogen dioxide [NO 2 ]), biomass burning from satellite remote sensing data, and individual birth weight data during 2015–2018. We performed a semi-ecological analysis to evaluate the association between mean trimester exposure to air pollutants and biomass burning with BW and low-birth weight (LBW) (<2500 g), adjusting for gestation age, sex, previous pregnancies, mother’s age, heat index, season, year, gaseous pollutant concentrations, and province. We examined potential effect modification of PM 10 and biomass burning exposures by sex. Results There were 83,931 eligible births with a mean pregnancy PM 10 exposure of 39.7 µg/m 3 (standard deviation [SD] = 7.7). The entire pregnancy exposure was associated with reduced BW both for PM 10 (−6.81 g per 10 µg/m 3 increase in PM 10 [95% CI = −12.52 to −1.10]) and biomass burning (−6.34 g per 1 SD increase in fires/km 2 [95% CI = −11.35 to −1.34]) only after adjustment for NO 2 . In contrast with these findings, a reduced odds ratio (OR) of LBW was associated with PM 10 exposure only in trimesters one and two, with no relationship across the entire pregnancy period. Associations with biomass burning were limited to increased ORs of LBW with exposure in trimester three, but only for male births. Conclusion Based on our results, we encourage further investigation of air pollution, biomass burning and BW in Thailand and other low-income and middle-income countries.

Objectives: This systematic review aimed to evaluate the evidence for air and surface contamination of workplace environments with SARS-CoV-2 RNA and the quality of the methods used to identify actions necessary to improve the quality of the data. Methods: We searched Web of Science and Google Scholar until 24 December 2020 for relevant articles and extracted data on methodology and results. Results: The vast majority of data come from healthcare settings, with typically around 6% of samples having detectable concentrations of SARS-CoV-2 RNA and almost none of the samples collected had viable virus.There were a wide variety of methods used to measure airborne virus, although surface sampling was generally undertaken using nylon flocked swabs. Overall, the quality of the measurements was poor. Only a small number of studies reported the airborne concentration of SARS-CoV-2 virus RNA, mostly just reporting the detectable concentration values without reference to the detection limit. Imputing the geometric mean air concentration assuming the limit of detection was the lowest reported value, suggests typical concentrations in healthcare settings may be around 0.01 SARS-CoV-2 virus RNA copies m -3 . Data on surface virus loading per unit area were mostly unavailable. Conclusions: The reliability of the reported data is uncertain.The methods used for measuring SARS-CoV-2 and other respiratory viruses in work environments should be standardized to facilitate more consistent interpretation of contamination and to help reliably estimate worker exposure.

In high-income countries, and increasingly in lower- and middle-income countries, chronic non-communicable diseases (NCDs) have become the primary health burden. It is possible that in utero exposure to environmental pollutants such as particulate matter (PM) may have an impact on health later in life, including the development of NCDs. Due to a lack of data on foetal growth, birth weight is often used in epidemiologic studies as a proxy to assess impacts on foetal development and adverse birth outcomes since it is commonly recorded at birth. There are no research studies with humans that directly link PM exposure in utero to birth weight (BW) and subsequently, the effects of lower BW on health outcomes in old age. It is, however, plausible that such associations exist, and it is thus important to assess the potential public health impacts of PM across the life course, and it is plausible to use birth weight as an indicator of risk. We therefore split this narrative review into two parts. In the first part, we evaluated the strength of the evidence on the impact of PM exposure during the entire pregnancy on birth weight outcomes in ten meta-analyses. In the second part, we reviewed the literature linking lower birth weight to childhood and adult chronic cardiovascular disease to explore the potential implications of PM exposure in utero on health later in life. Within the reviewed meta-studies on birth weight, there is sufficient evidence that PM pollution is associated with lower birth weight, i.e., the majority of meta-studies found statistically significant reductions in birth weight. From the second part of the review, it is evident that there is good evidence of associations between lower birth weight and subsequent cardiovascular disease risk. It is thus plausible that in utero exposure to PM is associated with lower birth weight and persisting biological changes that could be associated with adverse health effects in adulthood. Based on the reviewed evidence, however, the magnitude of later life cardiovascular health impacts from in utero exposure and its impact on BW are likely to be small compared to health effects from exposure to particulate air pollution over a whole lifetime.

Background/Aim: The exposome includes urban greenspace, which may affect health via a complex set of pathways, including reducing exposure to particulate matter (PM) and noise. We assessed these pathways using indoor exposure monitoring data from the HEALS study in four European urban areas (Edinburgh, UK; Utrecht, Netherlands; Athens and Thessaloniki, Greece). Methods: We quantified three metrics of residential greenspace at 50 m and 100 m buffers: Normalised Difference Vegetation Index (NDVI), annual tree cover density, and surrounding green land use. NDVI values were generated for both summer and the season during which the monitoring took place. Indoor PM2.5 and noise levels were measured by Dylos and Netatmo sensors, respectively, and subjective noise annoyance was collected by questionnaire on an 11-point scale. We used random-effects generalised least squares regression models to assess associations between greenspace and indoor PM2.5 and noise, and an ordinal logistic regression to model the relationship between greenspace and road noise annoyance. Results: We identified a significant inverse relationship between summer NDVI and indoor PM2.5 (-1.27 mu g/m(3) per 0.1 unit increase [95% CI -2.38 to -0.15]) using a 100 m residential buffer. Reduced (i.e., < 1.0) odds ratios (OR) of road noise annoyance were associated with increasing summer (OR = 0.55 [0.31 to 0.98]) and season specific (OR = 0.55 [0.32 to 0.94]) NDVI levels, and tree cover density (OR = 0.54 [0.31 to 0.93] per 10 percentage point increase), also at a 100 m buffer. In contrast to these findings, we did not identify any significant associations between greenspace and indoor noise in fully adjusted models. Conclusions: We identified reduced indoor levels of PM2.5 and noise annoyance, but not overall noise, with increasing outdoor levels of certain greenspace indicators. To corroborate our findings, future research should examine the effect of enhanced temporal resolution of greenspace metrics during different seasons, characterise the configuration and composition of green areas, and explore mechanisms through mediation modelling.

(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 (PM2.5 and PM10); nitrogen dioxide (NO2); volatile organic compounds (VOCs) including benzene, toluene, xylenes and formaldehyde; and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Identified indoor PM2.5 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 PM2.5 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 PM2.5, 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.

The aim of this study was to (a) develop a method for converting particle number concentrations (PNC) obtained by Dylos to PM2.5 mass concentrations, (b) compare this conversion with similar methods available in the literature, and (c) compare Dylos PM2.5 obtained using all available conversion methods with gravimetric samples. Data were collected in multiple residences in three European countries using the Dylos and an Aerodynamic Particle Sizer (APS, TSI) in the Netherlands or an optical particle counter (OPC, GRIMM) in Greece. Two statistical fitted curves were developed based on Dylos PNC and either an APS or an OPC particle mass concentrations (PMC). In addition, at the homes of 16 volunteers (UK and Netherlands), Dylos measurements were collected along with gravimetric samples. The Dylos PNC were transformed to PMC using all the fitted curves obtained during this study (and three found in the literature) and were compared with gravimetric samples. The method developed in the present study using an OPC showed the highest correlation (Pearson (R) = 0.63, Concordance (ρc ) = 0.61) with gravimetric data. The other methods resulted in an underestimation of PMC compared to gravimetric measurements (R = 0.65-0.55, ρc  = 0.51-0.24). In conclusion, estimation of PM2.5 concentrations using the Dylos is acceptable for indicative purposes.

Purpose of Review A large body of epidemiological evidence demonstrates that exposure to particulate matter (PM) is associated with increased morbidity and mortality. Many epidemiology studies have investigated the health effects of PM in Europe and North America and focussed on traffic derived PM. However, elevated levels of PM are a global problem and the impacts of other sources of PM on health should be assessed. Biomass burning can increase PM levels in urban and rural indoor and outdoor environments in developed and developing countries. We aim to identify whether the health effects of traffic and biomass burning derived PM are similar by performing a narrative literature review. We focus on Thailand as haze episodes from agricultural biomass burning can substantially increase PM levels. Recent Findings Existing epidemiology, in vitro and in vivo studies suggest that biomass burning derived PM elicits toxicity via stimulation of oxidative stress, inflammation and genotoxicity. Thus, it is likely to cause similar adverse health outcomes to traffic PM, which causes toxicity via similar mechanisms. However, there is conflicting evidence regarding whether traffic or biomass burning derived PM is most hazardous. Also, there is evidence that PM released from different biomass sources varies in its toxic potency. Summary We recommend that epidemiology studies are performed in Thailand to better understand the impacts of PM emitted from specific biomass sources (e.g. agricultural burning). Further, experimental studies should assess the toxicity of PM emitted from more diverse biomass sources. This will fill knowledge gaps and inform evidence-based interventions that protect human health.

Inhalation of ash can be of great concern for affected communities, during and after volcanic eruptions. Governmental and humanitarian agencies recommend and distribute a variety of respiratory protection (RP), most commonly surgical masks. However, there is currently no evidence on how effective such masks are in protecting wearers from volcanic ash. In Part I of this study (Mueller et al., 2018), we assessed the filtration efficiency (FE) of 17 materials from different forms of RP against volcanic ash and a surrogate, low-toxicity dust, Aloxite. Based on those results, we now present the findings from a volunteer simulation study to test the effect of facial fit through assessment of Total Inward Leakage (TIL). Four different disposable RP types that demonstrated very high median FE (>= 96% for Aloxite; >= 89% for volcanic ash) were tested without provision of training on fit. These were an industry-certified mask (N95-equiv.); a surgical mask from Japan designed to filter PM2.5; a flat-fold basic mask from Indonesia; and a standard surgical mask from Mexico, which was also tested with an added medical bandage on top, as an additional intervention to improve fit. Ten volunteers (6 female, 4 male) were recruited. Each RP type was worn by volunteers under two different conditions simulating cleaning-up activities during/after volcanic ashfall. Each activity lasted 10 min and two repeats were completed for each RP type per activity. Dust (as PM2.5) concentration inside and outside the mask was measured with two TSI SidePak aerosol monitors (Models AM510 and AM520, TSI, Minnesota, USA) to calculate TIL. A questionnaire was administered after each test to collect perceptions of fit, comfort, protection and breathability. The best-performing RP type, across both activities, was the industry-certified N95-equiv. mask with 9% mean TIL. The standard surgical mask and the basic flat-fold mask both performed worst (35% TIL). With the additional bandage intervention, the surgical mask mean TIL improved to 24%. The PM2.5 surgical mask performed similarly, with 22% TIL. The N95-equiv. mask was perceived to provide the best protection, but was also perceived as being uncomfortable and more difficult to breathe through. This study provides a first objective evidence base for the effectiveness of a selection of RP types typically worn around the world during volcanic crises. The findings will help agencies to make informed decisions on the procurement and distribution of RP in future eruptions.

Background: Air pollution is an important preventable cause of illness and disease around the world.Objective: To assess trends in the concentrations of different air pollutants in Thailand across three decades and to make a preliminary assessment of associated health impacts from prolonged exposures.Methods: We collected data from the Thai Pollution Control Department on CO, NO2, O3, PM10, PM2.5, and SO2 from 68 automatic monitoring stations across Thailand, spanning the period from 1996 to 2015. We calculated annual averages of each pollutant and assessed the magnitude and direction of pollutant concentration changes over time. We will combine this historic exposure data with health data, to be provided by the Ministry of Public Health, to conduct a health impact assessment (HIA), based on longer-term exposures, of current disease burdens for select causes of mortality and morbidity.Results: Data were available for each year of the study period from 30 monitoring stations. Reductions in annual mean concentrations were observed for CO (0.88 ppm to 0.70 ppm; -20%), SO2 (5.4 ppb to 2.4 ppb; -56%), and PM10 (90.6 µg/m3 to 44.2 µg/m3; -51%). Concentrations remained similar for NO2 (15.1 ppb to 15.9 ppb; +5%) and increased for both O3 (14.0 ppb to 21.2 ppb; +51%) and PM2.5, though monitoring for the latter only commenced in 2011 (22.5 µg/m3 to 31.1 µg/m3; +38%).Conclusion: Preliminary analysis suggests mixed air quality trends in Thailand in recent decades. Although some improvements are apparent, there is an indication that certain pollutants, i.e., PM2.5 and O3, still may be rising, which will entail adverse health consequences. For further analysis, we will complete a HIA using historic exposure trends, and, taking into account the introduction of air quality policies, we will estimate scenarios of air quality and health in the future.

Objectives Many residents in Beijing use disposable face masks in an attempt to protect their health from high particulate matter (PM) concentrations. Retail masks may be certified to local or international standards, but their real-life performance may not confer the exposure reduction potential that is marketed. This study aimed to evaluate the effectiveness of a range of face masks that are commercially available in China. Methods Nine masks claiming protection against fine PM (PM2.5) were purchased from consumer outlets in Beijing. The masks’ filtration efficiency was tested by drawing airborne diesel exhaust through a section of the material and measuring the PM2.5 and black carbon (BC) concentrations upstream and downstream of the filtering medium. Four masks were selected for testing on volunteers. Volunteers were exposed to diesel exhaust inside an experimental chamber while performing sedentary tasks and active tasks. BC concentrations were continuously monitored inside and outside the mask. Results The mean per cent penetration for each mask material ranged from 0.26% to 29%, depending on the flow rate and mask material. In the volunteer tests, the average total inward leakage (TIL) of BC ranged from 3% to 68% in the sedentary tests and from 7% to 66% in the active tests. Only one mask type tested showed an average TIL of less than 10%, under both test conditions. Conclusions Many commercially available face masks may not provide adequate protection, primarily due to poor facial fit. Our results indicate that further attention should be given to mask design and providing evidence-based guidance to consumers.

During volcanic eruptions and their aftermath, communities may be concemed about the impacts of inhaling volcanic ash. Access to effective respiratory protection (RP) is therefore important for many people in volcanic areas all over the world. However, evidence to support the use of effective RP during such crises is currently lacking. The aim of this study was to build the first evidence base on the effectiveness of common materials used to protect communities from ash inhalation in volcanic crises. We obtained 17 forms of RP, covering various types of cloth through to disposable masks (typically used in occupational settings), which communities are known to wear during volcanic crises. The RP materials were characterised and subjected to filtration efficiency (FE) tests, which were performed with three challenge dusts: ashes from Sakurajima (Japan) and Soufriere Hills (Montserrat) volcanoes and aluminium oxide (Aloxite), chosen as a low-toxicity surrogate dust of similar particle size distribution. FE tests were conducted at two concentrations (1.5 mg/m(3) and 2.5 mg/m(3)) and two flow rates (equivalent to 40 and 801/min through 15.9 cm(2) sections of each RP type). Each material was held in a sample holder and PM2.5 dust concentrations were measured both outside the mask material and inside the sample holder to determine FE. A limited number of tests were undertaken to assess the effect on FE of wetting a bandana and a surgical mask, as well as folding a bandana to provide multiple filter layers. Overall, four RP materials performed very well against volcanic ash, with median FEs in excess of 98% (N95-equiv., N99-equiv., PM2.5 surgical (Japan), and Basic flat-fold (Indonesia)). The two standard surgical masks tested had median FEs of 89-91%. All other materials had median FEs ranging from 23 to 76% with no cloth materials achieving > 44%. Folding a bandana resulted in better FE (40%; 3 x folded) than single-layered material (29%). Wetting the bandana and surgical mask material did not improve FE overall. This first evidence base on the FE of common materials used to protect communities in volcanic crises from ash inhalation has been extended in a companion study (Steinle et al., 2018) on the total inward leakage of the best-performing masks when worn by human volunteers. This will provide a complete assessment of the effectiveness of these RP types.

Scientific investigations have progressively refined our understanding of the influence of the environment on human health, and the many adverse impacts that human activities exert on the environment, from the local to the planetary level. Nonetheless, throughout the modern public health era, health has been pursued as though our lives and lifestyles are disconnected from ecosystems and their component organisms. The inadequacy of the societal and public health response to obesity, health inequities, and especially global environmental and climate change now calls for an ecological approach which addresses human activity in all its social, economic and cultural complexity. The new approach must be integral to, and interactive, with the natural environment. We see the continuing failure to truly integrate human health and environmental impact analysis as deeply damaging, and we propose a new conceptual model, the ecosystems-enriched Drivers, Pressures, State, Exposure, Effects, Actions or 'eDPSEEA' model, to address this shortcoming. The model recognizes convergence between the concept of ecosystems services which provides a human health and well-being slant to the value of ecosystems while equally emphasizing the health of the environment, and the growing calls for 'ecological public health' as a response to global environmental concerns now suffusing the discourse in public health. More revolution than evolution, ecological public health will demand new perspectives regarding the interconnections among society, the economy, the environment and our health and well-being. Success must be built on collaborations between the disparate scientific communities of the environmental sciences and public health as well as interactions with social scientists, economists and the legal profession. It will require outreach to political and other stakeholders including a currently largely disengaged general public. The need for an effective and robust science-policy interface has never been more pressing. Conceptual models can facilitate this by providing theoretical frameworks and supporting stakeholder engagement process simplifications for inherently complex situations involving environment and human health and well-being. They can be tools to think with, to engage, to communicate and to help navigate in a sea of complexity. We believe models such as eDPSEEA can help frame many of the issues which have become the challenges of the new public health era and can provide the essential platforms necessary for progress.

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing ‘Big Data’ and, more importantly, make the vital step from ‘Big Data’ to ‘Big Information’. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example. Crown Copyright © 2015 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing ‘Big Data’ and, more importantly, make the vital step from ‘Big Data’ to ‘Big Information’. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example.

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.