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Environmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.

the elderly --- regression analysis --- walking event --- green space --- missing data --- crop residue burning --- correlation analysis --- imputation --- physical environment --- crowdedness --- Guangzhou --- mobile phone data --- GPS trace --- noise pollution --- mental disorders --- Beijing --- urban leisure --- environmental exposure --- environmental context cube --- subway stations --- air pollution exposure --- long-distance walking --- car ownership --- multilevel model --- CHAS --- ecological momentary assessment --- cycling for transportation --- cognitive aging --- 3SFCA --- interannual and seasonal variations --- well-being experience --- personal projects --- spatial spread --- E2SFCA --- activity space --- catchment areas --- structural equation modeling --- transport modes --- greenspace exposure --- health --- train stations --- human mobility --- quantile regression --- the neighborhood effect averaging problem (NEAP) --- emissions estimation --- taxi GPS trajectories --- real-time traffic --- primary healthcare --- rail travel --- spatial accessibility --- commuting route --- GPS --- urban planning --- environmental health --- Brazil --- EMA --- geographical accessibility --- big data --- dynamic assessment --- obesity --- healthcare accessibility --- population demand --- the uncertain geographic context problem (UGCoP) --- geographic impedance --- collective leisure activity --- multimodal network --- GIS --- 2009 influenza A(H1N1) pandemic --- UGCoP --- environmental exposures --- spatial data --- the uncertain geographic context problem --- Singapore --- built environment --- adults --- time-weighted exposure --- geographic imputation --- Public Participatory GIS (PPGIS) --- access probability --- life-course perspectives --- China --- walking --- active travel --- foodscape exposure --- car use --- food environment --- fuel consumption --- ageing --- Healthcare services --- road traffic accidents --- space-time kernel density estimation --- multilevel Bayesian model --- environmental context exposure index --- spatial autocorrelation --- PM concentrations --- physical activity --- bike paths

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The book “Integrated human exposure to air pollution” aimed to increase knowledge about human exposure in different micro-environments, or when citizens are performing specific tasks, to demonstrate methodologies for the understanding of pollution sources and their impact on indoor and ambient air quality, and, ultimately, to identify the most effective mitigation measures to decrease human exposure and protect public health. Taking advantage of the latest available tools, such as internet of things (IoT), low-cost sensors and a wide access to online platforms and apps by the citizens, new methodologies and approaches can be implemented to understand which factors can influence human exposure to air pollution. This knowledge, when made available to the citizens, along with the awareness of the impact of air pollution on human life and earth systems, can empower them to act, individually or collectively, to promote behavioral changes aiming to reduce pollutants’ emissions. Overall, this book gathers fourteen innovative studies that provide new insights regarding these important topics within the scope of human exposure to air pollution. A total of five main areas were discussed and explored within this book and, hopefully, can contribute to the advance of knowledge in this field.

Research & information: general --- Biology, life sciences --- Personal Air Pollution Exposure (PAPE) --- air pollution monitoring --- IoT --- Air Quality Decision Support System --- health impact --- air pollution --- public concern --- air quality index --- Baidu index --- Shanghai --- air quality --- crowd-sensing --- crowd-sourced sensing --- environmental analysis --- pollution --- particulate matter --- dust sensor --- human exposure --- Arduino --- wireless networks --- oxides --- traffic --- state space --- milan --- area b --- cross validation --- policy intervention analysis --- counter-factual --- unobservable components --- PM2.5 --- population exposure --- tier-models --- health burden misclassification --- BenMap-CE --- tuberculosis --- infectious disease --- time-series --- Poisson regression --- kriging --- road dust --- PM10 emission factors --- enrichment index --- human health risk --- atmospheric aerosols --- bioaerosols --- culturable bacteria --- long-term trends --- hazard for human --- indoor air quality --- e-cigarettes --- heat-not-burn tobacco --- traditional smoking products --- tobacco smoke --- passenger cars --- lung inflammation --- allergy --- indoor pollutants --- biomarkers --- FeNO --- eosinophil --- neutrophil --- fine particulate matter --- economic growth --- urbanization --- industrialization --- Granger causality test --- air pollutants --- monitoring --- seasonality --- chemical characterization --- source apportionment --- particulate matters (PM) --- air purifier --- experiment --- real-time monitoring unit --- transfer unit --- occupant --- breathing zone --- cooking fuel --- household air pollution --- preterm births --- perinatal mortality --- low birth weight --- stillbirth --- Nigeria