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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 --- 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
Choose an application
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.
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 --- n/a
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