scholarly journals Air pollution exposure monitoring using portable low-cost air quality sensors

Smart Health ◽  
2021 ◽  
pp. 100241
Author(s):  
Pranvera Korto¸ci ◽  
Naser Hossein Motlagh ◽  
Martha Arbayani Zaidan ◽  
Pak Lun Fung ◽  
Samu Varjonen ◽  
...  
Author(s):  
Keith April G. Arano ◽  
Shengjing Sun ◽  
Joaquin Ordieres-Mere ◽  
and Bing Gong

This paper proposes a framework for an Air Quality Decision Support System (AQDSS), and as a proof of concept, develops an Internet of Things (IoT) application based on this framework. This application was assessed by means of a case study in the City of Madrid. We employed different sensors and combined outdoor and indoor data with spatiotemporal activity patterns to estimate the Personal Air Pollution Exposure (PAPE) of an individual. This pilot case study presents evidence that PAPE can be estimated by employing indoor air quality monitors and e-beacon technology that have not previously been used in similar studies and have the advantages of being low-cost and unobtrusive to the individual. In future work, our IoT application can be extended to include prediction models, enabling dynamic feedback about PAPE risks. Furthermore, PAPE data from this type of application could be useful for air quality policy development as well as in epidemiological studies that explore the effects of air pollution on certain diseases.


1999 ◽  
Vol 1 (4) ◽  
pp. 327-332
Author(s):  
Cristina Guerreiro ◽  
Jocelyne Clench-Aas ◽  
Alena Bartonova

2016 ◽  
Vol 59 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Sally Radisic ◽  
K. Bruce Newbold ◽  
John Eyles ◽  
Allison Williams

Research associating adverse health effects with air pollution exposure is robust. Public health authorities recognize the need to implement population health strategies that protect public health from air pollution exposure. The Air Quality Health Index (AQHI) is a public health initiative that is intended to protect the public's health from exposure to air pollution. The aim of this research was to identify and explain factors influencing AQHI adoption at the individual level and to establish intervention strategies. A cross-sectional survey with both quantitative and qualitative questions was administered in Hamilton, Ontario, Canada, during the months of June to October 2012. Logistic regression and the Health Belief Model are used to explore the data. Demographics (gender, age, education, and area of residence), knowledge/understanding, and individual risk perceptions (neighbourhood air effects on health) were found to be significant predictors of AQHI adoption. The perceived benefits of AQHI adoption included protection of health for self and those cared for via familial and (or) occupational duties, whereas the perceived barriers of AQHI adoption included lack of knowledge about where to check and lack of time required to check and follow AQHI health messages. Also, self-efficacy was uncovered as a factor influencing AQHI adoption. Accordingly, increases in AQHI adoption could be achieved via increasing AQHI knowledge among low socioeconomic status females, communicating the benefits of AQHI adoption to “at-risk” populations and implementing supports for males to follow AQHI health messages.


1999 ◽  
Vol 1 (4) ◽  
pp. 341-347 ◽  
Author(s):  
Jocelyne Clench-Aas ◽  
Alena Bartonova ◽  
Knut E. Grønskei ◽  
Leif O. Hagen ◽  
Ole-Anders Braathen ◽  
...  

2020 ◽  
Vol 28 (3) ◽  
pp. 3296-3306
Author(s):  
Li Shang ◽  
Liyan Huang ◽  
Liren Yang ◽  
Longtao Leng ◽  
Cuifang Qi ◽  
...  

AbstractPrevious studies have suggested that maternal exposure to air pollution might affect term birth weight. However, the conclusions are controversial. Birth data of all term newborns born in Xi’an city of Shaanxi, China, from 2015 to 2018 and whose mother lived in Xi’an during pregnancy were selected form the Birth Registry Database. And the daily air quality data of Xi’an city was collected from Chinese Air Quality Online Monitoring and Analysis Platform. Generalized additive models (GAM) and 2-level binary logistic regression models were used to estimate the effects of air pollution exposure on term birth weight, the risk term low birth weight (TLBW), and macrosomia. Finally, 321521 term newborns were selected, including 4369(1.36%) TLBW infants and 24,960 (7.76%) macrosomia. The average pollution levels of PM2.5, PM10, and NO2 in Xi’an city from 2015 to 2018 were higher than national limits. During the whole pregnancy, maternal exposure to PM2.5, PM10, SO2, and CO all significantly reduced the term birth weight and increased the risk of TLBW. However, NO2 and O3 exposure have significantly increased the term birth weight, and O3 even increased the risk of macrosomia significantly. Those effects were also observed in the first and second trimesters of pregnancy. But during the third trimester, high level of air quality index (AQI) and maternal exposure to PM2.5, PM10, SO2, NO2, and CO increased the term birth weight and the risk of macrosomia, while O3 exposure was contrary to this effect. The findings suggested that prenatal exposure to air pollution might cause adverse impacts on term birth weight, and the effects varied with trimesters and pollutants, which provides further pieces of evidence for the adverse effects of air pollution exposure in heavy polluted-area on term birth weight.


2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
E Ceretti ◽  
F Donato ◽  
D Feretti ◽  
A Carducci ◽  
M Moretti ◽  
...  

Abstract Background Children are at high risk of suffering health consequences of air pollution and childhood exposure can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE project, funded by EU Life+ Programme (LIFE12 ENV/IT/000614), aimed to evaluate the association between air pollution exposure and biomarkers of early effect in children and to propose guidance for implementing environmental policies. Methods The study was carried out on 6-8-year-old children. Micronucleus (MN) frequency was investigated in buccal cells of children and its association with air pollution exposure was assessed applying multiple Poisson regression mixed models, including socio-demographic and lifestyle factors as confounders. We also dichotomize air pollutants concentration according to the EU Ambient Air Quality Directives and WHO Air Quality Guidelines in all Poisson regression models to assess their risk predictive capacity. Results The project involved 1149 children providing buccal cells in winter and spring. 2139 biological samples were included in the analysis (1093 collected in winter, 1046 in spring). The analysis of the association between MN frequency and air quality parameters found positive associations for PM10, PM2.5, benzene, SO2 and ozone. Considering EU Directives, an association was found between MN frequency and PM10 exposure higher than the annual limit value, with an increase of the risk of 17.9% (95%CIs: 0.6-38.1%). Considering WHO Guidelines, the exposures to levels of PM10, benzene and BaP higher than the annual limits were associated with MN frequency, with a risk increase of 22.5%, 27.8% and 59.8% (95%CIs: 3.9-44.3%, 3.8-57.3%, 21.0-111.1%), respectively. Conclusions The analyses conducted showed an association between MN frequency in buccal cells of children and levels of some air pollutants, even at concentration below EU and WHO thresholds, which hence seemed to be insufficient for protecting children from this type of damage. Key messages Air pollution exposure induced chromosomal damage in buccal cells of children, even at concentration below the law limits. Early biological damage detected might be predictive of the occurrence of future harmful effects in humans, at a population level.


1999 ◽  
Vol 1 (4) ◽  
pp. 333-336 ◽  
Author(s):  
Jocelyne Clench-Aas ◽  
Alena Bartonova ◽  
Knut E. Grønskei ◽  
Sam-Erik Walker

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