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Dynamic assessment of exposure to air pollution using mobile phone data

Overview of attention for article published in International Journal of Health Geographics, April 2016
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  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

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6 tweeters
facebook
1 Facebook page

Citations

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68 Dimensions

Readers on

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153 Mendeley
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Title
Dynamic assessment of exposure to air pollution using mobile phone data
Published in
International Journal of Health Geographics, April 2016
DOI 10.1186/s12942-016-0042-z
Pubmed ID
Authors

Bart Dewulf, Tijs Neutens, Wouter Lefebvre, Gerdy Seynaeve, Charlotte Vanpoucke, Carolien Beckx, Nico Van de Weghe

Abstract

Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments. In this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach). The mean exposure to NO2 increases with 1.27 μg/m(3) (4.3 %) during the week and with 0.12 μg/m(3) (0.4 %) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations. It is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones).

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 1%
Canada 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Belgium 1 <1%
Spain 1 <1%
Poland 1 <1%
Unknown 145 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 28%
Researcher 24 16%
Student > Master 16 10%
Student > Doctoral Student 13 8%
Student > Bachelor 11 7%
Other 22 14%
Unknown 24 16%
Readers by discipline Count As %
Environmental Science 36 24%
Social Sciences 22 14%
Computer Science 10 7%
Medicine and Dentistry 9 6%
Engineering 8 5%
Other 30 20%
Unknown 38 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2016.
All research outputs
#3,646,664
of 13,893,500 outputs
Outputs from International Journal of Health Geographics
#147
of 501 outputs
Outputs of similar age
#74,806
of 262,187 outputs
Outputs of similar age from International Journal of Health Geographics
#1
of 1 outputs
Altmetric has tracked 13,893,500 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 501 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,187 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them