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Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment

Overview of attention for article published in Environmental Health, November 2013
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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4 X users
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1 Facebook page

Citations

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52 Dimensions

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151 Mendeley
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Title
Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment
Published in
Environmental Health, November 2013
DOI 10.1186/1476-069x-12-93
Pubmed ID
Authors

Hai-Ying Liu, Erik Skjetne, Mike Kobernus

Abstract

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 1%
Tanzania, United Republic of 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Saudi Arabia 1 <1%
Belgium 1 <1%
Unknown 144 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 22%
Student > Master 31 21%
Researcher 21 14%
Student > Bachelor 9 6%
Student > Doctoral Student 8 5%
Other 25 17%
Unknown 24 16%
Readers by discipline Count As %
Environmental Science 29 19%
Computer Science 22 15%
Engineering 17 11%
Medicine and Dentistry 10 7%
Social Sciences 8 5%
Other 34 23%
Unknown 31 21%
Attention Score in Context

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 07 April 2015.
All research outputs
#8,246,378
of 24,851,605 outputs
Outputs from Environmental Health
#913
of 1,575 outputs
Outputs of similar age
#74,091
of 221,412 outputs
Outputs of similar age from Environmental Health
#12
of 23 outputs
Altmetric has tracked 24,851,605 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,575 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 221,412 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 66% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.