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An evaluation tool kit of air quality micro-sensing units

Overview of attention for article published in Science of the Total Environment, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

policy
1 policy source
twitter
15 tweeters

Citations

dimensions_citation
42 Dimensions

Readers on

mendeley
164 Mendeley
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Title
An evaluation tool kit of air quality micro-sensing units
Published in
Science of the Total Environment, January 2017
DOI 10.1016/j.scitotenv.2016.09.061
Pubmed ID
Authors

Barak Fishbain, Uri Lerner, Nuria Castell, Tom Cole-Hunter, Olalekan Popoola, David M. Broday, Tania Martinez Iñiguez, Mark Nieuwenhuijsen, Milena Jovasevic-Stojanovic, Dusan Topalovic, Roderic L. Jones, Karen S. Galea, Yael Etzion, Fadi Kizel, Yaela N. Golumbic, Ayelet Baram-Tsabari, Tamar Yacobi, Dana Drahler, Johanna A. Robinson, David Kocman, Milena Horvat, Vlasta Svecova, Alexander Arpaci, Alena Bartonova

Abstract

Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Unknown 161 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 23%
Researcher 29 18%
Student > Master 29 18%
Professor > Associate Professor 12 7%
Student > Doctoral Student 11 7%
Other 27 16%
Unknown 19 12%
Readers by discipline Count As %
Environmental Science 53 32%
Engineering 29 18%
Computer Science 18 11%
Social Sciences 8 5%
Chemistry 7 4%
Other 24 15%
Unknown 25 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 30 July 2019.
All research outputs
#1,467,539
of 16,094,474 outputs
Outputs from Science of the Total Environment
#1,360
of 15,199 outputs
Outputs of similar age
#34,883
of 270,620 outputs
Outputs of similar age from Science of the Total Environment
#44
of 362 outputs
Altmetric has tracked 16,094,474 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,199 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 91% 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 270,620 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 362 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.