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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An evaluation tool kit of air quality micro-sensing units
|
|---|---|
| Published in |
Science of the Total Environment, September 2016
|
| 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. |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 13% |
| Norway | 2 | 13% |
| Belgium | 1 | 7% |
| Comoros | 1 | 7% |
| Netherlands | 1 | 7% |
| Spain | 1 | 7% |
| Ireland | 1 | 7% |
| New Zealand | 1 | 7% |
| United Kingdom | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 3 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 60% |
| Scientists | 5 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 203 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 | 200 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 38 | 19% |
| Student > Master | 36 | 18% |
| Researcher | 35 | 17% |
| Student > Doctoral Student | 14 | 7% |
| Professor > Associate Professor | 13 | 6% |
| Other | 31 | 15% |
| Unknown | 36 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 60 | 30% |
| Engineering | 35 | 17% |
| Computer Science | 20 | 10% |
| Chemistry | 9 | 4% |
| Social Sciences | 9 | 4% |
| Other | 26 | 13% |
| Unknown | 44 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 17 March 2021.
All research outputs
#2,307,748
of 25,728,855 outputs
Outputs from Science of the Total Environment
#3,104
of 30,201 outputs
Outputs of similar age
#38,422
of 330,970 outputs
Outputs of similar age from Science of the Total Environment
#40
of 320 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 30,201 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 89% 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 330,970 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 88% of its contemporaries.
We're also able to compare this research output to 320 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.