↓ Skip to main content

PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic

Overview of attention for article published in Environmental Science and Pollution Research, April 2013
Altmetric Badge

Mentioned by

twitter
1 X user
facebook
1 Facebook page

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
60 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic
Published in
Environmental Science and Pollution Research, April 2013
DOI 10.1007/s11356-013-1682-1
Pubmed ID
Authors

Regina E. Ducret-Stich, Ming-Yi Tsai, Devraj Thimmaiah, Nino Künzli, Philip K. Hopke, Harish C. Phuleria

Abstract

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter < 10 μm (PM10) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM10 sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM10 filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM10 concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
India 1 2%
Brazil 1 2%
Unknown 56 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 23%
Student > Ph. D. Student 9 15%
Student > Master 9 15%
Professor 4 7%
Student > Postgraduate 3 5%
Other 12 20%
Unknown 9 15%
Readers by discipline Count As %
Environmental Science 19 32%
Medicine and Dentistry 6 10%
Engineering 5 8%
Earth and Planetary Sciences 4 7%
Chemistry 3 5%
Other 10 17%
Unknown 13 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 April 2013.
All research outputs
#18,756,367
of 23,911,072 outputs
Outputs from Environmental Science and Pollution Research
#5,072
of 9,883 outputs
Outputs of similar age
#143,716
of 197,677 outputs
Outputs of similar age from Environmental Science and Pollution Research
#45
of 63 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,883 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 44th percentile – i.e., 44% 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 197,677 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.