Title |
PM10and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set
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Published in |
BMC Chemistry, February 2014
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DOI | 10.1186/1752-153x-8-14 |
Pubmed ID | |
Authors |
Pierina Ielpo, Vincenzo Paolillo, Gianluigi de Gennaro, Paolo Rosario Dambruoso |
Abstract |
The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it's referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). |
X Demographics
Geographical breakdown
Country | Count | As % |
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Italy | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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India | 1 | 3% |
Unknown | 36 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 9 | 24% |
Researcher | 4 | 11% |
Student > Bachelor | 3 | 8% |
Student > Master | 3 | 8% |
Student > Postgraduate | 2 | 5% |
Other | 3 | 8% |
Unknown | 13 | 35% |
Readers by discipline | Count | As % |
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Environmental Science | 7 | 19% |
Engineering | 3 | 8% |
Earth and Planetary Sciences | 3 | 8% |
Physics and Astronomy | 2 | 5% |
Agricultural and Biological Sciences | 1 | 3% |
Other | 6 | 16% |
Unknown | 15 | 41% |