Abstract
The paper discusses and analyzes the effect of environmental factors on ion concentrations in urban air. Statistically mathematical method was used to analyze the measurements of air ion concentration collected in a period of several months, with ion size ranging from 0.75 to 36.6 nm. As environmental factors related to air ions, the following chemical and physical parameters of the atmospheric air were analyzed: CO, NO, NO2, NOx, SO2, O3, PM10, PM2.5, temperature, relative humidity, wind speed and direction. When analyzing data in this combination, there is often a problem of multicollinearity between air chemical and physical parameters. This paper addresses this problem by using the component regression. Regression equations were elaborated to understand the dependence of concentrations of various classes of positive and negative air ions on chemical and physical parameters of the air.
Original language | English |
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Title of host publication | Environment. Technology. Resources |
Subtitle of host publication | Proceedings of the 10th International Scientific and Practical Conference. June 18-20, 2015 |
Place of Publication | Rezekne |
Publisher | Rezekne Higher Education Institution |
Pages | 274-279 |
Number of pages | 6 |
Volume | 2 |
ISBN (Electronic) | 9789984441726 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | 10th International Scientific and Practical Conference on Environment, Technology and Resources - Rezekne, Latvia Duration: 18 Jun 2015 → 20 Jun 2015 Conference number: 10 |
Publication series
Name | Vide. Tehnologija. Resursi - Environment, Technology, Resources |
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ISSN (Print) | 1691-5402 |
Conference
Conference | 10th International Scientific and Practical Conference on Environment, Technology and Resources |
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Country/Territory | Latvia |
City | Rezekne |
Period | 18/06/15 → 20/06/15 |
Other | X Starptautiskā zinātniski praktiskā konference "Vide. Tehnoloģija. Resursi" |
Keywords*
- Air ions
- Air pollution
- Multicollinearity
- Multivariate regression
- Principal Component Regression (PCR)
Field of Science*
- 1.6 Biological sciences
- 2.8 Environmental biotechnology
Publication Type*
- 3.1. Articles or chapters in proceedings/scientific books indexed in Web of Science and/or Scopus database