Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Construction and Environment | en_US |
| dc.creator | Liu, Yi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/7573 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Analysis of seasonal variation and impact factors of PM2.5 in urban area of Beijing | en_US |
| dcterms.abstract | To analyze characteristic of PM2.5 seasonal variation and its impact factors in Beijing, this thesis centers on PM2.5 variation of the main urban area in Beijing. Research period is from October 2013 to March 2014. Whole period contains three seasons, spring, autumn and winter. Using statistical analysis is one innovation of research. Analysis result could explain the characteristics of variation in different seasons. Comparison result between research period and 2009 to 2010 shows the variation trend of seasonal characteristic through the years. Impact factor analysis is another innovation of this research. Statistical analysis can show relevance between PM2.5 and different meteorological factors. A regression equation based on factors created by program displays how well those factors could explain variation of PM2.5. Humidity and wind are two factors who have strong correlation with PM2.5 according to analysis result. Based on atmospheric physic knowledge, a further step analysis has been conducted to discuss why the wind has a strong negative correlation with PM2.5 and its mode to impact PM2.5 variation. Secondary inorganic aerosol is the major component of PM2.5 in Beijing. The chemical analysis result shows humidity could influence PM2.5 concentration through influencing secondary inorganic aerosol production. This result can further explain how automobile exhaust could indirectly contribute to PM2.5 pollution. Many scientists focus on those factors who are compositions of PM2.5. They study PM2.5's variation characteristic through studying variation of those factors. The result of this research proves that some factors which are not compositions of PM2.5 still could have a strong impact to PM2.5 variation. This is major breakthrough offered by this research. It can provide a new study idea for PM2.5 research in future. | en_US |
| dcterms.extent | iii, 127 leaves : color illustrations ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2014 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Air -- Pollution -- China -- Beijing | en_US |
| dcterms.LCSH | Air quality monitoring stations -- United States -- Management. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b27591244.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.97 MB | Adobe PDF | View/Open |
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