Multivariate statistical analysis approach for PNC2.5 dust concentration prediction around a quarry area in Lumut, Perak
| dc.contributor.author | Yao Benjamin | |
| dc.date.accessioned | 2021-07-23T01:54:41Z | |
| dc.date.available | 2021-07-23T01:54:41Z | |
| dc.date.issued | 2016-06 | |
| dc.description.abstract | Dust emission is one of the main issues faced by quarries worldwide due to the health effects it can potentially bring to its surrounding communities. Of particular concern are the dust particles that fall into the submicron range, which have been shown to cause more grievous health effects than coarser particles. While useful, current gravimetric air quality monitoring methods based on PM10 and PM2.5 (particulate matter less than 10 microns and 2.5 microns respectively) are not sufficient to monitor ultrafine particles due to their insignificant mass. This thesis presents the results of a study conducted in Lumut, Perak to develop a new dust prediction model based on PNC2.5 (number concentration of particulates less than 2.5 microns) which take into account the particles that fall into the submicron range. Data for five meteorological variables were collected using a GRIMM EDM 164 outdoor environment dust monitor from 21st September to 1st October 2015 and were analysed using IBM SPSS 13.0 software package. A PM2.5 to PNC2.5 conversion formula was developed with a regression coefficient (R2) value of 0.990 and 82.6 % estimation accuracy on external data. Subsequently, principal component analysis (PCA) and multiple regression analysis (MRA) were used to develop a new algorithm model for PNC2.5 prediction using meteorological data. The model yielded an R2 value of 0.355, which was comparable to the results of other PNC studies in Malaysia for different particle size ranges but indicates a lesser influence of meteorological variables on PNC2.5. Validation of the model performance using external data obtained from other sites showed that the model predictive accuracy was 71.6%. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/13792 | |
| dc.language.iso | en | en_US |
| dc.title | Multivariate statistical analysis approach for PNC2.5 dust concentration prediction around a quarry area in Lumut, Perak | en_US |
| dc.type | Other | en_US |
Files
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: