Development of a synoptic climatological approach to predict ambient SO2 concentrations at the Mae Moh Valley | |
| Author | Chutimon Piromyaporn |
| Call Number | AIT Thesis no.EV-00-3 |
| Subject(s) | Sulphur dioxide--Mae Moh Valley Pollution--Research--Mae Moh Valley |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | This study was an attempt to establish mathematical models to predict S02 concentrations in the Mae Moh Valley where S02 episodes often occurred. A synoptic climatological approach, which accounts for both synoptic and local meteorological conditions affecting the pollutant dispersions, was applied to achieve the purpose. The composite procedure utilizing principal component analysis (PCA) followed by a twostage clustering used in this study could identify objectively distinct synoptic meteorological clusters and also describe the typical S02 pollutant levels in each of the identified synoptic categories. The procedure was applied for 5-year (1995-2000) winter months (NovemberJanuary) on 13 meteorological parameters at OlOOLST, six distinct synoptic categories were identified, which exhibited rather clear differences in the daily maximum 1-h average S02 concentrations throughout the Mae Moh Valley. Preliminary multiple linear regression models were developed for the polluted synoptic categories, categories one and five, which contain cases with the daily maximum 1-h S02 concentrations greater than NAAQS of 780 μg/m3 . The results of the multiple linear regression analysis for the winter period of 1995-1997 revealed reasonable agreements between the predicted and observed S02 concentrations for both synoptic categories. The coefficients of determination (R2), which indicate the proportion of the total variance of the maximum hourly S02 concentrations explained by the models, are 66% and 61 % for clusters one and five, respectively. Corresponding root mean square errors (RMSEs) are 252 and 340 μg/m3 , and relative errors are 34% and 33%, respectively. The prediction results would have been much improved if the S02 emission data had been available for consideration. New regression models are planned to be developed taking S02 daily emission data into the account. A preliminary application procedure of the synoptic climatological approach to predict daily maximum 1-h average S02 concentrations was developed. A warning signal of unfavorable meteorological conditions with potential high S02 concentrations during the day could be released based on the OlOOLST meteorological conditions. Regression ·equations for each synoptic category would give the prediction of S02 concentrations for the day. |
| Year | 2000 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Environmental Engineering and Management (EV) |
| Chairperson(s) | N. T. Kim Oanh; |
| Examination Committee(s) | Samorn Muttamara;Supat Wangwongwatana; |
| Scholarship Donor(s) | Asian Institute of Technology;Partial Scholarship;Petroleum Authority of Thailand |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2000 |