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| 005 | 20260817162949.0 | ||
| 008 | 200708s2020 th u m rtt 000 a eng d | ||
| 035 | _a.b12346706 | ||
| 099 | _aAIT Thesis no.EV-20-06 | ||
| 100 | 0 | _aNuttawadee Chanwaro | |
| 245 | 1 | 0 | _aApplication of synoptic climatological classification to predict fine particulate matter concentration in the Bangkok metropolitan region |
| 260 |
_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2020 |
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| 300 |
_a77 leaves : _bill. |
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| 490 | 1 |
_aThesis ; _vno. EV-20-06 |
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| 500 | _aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Engineering and Management | ||
| 502 | _aThesis (M. Sc.) - Asian Institute of Technology, 2020 | ||
| 520 | _aThis study aimed at developing a warning system for high PM2.5 concentration based on the synoptic patterns in Bangkok Metropolitan Region (BMR). Six synoptic patterns were identified for each day during January {u2013} May and November {u2013} December of 2017 - 2018 by using nineteen meteorological parameters from seven regional meteorological stations. Then, the PM2.5 prediction models were developed for different synoptic patterns, and the warning tool which was related to the maximum 24-hr average PM2.5 concentration in BMR was discussed. The result of the different synoptic patterns showed that the means of maximum PM2.5 concentration were 44.6, 46.9, 28.1, 41.8, 44.3 and 43.5 æg/m3 for synoptic patterns 1-6, respectively. Percent of the days exceeding the National Ambient Air Quality Standard (NAAQS) of the synoptic pattern 1 to 6 were 34.5, 41.0, 4.5, 27.9, 30.4 and 37.1%, respectively. Moreover, the maximum concentration of PM2.5 in each synoptic pattern were 88.8, 115.0, 73.0, 97.1, 108.6 and 105.5 æg/m3, respectively. Thus, in this study, based on the information of mean, maximum and number of days exceeding standard, two priority synoptic patterns which showed high PM2.5 concentration in BMR were synoptic pattern 2 and 6. The synoptic pattern 3 was identified as low PM2.5 concentration pattern. The results of the linear regression analysis which was used to developed the PM2.5 prediction model exhibited reasonable agreement between the observed and predicted PM2.5 concentration in BMR with the coefficient of determination during January {u2013} May and November {u2013} December of 2017 {u2013} 2018. The link between synoptic pattern and the Air Quality Index (AQI) showed that the synoptic pattern 2 and 6 presented the air quality as unhealthy. Thus, most people should reduce their outdoor activities and they have to protect themselves by using protecting equipment in these synoptic patterns. Synoptic pattern one, four and five were at moderate level of AQI. Thus, general people could do outdoor activities, but sensitive group people should not do the outdoor activities. Finally, synoptic pattern three presented the air quality as satisfactory. Therefore, all people could do outdoor activities and travel due to good air quality. Finally, the warning system which would use the meteorological data of the new day to identify the synoptic pattern which can be linked to the level of maximum 24-hr PM2.5 concentration in BMR was suggested. | ||
| 650 | 0 |
_aAir _xPollution _zThailand _zBangkok |
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| 650 | 0 |
_aAir Quality _zThailand _zBangkok |
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| 650 | 0 |
_aClimatology _zThailand _zBangkok |
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| 700 | 0 |
_aEkbordin Winijkul, _eChairperson |
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| 700 | 1 |
_aNguyen, Thi Kim Oanh, _eExamination Committee |
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| 700 | 1 |
_aDhakal, Shobhakar, _eExamination Committee |
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| 700 | 1 |
_aXue, Wenchao, _eExamination committee |
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| 710 | 2 |
_aHer Majesty the Queen{u2019}s Scholarships (Thailand), _eScholarship donor |
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| 810 | 2 |
_aAsian Institute of Technology. _tThesis ; _vno. EV-20-06 |
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| 856 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B17082 |
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