Assessment of levels and contributing sources of particulate matter in the Bangkok Metropolitan Region | |
| Author | Tanatat Ratanajaratroj |
| Call Number | AIT Thesis no.EV-18-30 |
| Subject(s) | Air--Pollution--Bangkok - Particles--Environmental aspects--Bangkok - |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science inEnvironmental Engineering and Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. EV-18-30 |
| Abstract | Particulate Matter (PM) is an important air pollution issue in Thailand. In this study, monitoring activities were conducted at the Asian Institute of Technology (AIT), a suburban area of the Bangkok Metropolitan Region (BMR). The monitoring was done during the period of March -November 2017. The obtained data were compiled together with the previous data monitored at the same site since September 2015 to form a longer data series. The monitoring data at AIT (September 2015–November 2017) and that at PCD site (September 2015–March 2017) obtained from previous studies were refined and used for source apportionment studies.During the monitoring period, March –November 2017, the average mass concentrations of PM2.5and PM>2.5at AIT were 14.6± 6.6μg/m3(9.6 –38.3)and 16.4± 11.2μg/m3(4.0 –53.1), respectively (wet period ofMay –Oct) while during the dry period (March, April, November) concentrations were measured of 37.4± 14.3μg/m3(12.6–64.7) and 40.3± 11.4μg/m3(17.4 –53.7), respectively. The results were comparable to those measured during wet and dry period respectively from September 2015 to February 2017 except for PM>2.5.For the whole period from September 2015 to February 2017, average mass concentrations of PM2.5and PM>2.5at PCD site were 15 μg/m3(10 –33)and 37μg/m3(13 -83)in wet period and 32 μg/m3(12 –54) and 44 μg/m3(16 -88) in dry period. The corresponding values for AIT in wet periods (over the entire period from September 2015) were 17μg/m3(16 –38) and 30 μg/m3(4 –83) in wet periods as compared to33μg/m3(13 –65) and 43μg/m3(16 –88) in dry periods. The average concentration of EC and OC at PCD site in PM2.5were 2.74 μg/m3and 4.31 μg/m3, respectively, while those in PM>2.5 were 0.75 μg/m3 and 1.86 μg/m3, respectively. At AIT the concentration of EC and OC in PM2.5were 4.70 μg/m3and 7.13 μg/m3, respectively, while those in PM>2.5were 1.34 μg/m3and 2.88 μg/m3, respectively.The major anion in PM2.5was SO42-and the major cation was NH4+, whilein PM>2.5 had NO3-as the major anion and Ca2+as the major cation. Among the 40 elements analyzed by ICP-MS, 15 elements, namely Na, Mg, K, Ca, Al, V, Cr, 54Fe, Mn, Ni, Cu, Zn, Mo, Ba and 208Pb were generally detected.At PCD, Ca was the highest concentration in wet period, while K was high in dry period. Al was the highest element in wet period at AIT, but Kwas the highest element in dry period.The reconstructed mass (RCM) showed that the organic matter was the highest share in PM2.5followed by the secondary inorganic aerosol (SIA) and soot(BC). Crustal group was the major component in PM>2.5, but the unexplained mass was the majority in PM>2.5. The results of CMB8.2showed that biomass burning was the major contributing source at PCD site in both periods (29 –34%) followed by traffic (23 –29%), SIA (17 –25%), Industry (6%), and sea salt (2 –5%). The major sources of PM2.5at AIT site were biomass burning (26 –41 %), traffic (27 –28%), SIA (16 –18%), industry (4 –7%), soil dust (4 –6%), and sea salt (3 –5%). PMF results showed that diesel vehicle (33 –58 %) was the major source of PM2.5at PCD site followed by gasoline vehicle (8 –23%), biomass burning (10 –23%), SIA (17 –22%), sea salt (2 –3%), while a distant sulfate source contributed about 0 –1%. The major sources of PM2.5at AIT shown by PMF were biomass burning (30 –43%), diesel vehicle (22 –43%), SIA (19 –28%), soil dust (2 –8%), distant sulfate source (0 –7 %), soil dust (2 –8%), and sea salt (2 –6%). The results between CMB and PMF at PCD was very different in term of main sources (biomass burning for CMB and Diesel vehicle for PMF). ivMoreover, PMF at PCD can identified gasoline vehicle. The result of both receptor models at AIT was similar. There is consistency between the major sources suggested by RCM, CMB and PMF but the quantitative source contributions results obtained by CMB and PMF still differed which suggested the need for refining the receptor model results.CPF was done and results showed consistency with the location of local sources, e.g. at both sites showed that diesel vehicle had higher contribution when wind blew from main road (Paholyothin). Biomass burning was highly associated with north and northeast wind coinciding with location of the agricultural areas, the distant sulfate source was from northeast direction, and sea salt was from southwest direction. Gasoline vehicle at the PCD site had major contributing direction from southwest also indicating the toll-way on west of the sampling site. Soil dust contribution at AIT site was seen from all directions surrounding the sampling site due to its on sub-urban location. HYSPLIT results showed that the weeks with high concentration of PM2.5had air mass trajectories pathways from the continental regions with stagnant meteorological conditions, while the weeks with low concentration of PM2.5had the air mass mainly from the ocean and longer marine pathways.The PSCFanalysis was done and the results at both sites show that biomass burning, SIA, the distant sulfate source had a high potential source area in the east and northeast of Thailand, Vietnam and in east and south of China, while the sea salt was mainly linked to the source region from the southwest direction where the seas is located.Future studies are required to combine PM dataset with gaseous data to apply the Multilinear Engine (ME) receptor modeling. The results of sources contribution of PM in BMR are beneficial for the policy making to reduce PM level in BMR |
| Year | 2018 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. EV-18-30 |
| 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 (EV) |
| Chairperson(s) | Nguyen Thi Kim Oanh; |
| Examination Committee(s) | Ekbordin Winijkul;Prapat Pongkiatkul;Sato, Keiichi; |
| Scholarship Donor(s) | Loom Nam Khong Pijai (Greater Mekong Subregion) Scholarships; |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2018 |