Preliminary monitoring of concentration of particulate matter (PM2.5) in seven townships of Yangon City, Myanmar - Ei Ei Pan Nu Yi; Nay Chi Nway; Win Yu Aung; Zarli Thant; Thet Hnin Wai; Kyu Kyu Hlaing; Cherry Maung; Mayuko Yagishita; Yang Ishigaki; Tin-T; Daisuke Nakajima; Ohn Mar (Komiyama Printing Co. Ltd, 2018)
Abstract Background Airborne particulate pollution is more critical in the developing world than in the developed countries in which industrialization and urbanization are rapidly increased. Yangon, a second capital of Myanmar, is a highly congested and densely populated city. Yet, there is limited study which assesses particulate matter (PM2.5) in Yangon currently. Few previous local studies were performed to assess particulate air pollution but most results were concerned PM10 alone using fixed monitoring. Therefore, the present study aimed to assess distribution of PM2.5 in different townships of Yangon, Myanmar. This is the first study to quantify the regional distribution of PM2.5 in Yangon City. Methods The concentration of PM2.5 was measured using Pocket PM2.5 Sensor (Yaguchi Electric Co., Ltd., Miyagi, Japan) three times (7:00 h, 13:00 h, 19:00 h) for 15 min per day for 5 days from January 25th to 29th in seven townships. Detailed information of eight tracks for PM2.5 pollution status in different areas with different conditions within Kamayut Township were also collected. Results The results showed that in all townships, the highest PM2.5 concentrations in the morning followed by the evening and the lowest concentrations in the afternoon were observed. Among the seven townships, Hlaingtharyar Township had the highest concentrations (164 ± 52 μg/m3) in the morning and (100 ± 35 μg/m3) in the evening. Data from eight tracks in Kamayut Township also indicated that PM2.5 concentrations varied between different areas and conditions of the same township at the same time. Conclusion Myanmar is one of the few countries that still have to establish national air quality standards. The results obtained from this study are useful for the better understanding of the nature of air pollution linked to PM2.5. Moreover, the sensor which was used in this study can provide real-time exposure, and this could give more accurate exposure data of the population especially those subpopulations that are highly exposed than fixed station monitoring.