Skip to main content

Advertisement

SpringerLink
Log in

Visibility, aerosol optical depth, and low-visibility events in Bangkok during the dry season and associated local weather and synoptic patterns

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Visibility and aerosol optical depth (AOD) characterization, and their relationship with PM10 and local and synoptic meteorology, were studied for January–March in 2014 and 2015 over Bangkok. Visibility degradation intensifies in the dry season as compared to the wet season due to increase in PM10 and unfavorable meteorological conditions. The average visibility is lower in January and February as compared to the other months. Relatively higher AOD in March despite lower PM10 is attributed to the synergetic effect of moderate relative humidity, secondary aerosols, elevated aerosol layer due to summertime convection, and biomass burning. Larger variability in visibility and PM10 in winter months is due to more synoptic weather fluctuations while AOD shows similar variability for all months attributed partly to fires. Higher PM10 and moderate-to-high relative humidity cause lower visibility in the morning while it improves in afternoon as PM10 and relative humidity decrease. AOD is higher in the afternoon as compared to that in the morning and evening as it is less sensitive to diurnal change in aerosols and meteorology at the surface level. Visibility and AOD relationships with PM10 are dependent on relative humidity. Weaker winds lead to lower visibility, higher PM10, and higher AOD irrespective of wind direction. Stronger winds improve visibility and decrease PM10 for all directions while AOD is higher for all directions except eastern and northeastern. The back-trajectory results show that the transport of pollutant and moist air is coupled with the synoptic weather and influence visibility and AOD. Two low-visibility events were investigated. The first event is potentially caused by the combined effect of local emissions and their accumulation due to stagnant weather conditions, secondary aerosols, and forest fires in the nearby regions. The second event can be attributed to the local emission and fires in the nearby area with hygroscopic growth of aerosols due to moist air from the Gulf of Thailand. Based on these findings, some policy implications have also been given.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The datasets used during the current study are available from the corresponding author on reasonable request.

References

  • Adeniran, J. A., Aremu, A. S., Saadu, Y. O., & Yusuf, R. O. (2018). Particulate matter concentration levels during intense haze event in an urban environment. Environmental Monitoring and Assessment, 190, 41.

    Article  CAS  Google Scholar 

  • Aman, N., Manomaiphiboon, K., Pala–En, N., Kokkaew, E., Boonyoo, T., Pattaramunikul, S., Devkota, B., & Chotamonsak, C. (2020). Evolution of urban haze in Greater Bangkok and association with local meteorological and synoptic characteristics during two recent haze episodes. International Journal of Environmental Research and Public Health, 17, 9499.

    Article  Google Scholar 

  • Aman, N., Manomaiphiboon, K., Pengchai, P., Suwanathada, P., Srichawana, J., & Assareh, N. (2019). Long–term observed visibility in eastern Thailand: Temporal variation, association with air pollutants and meteorological factors, and trends. Atmosphere, 10, 122.

    Article  CAS  Google Scholar 

  • Babu, S. S., Manoj, M. R., Krishna Moorthy, K., Gogoi, M. M., Nair, V. S., Kompalli, S. K., Satheesh, S. K., Niranjan, K., Ramagopal, K., Bhuyan, P. K., & Singh, D. (2013). Trends in aerosol optical depth over Indian region: Potential causes and impact indicators. Journal of Geophysical Research: Atmospheres, 118, 11794–11806.

    Article  Google Scholar 

  • Baltaci, H., Akkoyunlu, B. O., Arslan, H., Yetemen, O., & Ozdemir, E. T. (2019). The influence of meteorological conditions and atmospheric circulation types on PM10 levels in western Turkey. Environmental Monitoring and Assessment, 191, 466.

    Article  CAS  Google Scholar 

  • Bridhikitti, A. (2013). Atmospheric aerosol layers over Bangkok Metropolitan Region from CALIPSO observations. Atmospheric Research, 127, 1–7.

    Article  CAS  Google Scholar 

  • Chen, J., Xin, J., An, J., Wang, Y., Liu, Z., Chao, N., & Meng, Z. (2014). Observation of aerosol optical properties and particulate pollution at background station in the pearl river delta region. Atmospheric Research, 143, 216–227.

    Article  CAS  Google Scholar 

  • Chuersuwan, N., Nimrat, S., Lekphet, S., & Kerdkumrai, T. (2008). Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region. Environment International, 34, 671–677.

    Article  CAS  Google Scholar 

  • Dejchanchaiwong, R., Tekasakul, P., Tekasakul, S., Phairuang, W., Nim, N., Sresawasd, C., Thongboon, K., Thongyen, T., & Suwattiga, P. (2020). Impact of transport of fine and ultrafine particles from open biomass burning on air quality during 2019 Bangkok haze episode. Journal of Environmental Sciences, 97, 149–161.

    Article  Google Scholar 

  • DOPA. (2014). Statistic of Population by Province in 2014. Department of Provincial Administration. http://stat.bora.dopa.go.th/stat/y_stat54.html. Accessed 28 September 2016.

  • Duc, H. N., Bang, H. Q., & Quang, N. X. (2016). Modelling and prediction of air pollutant transport during the 2014 biomass burning and forest fires in peninsular Southeast Asia. Environmental Monitoring and Assessment, 188, 106.

    Article  CAS  Google Scholar 

  • Giglio, L., Schroeder, W., & Justice, C. O. (2016). The collection 6 MODIS active fire detection algorithm and fire products. Remote Sensing of Environment, 178, 31–41.

    Article  Google Scholar 

  • Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., & Zhai, P. (2016). The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data. Atmospheric Chemistry and Physics, 16, 13309–13319.

    Article  CAS  Google Scholar 

  • Han, X., Zhang, M., Tao, J., Wang, L., Gao, J., Wang, S., & Chai, F. (2013). Modeling aerosol impacts on atmospheric visibility in Beijing with RAMS-CMAQ. Atmospheric Environment, 72, 177–191.

    Article  CAS  Google Scholar 

  • Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., & Smirnov, A. (1998). AERONET – A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66, 1–16.

    Article  Google Scholar 

  • Janjai, S., Nunez, M., Masiri, I., Wattan, R., Buntoung, S., Jantarach, T., & Promsen, W. (2012). Aerosol optical properties at four sites in Thailand. Atmospheric and Climate Sciences, 2, 441–453.

    Article  Google Scholar 

  • Janjai, S., Suntaropas, S., & Nunez, M. (2009). Investigation of aerosol optical properties in Bangkok and suburbs. Theoretical and Applied Climatology, 96, 221–233.

    Article  Google Scholar 

  • Kallos, G., Kassomenos, P., & Pielke, R. A. (1993). Synoptic and mesoscale weather conditions during air pollution episodes in Athens, Greece. Boundary-Layer Meteorology, 62, 163–184.

    Article  Google Scholar 

  • Kamma, J., Manomaiphiboon, K., Aman, N., Thongkamdee, T., Chuangchote, S., & Bonnet, S. (2020). Urban heat island analysis for Bangkok: Multi-scale temporal variation, associated factors, directional dependence, and cool island condition. ScienceAsia, 46, 213–223.

    Article  Google Scholar 

  • Kaskaoutis, D. G., Badarinath, K. V. S., Kharol, S. K., Sharma, A. R., & Kambezidis, H. D. (2009). Variations in the aerosol optical properties and types over the tropical urban site of Hyderabad India. Journal of Geophysical Research: Atmospheres, 114, D22204. https://doi.org/10.1029/2009JD012423

    Article  Google Scholar 

  • Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., & Schöpp, W. (2017). Global anthropogenic emissions of particulate matter including black carbon. Atmospheric Chemistry and Physics, 17, 8681–8723.

    Article  CAS  Google Scholar 

  • Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., & Hsu, N. C. (2013). The collection 6 MODIS aerosol products over land and ocean. Atmospheric Measurement Techniques, 6, 2989–3034.

    Article  Google Scholar 

  • Liu, J., Zheng, Y., Li, Z., & Wu, R. (2008). Ground–based remote sensing of aerosol optical properties in one city in Northwest China. Atmospheric Research, 89, 194–205.

    Article  Google Scholar 

  • Majewski, G., Szelag, B., Mach, T., Rogula-Kozłowska, W., Anioł, E., Bihałowicz, J., Dmochowska, A & Bihałowicz, J.S. (2021). Predicting the number of days with visibility in a specific range in Warsaw (Poland) based on meteorological and air quality data. Frontiers in Environmental Science, 9:623094.

  • Malm, W., & Day, D. E. (2001). Estimates of aerosol species scattering characteristics as a function of relative humidity. Atmospheric Environment, 35, 2845–2860.

    Article  CAS  Google Scholar 

  • Morys, M., Mims, F. M., Hagerup, S., Anderson, S. E., Baker, A., Kia, J., & Walkup, T. (2001). Design, calibration, and performance of MICROTOPS II handheld ozone monitor and Sun photometer. Journal of Geophysical Research: Atmospheres, 106, 14573–14582.

    Article  Google Scholar 

  • Narita, D., Kim Oanh, N. T., Sato, K., Huo, M., Permadi, D. A., Chi, N. N. H., Ratanajaratroj, T., & Pawarmart, I. (2019). Pollution characteristics and policy actions on fine particulate matter in a growing Asian economy: The case of Bangkok Metropolitan Region. Atmosphere, 10, 227.

    Article  CAS  Google Scholar 

  • NESDB. (2015). Gross Regional and Provincial Product, Chain Volume Measures 2015 Edition. Office of the National Economic and Social Development Board, Thailand. http://www.nesdb.go.th/nesdb_en/ewt_dl_link.php?nid=4317. Accessed 15 May 2018.

  • NSO. (2016). Gross Regional and Provincial Products (2005–2015). National Statistical Office, Thailand. http://service.nso.go.th/nso/web/statseries/statseries15.html. Accessed 1 December 2016.

  • Odman, M. T., Hu, Y. T., Russell, A. G., Hanedar, A., Boylan, J. W., & Brewer, P. F. (2009). Quantifying the sources of ozone, fine particulate matter, and regional haze in the Southeastern United States. Journal of Environmental Management, 90, 3155–3168.

    Article  CAS  Google Scholar 

  • PCD. (2020). Thailand State of Pollution Report 2019. Pollution Control Department, Thailand. https://www.pcd.go.th/publication/8013/. Accessed 20 December 2020.

  • Pengchai, P., Chantara, S., Sopajaree, K., Wangkarn, S., Tengcharoenkul, U., & Rayanakorn, M. (2009). Seasonal variation, risk assessment and source estimation of PM10 and PM10–bound PAHs in the ambient air of Chiang Mai and Lamphun, Thailand. Environmental Monitoring and Assessment, 154, 197–218.

    Article  CAS  Google Scholar 

  • Phairuang, W., Suwattiga, P., Chetiyanukornkul, T., Hongtieab, S., Limpaseni, W., Ikemori, F., Hata, M., & Furuuchi, M. (2019). The influence of the open burning of agricultural biomass and forest fires in Thailand on the carbonaceous components in size-fractionated particles. Environmental Pollution, 247, 238–247.

    Article  CAS  Google Scholar 

  • Pitchford, M., Malm, W., Schichtel, B., Kumar, N., Lowenthal, D., & Hand, J. (2007). Revised algorithm for estimating light extinction from IMPROVE particle speciation data. Journal of the Air and Waste Management Association, 57, 1326–1336.

    Article  CAS  Google Scholar 

  • Pongkiatkul, P., & Kim Oanh, N. T. (2007). Assessment of potential long-range transport of particulate air pollution using trajectory modeling and monitoring data. Atmospheric Research, 85, 3–17.

    Article  CAS  Google Scholar 

  • R Core Development Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

  • Ruangjun, S., & Exell, R. H. B. (2008). Regression models for forecasting fog and poor visibility at Donmuang airport in winter. Asian Journal on Energy and Environment, 9, 215–230.

    Google Scholar 

  • Saha, S., Moorthi, S., Pan, H. L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., et al. (2010). The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91, 1015–1057.

    Article  Google Scholar 

  • Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H.-Y., Iredell, M., et al. (2014). The NCEP climate forecast system version 2. Journal of Climate, 27, 2185–2208.

    Article  Google Scholar 

  • Seinfeld, J. H., & Pandis, S. N. (2006). Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. 2nd edition; John Wiley & Sons, Inc.: New York, NY, USA, ISBN 9780471720171.

  • Shi, G., Yang, F., Zhang, L., Zhao, T., & Hu, J. (2019). Impact of atmospheric circulation and meteorological parameters on wintertime atmospheric extinction in Chengdu and Chongqing of southwest China during 2001–2016. Aerosol and Air Quality Research, 19, 1538–1554.

    Article  CAS  Google Scholar 

  • Singh, A., Bloss, W. J., & Pope, F. D. (2017). 60 years of UK visibility measurements: Impact of meteorology and atmospheric pollutants on visibility. Atmospheric Chemistry and Physics, 17, 2085–2101.

    Article  CAS  Google Scholar 

  • Sloane, C.S. (1982). Visibility trends – I. Methods of analysis. Atmospheric Environment, 16, 41–51.

  • Smirnov, A., Holben, B. N., Eck, T. F., Slutsker, I., Chatenet, B., & Pinker, R. T. (2002). Diurnal variability of aerosol optical depth observed at AERONET (Aerosol Robotic Network) sites. Geophysical Research Letters, 29, 2115. https://doi.org/10.1029/2002GL016305

    Article  Google Scholar 

  • Solanki, R., Macatangay, R., Sakulsupich, V., Sonkaew, T., & Mahapatra, P. S. (2019). Mixing layer height retrievals from MiniMPL measurements in the Chiang Mai valley: Implications for particulate matter pollution. Frontiers in Environmental Science, 7, 308.

    Google Scholar 

  • Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., & Ngan, F. (2015). NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bulletin of the American Meteorological Society, 96, 2059–2077.

    Article  Google Scholar 

  • Stewart, I. D., & Oke, T. R. (2012). Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society, 93, 1879–1900.

    Article  Google Scholar 

  • TMD. (2020). Climate of Thailand. Thai Meteorological Department, Thailand. https://www.tmd.go.th/en/archive/thailand_climate.pdf. Accessed 20 December 2020.

  • Tsai, Y. I. (2005). Atmospheric visibility trends in an urban area in Taiwan 1961–2003. Atmospheric Environment, 39, 5555–5567.

    Article  CAS  Google Scholar 

  • Vajanapoom, N., Shy, C. M., Neas, L. M., & Loomis, D. (2001). Estimation of particulate matter from visibility in Bangkok, Thailand. Journal of Exposure Analysis and Environmental Epidemiology, 11, 97–102.

    Article  CAS  Google Scholar 

  • Wang, Y., Li, H., Feng, J., Wang, W., Liu, Z., Huang, L., Yaluk, E., Lu, G., Manomaiphiboon, K., Gong, Y., Traore, D., & Li, L. (2021). Spatial characteristics of PM2.5 pollution among cities and policy implication in the northern part of the north China plain. Atmosphere, 12, 77.

  • Watson, J. G. (2002). Visibility: Science and regulation. Journal of the Air and Waste Management Association, 52, 628–713.

    Article  Google Scholar 

  • Wilks, D. S. (2006). Statistical Methods in the Atmospheric Sciences, 2nd ed.; International Geophysics Series; Elsevier: London, UK.

  • Wimolwattanapun, W., Hopke, P. K., & Pongkiatkul, P. (2011). Source apportionment and potential source locations of PM2.5 and PM2.5–10 at residential sites in metropolitan Bangkok. Atmospheric Pollution Research, 2, 172–181.

    Article  CAS  Google Scholar 

  • Wongsaming, P., & Exell, R. H. B. (2011). Criteria for forecasting cold surges associated with strong high pressure areas over Thailand during the winter monsoon. Journal of Sustainable Energy & Environment, 2, 145–156.

    Google Scholar 

  • Wu, M. C., & Chan, J. C. L. (1995). Surface features of winter monsoon surges over south China. Monthly Weather Review, 123, 662–680.

    Article  Google Scholar 

  • Zahumenský, I. (2004). Guidelines on Quality Control Procedures for Data from Automatic Weather Stations. World Meteorological Organization.

  • Zeeshan, M., & Kim Oanh, N. T. (2014). Assessment of the relationship between satellite AOD and ground PM10 measurement data considering synoptic meteorological patterns and Lidar data. Science of the Total Environment, 473–474, 609–618.

    Article  CAS  Google Scholar 

  • Zheng, C., Zhao, C., Zhu, Y., Wang, Y., Shi, X., Wu, X., Chen, T., Wu, F., & Qiu, Y. (2017). Analysis of influential factors for the relationship between PM2.5 and AOD in Beijing. Atmospheric Chemistry and Physics, 17, 13473–13489.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank the Thai Meteorological Department (TMD) and the Pollution Control Department (PCD) for the observed data, and the Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok (KMUTNB) for the access to the AOD measurement site. We thank Thiantawan Chulathipyachat (PCD) for the station information and Vithaya Saetang for his technical assistance. The Joint Graduate School of Energy and Environment (JGSEE) provided a doctoral scholarship to Nishit Aman while King Mongkut’s University of Technology Thonburi (KMUTT) provided a postdoctoral fellowship to Vacharaporn Soonsin. We thank the two anonymous reviewers for many useful comments and suggestions.

Funding

This study was financially supported by the Joint Graduate School of Energy and Environment (JGSEE), the Postgraduate Education and Research Development Office (PERDO), and partly by the National Research Council of Thailand (NRCT), the Energy Conservation and Promotion Fund (ENCONFUND) of the Ministry of Energy, and Asia Pacific Space Cooperation Organization (APSCO, China).

Author information

Authors and Affiliations

  1. The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Nishit Aman, Kasemsan Manomaiphiboon, Nosha Assareh & Vacharaporn Soonsin

  2. Center of Excellence on Energy Technology and Environment, Ministry of Higher Education, Science, Research and Innovation, Bangkok, Thailand

    Nishit Aman, Kasemsan Manomaiphiboon, Nosha Assareh & Vacharaporn Soonsin

  3. Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Panwadee Suwattiga

  4. Institute of Metropolitan Development, Navamindradhiraj University, Bangkok, Thailand

    Wongpun Limpaseni

  5. Pollution Control Department, Ministry of Natural Resources and Environment, Bangkok, Thailand

    Patcharawadee Suwanathada

  6. School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China

    Yangjun Wang

Authors
  1. Nishit Aman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kasemsan Manomaiphiboon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Panwadee Suwattiga
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nosha Assareh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wongpun Limpaseni
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Patcharawadee Suwanathada
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Vacharaporn Soonsin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yangjun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kasemsan Manomaiphiboon.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 13703 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aman, N., Manomaiphiboon, K., Suwattiga, P. et al. Visibility, aerosol optical depth, and low-visibility events in Bangkok during the dry season and associated local weather and synoptic patterns. Environ Monit Assess 194, 322 (2022). https://doi.org/10.1007/s10661-022-09880-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-09880-2

Keywords

Search

Navigation