Vegetation fires and air pollution in Vietnam

Le, Thanh; Nguyen, Tri-Thanh; Lasko, Kristofer; Ilavajhala, S.; Vadrevu, Krishna Prasad; Justice, Chris

doi:10.1016/j.envpol.2014.07.023

Cited by 67 publications

(28 citation statements)

References 9 publications

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“…In comparing the two rice growing regions of Vietnam, the Red River Delta averages only 25 active fires during the June rice burning time, whereas the Mekong River Delta averages 556 fires during the peak residue burning month of March. This discrepancy can be largely attributed to the higher cloud cover over the Red River Delta during burning months, compounded by relatively smaller field and fire sizes with average field size of about 5000m 2 in the Mekong River Delta compared to about 800m 2 in Hanoi and the Red River Delta [ 30 – 31 , 60 – 61 ].…”

Section: Resultsmentioning

confidence: 99%

“…BC levels in the Southeast Asia region show a peak during March across Thailand and Myanmar attributed to agricultural and small-holder burning fires detected by MODIS ( Fig 3 ) [ 33 ]. During March and April, high BC values over Laos and Northwest province of Vietnam are attributed especially to forest fires and slash and burn agriculture [ 30 ]. Relatively high BC levels throughout all months are consistently observed from Southern China largely originating from the mega-urban Chengdu and Chongqing cities with biomass burning also as a non-negligible emission source during these months [ 62 – 63 ].…”

Section: Resultsmentioning

confidence: 99%

“…Of the different countries in Asia, Vietnam emits approximately 83Gg of BC annually, and it as the fifth highest emitter after some of the most populous countries including China, India, Indonesia, and Pakistan [ 3 ]. Much of the BC emissions from Vietnam are concentrated in the capital region of Hanoi, home to over 10 million people [ 29 ] with areas of forest biomass burning impacting air pollution in the Northwest, and rice straw burning within the Red River Delta surrounding Hanoi [ 30 ]. It’s uncertain how much of the air pollution in Hanoi is due to different sources from the surrounding region.…”

Section: Introductionmentioning

confidence: 99%

“…It’s uncertain how much of the air pollution in Hanoi is due to different sources from the surrounding region. This study explores how and if pollution contribution from other sources impact Hanoi’s pollution levels, such as local rice residue burning within the Red River Delta during June and October [ 31 ], as well as urban pollution from megacities in Southern China, and absorbing aerosols from forest fires in Laos and Vietnam [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets

2018

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Air pollution is one of the major environmental concerns in Vietnam. In this study, we assess the current status of air pollution over Hanoi, Vietnam using multiple different satellite datasets and weather information, and assess the potential to capture rice residue burning emissions with satellite data in a cloud-covered region. We used a timeseries of Ozone Monitoring Instrument (OMI) Ultraviolet Aerosol Index (UVAI) satellite data to characterize absorbing aerosols related to biomass burning. We also tested a timeseries of 3-hourly MERRA-2 reanalysis Black Carbon (BC) concentration data for 5 years from 2012–2016 and explored pollution trends over time. We then used MODIS active fires, and synoptic wind patterns to attribute variability in Hanoi pollution to different sources. Because Hanoi is within the Red River Delta where rice residue burning is prominent, we explored trends to see if the residue burning signal is evident in the UVAI or BC data. Further, as the region experiences monsoon-influenced rainfall patterns, we adjusted the BC data based on daily rainfall amounts. Results indicated forest biomass burning from Northwest Vietnam and Laos impacts Hanoi air quality during the peak UVAI months of March and April. Whereas, during local rice residue burning months of June and October, no increase in UVAI is observed, with slight BC increase in October only. During the peak BC months of December and January, wind patterns indicated pollutant transport from southern China megacity areas. Results also indicated severe pollution episodes during December 2013 and January 2014. We observed significantly higher BC concentrations during nighttime than daytime with peaks generally between 2130 and 0030 local time. Our results highlight the need for better air pollution monitoring systems to capture episodic pollution events and their surface-level impacts, such as rice residue burning in cloud-prone regions in general and Hanoi, Vietnam in particular.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets

2018

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“…Dust lifting and suspending in the air is result of North-East monsoon flows in October causing the stable temperature and dry weather in Hanoi. In addition, Huang et al [20] and Le et al [21] reported the peak of biomass burning in Southeast Asia and in Vietnam in March. It can be seen from Fig.…”

Section: Methods For Comparison Between Modis Satellite-based and Aeromentioning

confidence: 99%

Comparison of aerosol products retrieved from AERONET and MODIS over an urban area in Hanoi city, Vietnam

Hieu

Luong²,

Hiep

et al. 2018

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To understand the dynamics of aerosols and their associated influence on regional and global climatic conditions requires the knowledge of spatial and temporal distributions of aerosols on regional and global scales. In this study, the satellite-based MODIS AODs retrievals level 2 products from Terra (MOD04-10 km) and Aqua (MYD04-10 km) satellites were inter-compared with the ground-based AERONET AODs (level 2) over Nghia Do station located in an urban area of Hanoi city, Vietnam for the period of 2010-2016. The Terra AODs showed good-match with the ground-based AODs measurements (slope = 0.830, intercept = 0.099, RMSE = 0.260, R 2 = 0.673, and RMB = 0.970). However, the Aqua AODs expressed systematically the underestimation of AERONET AODs (slope = 0.556, intercept = 0.184, RMSE = 0.390, R 2 = 0.408, and RMB = 0.810). All MODIS AODs indicated the moderate correlation with AERONET AODs (slope = 0.683, intercept = 0.147, RMSE = 0.330, R 2 = 0.520, and RMB = 0.890). Although MODIS AODs followed well the monthly variations of AERONET AODs, the relatively high discrepancy between MODIS and AERONET AODs could be observed during the winter months.

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