Literature DB >> 33002702

Biomass burning spatiotemporal variations over South and Southeast Asia.

Shuai Yin1.   

Abstract

In this study, Moderate Resolution Imaging Spectroradiometer active fire and land use products were integrated to extract and classify biomass burning (BB) data for South Asia (SA) and Southeast Asia (SEA). Several trend and geographic distribution analyses were conducted at the grid (0.25° × 0.25°) and regional scales. As the principal local form of BB, crop residue burning (CRB) in SA increased by 844 spots/yr, and the Mann-Kendall (MK) τ reached 0.61. Additionally, the CRB in Punjab-Haryana, a region a well-known for severest CRB, presented a significant declining trend. BB in mainland SEA was much more intense and was dominated by forest and shrubland fires. Forest fires in mainland SEA declined at a rate of -209 spots/yr, and shrubland fire conversely grew at a rate of 803 spots/yr, which was likely related to the dramatic land cover change induced by the local swidden agriculture. Unlike other regions, BB in equatorial SEA primarily occurred in the second half of the year (August to October), and it was extremely vulnerable to El Niño events. When the annual sea surface temperature anomalies within the Niño 3 region improved by 1 °C, the annual BB spots and fire radiative power in equatorial SEA increased by 5.18 × 104 and 2.40 × 106 MW, respectively. Although the interannual variations in equatorial SEA were dramatic, the robust Siegel's repeated median estimator still revealed that equatorial SEA BB significantly declined by -1825 spots/yr. This regional decline reflects government endeavors to curb indigenous BB. However, regions with enhanced BB still need to draw more attention, and it is imperative for the Indonesian government to take substantial measures to reduce anthropogenic fire sources during El Niño events.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Crop residue burning; Forest fire; Siegel’s repeated median; Standard deviation ellipse; Time series

Year:  2020        PMID: 33002702     DOI: 10.1016/j.envint.2020.106153

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


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