Exploration of the Contribution of Fire Carbon Emissions to PM2.5 and Their Influencing Factors in Laotian Tropical Rainforests
It is of great significance to understand the drivers of PM2.5 and fire carbon emission (FCE) and the relationship between them for the prevention, control, and policy formulation of severe PM2.5 exposure in areas where biomass burning is a major source. In this study, we considered northern Laos as...
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Published in: | Remote sensing (Basel, Switzerland) Vol. 14; no. 16; p. 4052 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Basel
MDPI AG
01-08-2022
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Subjects: | |
Online Access: | Get full text |
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Summary: | It is of great significance to understand the drivers of PM2.5 and fire carbon emission (FCE) and the relationship between them for the prevention, control, and policy formulation of severe PM2.5 exposure in areas where biomass burning is a major source. In this study, we considered northern Laos as the area of research, and we utilized space cluster analysis to present the spatial pattern of PM2.5 and FCE from 2003–2019. With the use of a random forest and structural equation model, we explored the relationship between PM2.5 and FCE and their drivers. The key results during the target period of the study were as follows: (1) the HH (high/high) clusters of PM2.5 concentration and FCE were very similar and distributed in the west of the study area; (2) compared with the contribution of climate variables, the contribution of FCE to PM2.5 was weak but statistically significant. The standardized coefficients were 0.5 for drought index, 0.32 for diurnal temperature range, and 0.22 for FCE; (3) climate factors are the main drivers of PM2.5 and FCE in northern Laos, among which drought and diurnal temperature range are the most influential factors. We believe that, as the heat intensifies driven by climate in tropical rainforests, this exploration and discovery can help regulators and researchers better integrate drought and diurnal temperature range into FCE and PM2.5 predictive models in order to develop effective measures to prevent and control air pollution in areas affected by biomass combustion. |
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ISSN: | 2072-4292 2072-4292 |
DOI: | 10.3390/rs14164052 |