4.7 Article

Spatiotemporal variation of domestic biomass burning emissions in rural China based on a new estimation of fuel consumption

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 626, 期 -, 页码 274-286

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2018.01.048

关键词

Domestic biomass burning; Regression; Emission; Spatiotemporal variation; Rural areas

资金

  1. Natural Sciences Foundation of China [91644110, 51408014]
  2. Beijing Municipal Commission of Science and Technology [Z171100002217002]

向作者/读者索取更多资源

Domestic biomass burning (DBB) influences both indoor and outdoor air quality due to the multiple pollutants released during incomplete and inefficient combustion. The emissions are notwell quantified because of insufficient information, which were the key parameters related to fuel consumption estimation, such as province- and year-specific percentage of domestic straw burning (Pstraw) and firewood consumption (Fc). In this study, we established the quantitative relationship between rural-related socioeconomic parameters (e.g., rural percapita income and rural Engel's coefficient) and Pstraw/Fc. DBB emissions, including 12 crop straw types and firewood for 12 kinds of pollutants in China during the period 1995-2014, were estimated based on fuel-specific emission factors and detailed fuel consumption data. The results revealed that the national emissions generally increased initially and then decreased with the turning point around 2007-2008. Firewood burning was the major source of the NH3 and BC emissions; straw burning contributed more to SO2, NMVOC, CO, OC, and CH4 emissions; while the major contributor changed from firewood to domestic straw burning for NOx, PM10, PM2.5, CO2, and Hg emissions. The emission trends varied among the 31 provinces. The major agricultural regions of north-eastern, central, and south-western Chinawere always characterized by high emissions. The spatial variation mainly occurred in the northeast and north China (increase), and central-south and coastal regions of China (decrease). (c) 2018 Elsevier B.V. All rights reserved.

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