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改善人类破坏森林边缘和城市地区的生物排放模型

Yanli Zhang¹, Haofan Ran^1,2, Alex Guenther³

¹State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China.

Nature communications

|August 28, 2025

概括

一个名为GEE-MEGAN的新模型改善了生物产生的挥发性有机化合物 (BVOC) 排放的估计. 这种工具提高了在多样化和不断变化的环境中跟踪排放的准确性.

科学领域:

大气化学和环境科学.
生物地化学循环和气候模型.

背景情况:

生态挥发性有机化合物 (BVOC) 对生物圈与大气相互作用至关重要,影响大气化学,空气质量和气候.
在各种生态系统中精确估计BVOC排放是具有挑战性的,特别是在快速变化的环境中.

研究的目的:

引入GEE-MEGAN,这是MEGAN2.1模型的云原生扩展,用于近乎实时的BVOC排放估计.
通过集成动态卫星数据和谷歌地球引擎,使BVOC排放能够精细追踪.

主要方法:

通过将MEGAN2.1模型扩展到动态,卫星衍生的土地覆盖和植被数据来开发GEE-MEGAN.
使用谷歌地球引擎进行云原生处理和高分辨率 (10-30m) BVOC排放计算.
将GEE-MEGAN估计与MEGAN2.1进行比较,重点关注受人类干扰的地区和城市环境.

主要成果:

与MEGAN2.1相比,GEE-MEGAN降低了BVOC排放的估计值31%,并减少了高达48.6%的平方根平均误差.
在主要城市地区 (伦敦,洛杉矶,巴黎,北京) 的夏季BVOC排放量高出此前估计的25倍.
展示了更好地捕捉微型景观异质性和人类驱动的动力.

结论:

通过纳入景观异质性和动态环境变化,GEE-MEGAN显著提高了BVOC排放估计的准确性.
提供了关于BVOC,气候和空气质量在自然环境和人为环境之间的复杂相互作用的关键见解.
能够在快速变化的环境中精细追踪排放,有助于环境监测和政策.

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