干旱区生态环境知识资源中心(Arid): Expanding the theory for reducing the CO2 disaster-Hypotheses from partial least-squares regression and machine learning

Arid

DOI	10.3389/feart.2022.1004920
	Expanding the theory for reducing the CO2 disaster-Hypotheses from partial least-squares regression and machine learning
	Xu, Bai-Zhou; Li, Xiao-Liang; Wang, Wen-Feng; Chen, Xi
通讯作者	Wang, WF ; Chen, X
来源期刊	FRONTIERS IN EARTH SCIENCE
EISSN	2296-6463
出版年	2022
卷号	10
英文摘要	The rapid increase in atmospheric CO2 concentration has caused a climate disaster (CO2 disaster). This study expands the theory for reducing this disaster by analyzing the possibility of reinforcing soil CO2 uptake (F-x) in arid regions using partial least-squares regression (PLSR) and machine learning models such as artificial neural networks. The results of this study demonstrated that groundwater level is a leading contributor to the regulation of the dynamics of the main drivers of F-x-air temperature at 10 cm above the soil surface, the soil volumetric water content at 0-5 cm (R (2)=0.76, RMSE=0.435), and soil pH (R (2)=0.978, RMSE=0.028) in arid regions. F-x can be reinforced through groundwater source management which influences the groundwater level (R (2)=0.692, RMSE=0.03). This study also presents and discusses some basic hypotheses and evidence for quantitively reinforcing F-x.
英文关键词	CO2 disaster partial least-squares regression (PLSR) artificial neural network (ANN) desert systems environmental controls
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000891646400001
WOS关键词	NET ECOSYSTEM CO2 ; CARBON BALANCE ; SOIL ; RESPIRATION ; EXCHANGE ; HIDDEN ; THREAT ; FLUX ; NEGLECT
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392679
推荐引用方式 GB/T 7714	Xu, Bai-Zhou,Li, Xiao-Liang,Wang, Wen-Feng,et al. Expanding the theory for reducing the CO2 disaster-Hypotheses from partial least-squares regression and machine learning[J],2022,10.
APA	Xu, Bai-Zhou,Li, Xiao-Liang,Wang, Wen-Feng,&Chen, Xi.(2022).Expanding the theory for reducing the CO2 disaster-Hypotheses from partial least-squares regression and machine learning.FRONTIERS IN EARTH SCIENCE,10.
MLA	Xu, Bai-Zhou,et al."Expanding the theory for reducing the CO2 disaster-Hypotheses from partial least-squares regression and machine learning".FRONTIERS IN EARTH SCIENCE 10(2022).