Analysis of Environmental Controls on the Quasi-Ocean and Ocean CO2 Concentration by Two Intelligent Algorithms

• Main Authors: Jialu Zhou, Xiaoqiang Li, Wenfeng Wang, Xi Chen
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2021/6666139

Previous studies have demonstrated CO2 absorption by soils in arid regions, where the absorbed CO2 is conjectured to be finally sequestrated in the “subterranean ocean”—groundwater. This study compares environmental controls of ocean CO2 concentration (surface ocean pCO2) and quasi-ocean CO2 concentration (deep-soil pCO2). We aim to explore the latent relationship, both linear and nonlinear between the environmental variables, and CO2 concentration, utilizing two intelligent algorithms—the partial least linear regression (PLSR) algorithm and the artificial neural network (ANN) algorithm. For quasi-ocean CO2 concentration, RPD <1.4 and R2 <40%. While for ocean CO2 concentration, RPD >1.4 and R2 is 99.7%. Linear relationships between the considered environmental controls and ocean CO2 concentration are proved; however, there is no evident relationship between most of the considered environmental controls and quasi-ocean CO2 concentration. Groundwater level is proved to be a relatively important environmental control on the quasi-ocean CO2 concentration, suggesting groundwater discharge/recharge as a significant modulator of soil CO2 absorption in arid regions.