Title: Measurement method of carbon dioxide using spatial decomposed parallel computing

Authors: Nan Liu; Weipeng Jing; Wenlong Song; Jiawei Zhang

Addresses: College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, China ' College of Information and Computer Engineering, Northeast Forestry University, Heilongjiang Province Engineering Technology Research Center for Forestry Ecological Big Data Storage and High Performance (Cloud) Computing, Harbin, China ' College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, China ' College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, China

Abstract: According to the carbon dioxide (CO₂) characteristics of weak absorption in the ultraviolet and visible (UV-VIS) bands, a measurement method based on spatial decomposed parallel computing of traditional differential optical absorption spectroscopy is proposed to measure CO₂ vertical column concentration in ambient atmosphere. Firstly, American Standard Profile is used to define solar absorption spectrum, and the spectrum acquisition of the incident light converged by the telescope is described as observed parameters. On these bases, spectrometer line model is established. Then, atmospheric radiation transmission is simulated using parallel computing, which obviously reduces the computational complexity while balancing the interference that participates in the fitting. Simulation analyses show that the proposed method can reduce the computational complexity, and run time is reduced by 1.18 s compared with IMLM and IMAP-DOAS in the same configuration. The proposed method can also increase accuracy, with its inversion error reduced by 5.3% and residual reduced by 0.8% than differential optical absorption spectroscopy. The spatial decomposed parallel computing method has advantages in processing CO₂, and it can be further used in the research of carbon sink.

Keywords: differential optical absorption spectroscopy; DOAS; ultraviolet and visible band; spatial decomposed parallel computing method; vertical column concentration; spectrometer; fitting.

DOI: 10.1504/IJHPCN.2019.099741

International Journal of High Performance Computing and Networking, 2019 Vol.14 No.1, pp.8 - 16

Received: 26 Oct 2016
Accepted: 01 Dec 2016
Published online: 21 May 2019 *

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