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Environ Sci Pollut Res Int. 2018 Sep;25(27):27378-27392. doi: 10.1007/s11356-018-2683-x. Epub 2018 Jul 22.

Simulation and analysis of XCO2 in North China based on high accuracy surface modeling.

Liu Y1,2, Yue T3,4, Zhang L5, Zhao N1,2, Zhao M1,2, Liu Y1,2.

Author information

1
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
2
University of Chinese Academy of Sciences, Beijing, 100049, China.
3
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. yue@lreis.ac.cn.
4
University of Chinese Academy of Sciences, Beijing, 100049, China. yue@lreis.ac.cn.
5
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China.

Abstract

As an important cause of global warming, CO2 concentrations and their changes have aroused worldwide concern. Establishing explicit understanding of the spatial and temporal distributions of CO2 concentrations at regional scale is a crucial technical problem for climate change research. High accuracy surface modeling (HASM) is employed in this paper using the output of the CO2 concentrations from weather research and forecasting-chemistry (WRF-CHEM) as the driving fields, and the greenhouse gases observing satellite (GOSAT) retrieval XCO2 data as the accuracy control conditions to obtain high accuracy XCO2 fields. WRF-CHEM is an atmospheric chemical transport model designed for regional studies of CO2 concentrations. Verified by ground- and space-based observations, WRF-CHEM has a limited ability to simulate the conditions of CO2 concentrations. After conducting HASM, we obtain a higher accuracy distribution of the CO2 in North China than those calculated using the classical Kriging and inverse distance weighted (IDW) interpolation methods, which were often used in past studies. The cross-validation also shows that the averaging mean absolute error (MAE) of the results from HASM is 1.12 ppmv, and the averaging root mean square error (RMSE) is 1.41 ppmv, both of which are lower than those of the Kriging and IDW methods. This study also analyses the space-time distributions and variations of the XCO2 from the HASM results. This analysis shows that in February and March, there was the high value zone in the southern region of study area relating to heating in the winter and the dense population. The XCO2 concentration decreased by the end of the heating period and during the growing period of April and May, and only some relatively high value zones continued to exist.

KEYWORDS:

GOSAT XCO2; HASM; WRF-CHEM; XCO2 simulation

PMID:
30033484
PMCID:
PMC6132398
DOI:
10.1007/s11356-018-2683-x
[Indexed for MEDLINE]
Free PMC Article

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