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Open AccessArticle

Spatial and Temporal Variations of Atmospheric CO2 Concentration in China and Its Influencing Factors

by Zhenghan Lv 1,2, Yusheng Shi 2,*, Shuying Zang 1,* and Li Sun 1
1
Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
2
State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
*
Authors to whom correspondence should be addressed.
Atmosphere 2020, 11(3), 231; https://doi.org/10.3390/atmos11030231
Received: 1 February 2020 / Revised: 22 February 2020 / Accepted: 25 February 2020 / Published: 27 February 2020
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
Over the past few decades, concentrations of carbon dioxide (CO2), a key greenhouse gas, have risen at a global rate of approximately 2 ppm/a. China is the largest CO2 emitter and is the principle contributor to the increase in global CO2 levels. Based on a satellite-retrieved atmospheric carbon dioxide column average dry air mixing ratio (XCO2) dataset, derived from the greenhouse gas observation satellite (GOSAT), this paper evaluates the spatial and temporal variations of XCO2 characteristics in China during 2009–2016. Moreover, the factors influencing changes in XCO2 were investigated. Results showed XCO2 concentrations in China increased at an average rate of 2.28 ppm/a, with significant annual seasonal variations of 6.78 ppm. The rate of change of XCO2 was greater in south China compared to other regions across China, with clear differences in seasonality. Seasonal variations in XCO2 concentrations across China were generally controlled by vegetation dynamics, characterized by the Normalized Difference Vegetation Index (NDVI). However, driving factors exhibited spatial variations. In particular, a distinct belt (northeast–southwest) with a significant negative correlation (r < −0.75) between XCO2 and NDVI was observed. Furthermore, in north China, human emissions were identified as the dominant influencing factor of total XCO2 variations (r > 0.65), with forest fires taking first place in southwest China (r > 0.47). Our results in this study can provide us with a potential way to better understand the spatiotemporal changes of CO2 concentration in China with NDVI, human activity and biomass burning, and could have an enlightening effect on slowing the growth of CO2 concentration in China. View Full-Text
Keywords: carbon dioxide (CO2); GOSAT; spatial variation; temporal trends; influencing factors carbon dioxide (CO2); GOSAT; spatial variation; temporal trends; influencing factors
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Lv, Z.; Shi, Y.; Zang, S.; Sun, L. Spatial and Temporal Variations of Atmospheric CO2 Concentration in China and Its Influencing Factors. Atmosphere 2020, 11, 231.

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