Qing Zhang

Dr. Qing Zhang


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
XSXiangjin Shen
Xiangjin Shen
BLBinhui Liu
Binhui Liu
ZXZhenshan Xue
Zhenshan Xue
MJMing Jiang
Ming Jiang
XLXianguo Lu
Xianguo Lu
QZQing Zhang
Qing Zhang

10 August 2017 in Journal of Geophysical Research: Atmospheres
Verified
Journal Article
Closed access
PDF file
RZRan Zhang
Ran Zhang
DJDabang Jiang
Dabang Jiang
ZZZhongshi Zhang
Zhongshi Zhang
ZCZhigang Cheng
Zhigang Cheng
QZQing Zhang
Qing Zhang

27 July 2019 in Journal of Geophysical Research: Biogeosciences
Verified
Journal Article
Closed access
GWGuocheng Wang
Guocheng Wang
YHYao Huang
Yao Huang
YWYurong Wei
Yurong Wei
WZWen Zhang
Wen Zhang
TLTingting Li
Tingting Li
QZQing Zhang
Qing Zhang

1 March 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
TLTingting Li
Tingting Li
HLHailing Li
Hailing Li
QZQing Zhang
Qing Zhang
ZMZhenfeng Ma
Zhenfeng Ma
LYLingfei Yu
Lingfei Yu
JLJia Liu
Jia Liu

5 December 2022 in Journal of Plant Physiology
Verified
Journal Article
Closed access
KYKai Yang
Kai Yang
YHYao Huang
Yao Huang
JYJingrui Yang
Jingrui Yang
LYLingfei Yu
Lingfei Yu
ZHZhenghua Hu
Zhenghua Hu
QZQing Zhang
Qing Zhang

26 August 2020 in Geoscientific Model Development
Verified
Journal Article
Open access
PDF file
TLTingting Li
Tingting Li
YLYanyu Lu
Yanyu Lu
LYLingfei Yu
Lingfei Yu
WSWenjuan Sun
Wenjuan Sun
QZQing Zhang
Qing Zhang
RZRan Zhang
Ran Zhang
Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH 4 ). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH 4 emissions from global wetlands. Reliable models are required to estimate global wetland CH 4 emissions. This study aimed to test two process-based models, CH4MOD wetland and Terrestrial Ecosystem Model (TEM), against the CH 4 flux measurements of marsh, swamp, peatland and coastal wetland sites across the world; specifically, model accuracy and generality were evaluated for different wetland types and in different continents, and then the global CH 4 emissions from 2000 to 2010 were estimated. Both models showed similar high correlations with the observed seasonal/annual total CH 4 emissions, and the regression of the observed versus computed total seasonal/annual CH 4 emissions resulted in R 2 values of 0.81 and 0.68 for CH4MOD wetland and TEM, respectively. The CH4MOD wetland produced accurate predictions for marshes, peatlands, swamps and coastal wetlands, with model efficiency (EF) values of 0.22, 0.52, 0.13 and 0.72, respectively. TEM produced good predictions for peatlands and swamps, with EF values of 0.69 and 0.74, respectively, but it could not accurately simulate marshes and coastal wetlands (EF <0). There was a good correlation between the simulated CH 4 fluxes and the observed values on most continents. However, CH4MOD wetland showed no correlation with the observed values in South America and Africa. TEM showed no correlation with the observations in Europe. The global CH 4 emissions for the period 2000–2010 were estimated to be 105.31 ± 2.72 Tg yr −1 by CH4MOD wetland and 134.31 ± 0.84 Tg yr −1 by TEM. Both models simulated a similar spatial distribution of CH 4 emissions globally and on different continents. Marshes contribute 36 %–39 % of global CH 4 emissions. Lakes/rivers and swamps are the second and third greatest contributors, respectively. Other wetland types account for only approximately 20 % of global emissions. Based on the model applicability, if we use the more accurate model, i.e., the one that performs best as evidenced by a higher model efficiency and a lower model bias, to estimate each continent and wetland type, we obtain a new assessment of 116.99–124.74 Tg yr −1 for the global CH 4 emissions for the period 2000–2010. Our results imply that performance at a global scale may conceal model uncertainty. Efforts should be made to improve model accuracy for different wetland types and regions, particularly hotspot regions, to reduce the uncertainty in global assessments.