Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Volume 15, issue 21
Biogeosciences, 15, 6713-6729, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Biogeosciences, 15, 6713-6729, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Nov 2018

Research article | 12 Nov 2018

Assessing biotic contributions to CO2 fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009

Archana Dayalu1,2, J. William Munger2, Steven C. Wofsy1,2, Yuxuan Wang3,4, Thomas Nehrkorn5, Yu Zhao6, Michael B. McElroy2, Chris P. Nielsen2, and Kristina Luus7 Archana Dayalu et al.
  • 1Department of Earth and Planetary Sciences, Harvard University, Cambridge, 02138, USA
  • 2School of Engineering and Applied Sciences, Harvard University, Cambridge, 02138, USA
  • 3Department of Earth and Atmospheric Sciences, University of Houston, Houston, 77204, USA
  • 4Department of Earth System Sciences, Tsinghua University, Beijing, 100084, People's Republic of China
  • 5Atmospheric and Environmental Research, Inc., Lexington, 02421, USA
  • 6School of the Environment, University of Nanjing, Nanjing, 210023, People's Republic of China
  • 7Centre for Applied Data Analytics (CeADAR), Dublin 4, Ireland

Abstract. Accurately quantifying the spatiotemporal distribution of the biological component of CO2 surface–atmosphere exchange is necessary to improve top-down constraints on China's anthropogenic CO2 emissions. We provide hourly fluxes of CO2 as net ecosystem exchange (NEE; µmolCO2m−2s−1) on a 0.25° × 0.25° grid by adapting the Vegetation, Photosynthesis, and Respiration Model (VPRM) to the eastern half of China for the time period from 2005 to 2009; the minimal empirical parameterization of the VPRM-CHINA makes it well suited for inverse modeling approaches. This study diverges from previous VPRM applications in that it is applied at a large scale to China's ecosystems for the first time, incorporating a novel processing framework not previously applied to existing VPRM versions. In addition, the VPRM-CHINA model prescribes methods for addressing dual-cropping regions that have two separate growing-season modes applied to the same model grid cell. We evaluate the VPRM-CHINA performance during the growing season and compare to other biospheric models. We calibrate the VPRM-CHINA with ChinaFlux and FluxNet data and scale up regionally using Weather Research and Forecasting (WRF) Model v3.6.1 meteorology and MODIS surface reflectances. When combined with an anthropogenic emissions model in a Lagrangian particle transport framework, we compare the ability of VPRM-CHINA relative to an ensemble mean of global hourly flux models (NASA CMS – Carbon Monitoring System) to reproduce observations made at a site in northern China. The measurements are heavily influenced by the northern China administrative region. Modeled hourly time series using vegetation fluxes prescribed by VPRM-CHINA exhibit low bias relative to measurements during the May–September growing season. Compared to NASA CMS subset over the study region, VPRM-CHINA agrees significantly better with measurements. NASA CMS consistently underestimates regional uptake in the growing season. We find that during the peak growing season, when the heavily cropped North China Plain significantly influences measurements, VPRM-CHINA models a CO2 uptake signal comparable in magnitude to the modeled anthropogenic signal. In addition to demonstrating efficacy as a low-bias prior for top-down CO2 inventory optimization studies using ground-based measurements, high spatiotemporal resolution models such as the VPRM are critical for interpreting retrievals from global CO2 remote-sensing platforms such as OCO-2 and OCO-3 (planned). Depending on the satellite time of day and season of crossover, efforts to interpret the relative contribution of the vegetation and anthropogenic components to the measured signal are critical in key emitting regions such as northern China – where the magnitude of the vegetation CO2 signal is shown to be equivalent to the anthropogenic signal.

Publications Copernicus
Short summary
Accounting for the vegetation signal is critical for comprehensive CO2 budget assessment in China. We model and evaluate hourly vegetation carbon dioxide (CO2) exchange (mass per unit area per unit time) in northern China from 2005 to 2009. The model is driven by satellite and meteorological data, is linked to ground-level ecosystem observations, and is applicable to other time periods. We find vegetation uptake of CO2 in summer is comparable to emissions from fossil fuels in northern China.
Accounting for the vegetation signal is critical for comprehensive CO2 budget assessment in...