Measuring multi-scale urban forest carbon flux dynamics using an integrated eddy covariance technique

Kaidi Zhang, Yuan Gong, Francisco J. Escobedo, Rosvel Bracho, Xinzhong Zhang, Min Zhao

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The multi-scale carbon-carbon dioxide (C-CO2) dynamics of subtropical urban forests and other green and grey infrastructure types were explored in an urbanized campus near Shanghai, China. We integrated eddy covariance (EC) C-CO2 flux measurements and the Agroscope Reckenholz-Tänikon footprint tool to analyze C-CO2 dynamics at the landscape-scale as well as in local-scale urban forest patches during one year. The approach measured the C-CO2 flux from different contributing areas depending on wind directions and atmospheric stability. Although the study landscape was a net carbon source (2.98 Mg C ha-1 yr-1), we found the mean CO2 flux in urban forest patches was -1.32 μmol m-2s-1, indicating that these patches function as a carbon sink with an annual carbon balance of -5.00 Mg C ha-1. These results indicate that urban forest patches and vegetation (i.e., green infrastructure) composition can be designed to maximize the sequestration of CO2. This novel integrated modeling approach can be used to facilitate the study of the multi-scale effects of urban forests and green infrastructure on CO2 and to establish low-carbon emitting planning and planting designs in the subtropics.

Translated title of the contributionMedición de la dinámica del flujo de carbono del bosque urbano a multiples escalas utilizando una técnica integrada de covarianza Eddy
Original languageEnglish (US)
Article number4335
JournalSustainability (Switzerland)
Issue number16
StatePublished - Aug 1 2019

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law


Dive into the research topics of 'Measuring multi-scale urban forest carbon flux dynamics using an integrated eddy covariance technique'. Together they form a unique fingerprint.

Cite this