Work

Enhancing CO2 flux inversion accuracy in a coastal megacity: Impacts of land cover and topography in a regional carbon assimilation system

Year: 2026

Type: article

Abstract: Human activities have significantly increased carbon dioxide (CO 2 ) emissions, exacerbating global warming. Therefore, accurately estimating anthropogenic emissions is crucial for developing effective emission reduction policies. This study focuses on evaluate the impact of land cover (LC) and topography (DEM) on inverted CO 2 fluxes using a new developed regional Carbon Assimilation System (RCAS). Our primary aim is to assess the extent to which LC and DEM influence CO 2 flux inversion in Shenzhen, a rapidly urbanizing coastal city. To achieve this, we analyzed the forward simulations of meteorological variables (wind speed/direction, relative humidity, temperature, and pressure) alongside CO 2 concentration simulations. Following this, we evaluated the posterior CO 2 concentration estimates with the CO 2 flux from the inversion system. The findings demonstrate that new LC and DEM data led to a mean bias reduction from -1.08 ppm to -0.88 ppm, representing a 0.2 ppm improvement, and a slight decrease in standard deviation values from 5.59 ppm to 5.57 ppm in the posterior CO 2 concentration simulation. These results underscore the critical importance of accurate LC and DEM data in enhancing CO 2 flux inversion accuracy, providing valuable insights for improving regional-scale carbon monitoring systems.

Source: Environmental and Sustainability Indicators

DOI: 10.1016/j.indic.2026.101497

Authors: Junjun Fang, Tianle Sun, Pei Zeng, Huifang Zhang, Baozhang Chen

Institutions: Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, Guangdong Province Environmental Monitoring Center

Language: English

Topic: Atmospheric and Environmental Gas Dynamics

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,350