Unravelling greenhouse gas variations in Xianghe, China

2023-2024
New research reveals the main sources of greenhouse gases (GHG) at the Xianghe site, near Beijing. Using advanced ground-based measurements and an atmospheric transport model (WRF-GHG), the key contributing sectors to CO₂ and CH₄ at Xianghe could be identified: industrial activities, agriculture, and energy production, but also the biosphere.

Further, weather patterns also significantly influence concentration levels by, for example, transporting pollution from the North China Plain. These findings improve our understanding of regional GHG dynamics and support more accurate climate assessments.

Observations at Xianghe

Since 1974, atmospheric observations of many compounds have been conducted at Xianghe, operated by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. The Xianghe site is located in a suburban area close to the capital Beijing, a highly populated and industrialized region.

Thanks to the expertise of BIRA-IASB, a new high-precision instrument was added, enabling ground-based measurements of CO₂, CH₄, and carbon monoxide (CO) since 2018.

The site now observes GHG levels using two methods:

  • remote sensing for measuring the total amount of gas in the column from the Earth’s surface to the top of the atmosphere and
  • in situ observations for measuring detailed near-surface concentrations.

Moreover, the ground-based remote sensing observations are part of the global Total Carbon Column Observation Network (TCCON), contributing to long-term atmospheric monitoring and satellite data validation.

 

Atmospheric transport model

To better understand the observed GHG variations at Xianghe, we applied an atmospheric transport model called WRF-GHG (Weather Research and Forecast model for Greenhouse Gases) to the region.

This model helps distinguish between different influencing factors: are the fluctuations due to industrial emissions, energy production, agricultural activities, or perhaps just changing weather patterns? By simulating one year of GHG concentrations at Xianghe, comparing model outputs with both column and near-surface observations, we can unravel the most important processes that influence the measurements.

 

Results

Our findings reveal that CH₄ concentrations are mainly driven by agricultural activities, residential heating, fossil fuel extraction, and waste management, while CO₂ variations are linked to industrial activities, energy production, and interactions with the biosphere.

Further, we show the crucial role of changing wind patterns: southwesterly winds bring polluted air from the urbanized North China Plain, whereas northerly winds bring cleaner air from remote regions like Inner Mongolia, respectively increasing or lowering the concentrations at Xianghe.

The model successfully captured many observed patterns and offered insights into regional GHG dynamics. Current research is using this model to verify emissions of CO2 and CH4 in Belgium through the VERBE project.

 

 

Reference

Callewaert, S., Zhou, M., Langerock, B., Wang, P., Wang, T., Mahieu, E., and De Mazière, M.: A WRF-Chem study of the greenhouse gas column and in situ surface concentrations observed at Xianghe, China. Part 1: Methane (CH4), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3228, 2024.

Illustration of Beijing
Illustration of Beijing
Greenhouse gases (GHG) like carbon dioxide (CO₂) and methane (CH₄) play a key role in climate change, making it crucial to understand their sources and behavior in the atmosphere. However, ground-based measurements of these gases are still relatively limited in China, one of the world’s largest GHG emitters. Source: pexels.com, photo by Zhang Kaiyv.
Map of North China
Map of North China. The red star indicates the location of the Xianghe site. The black dots represent the largest cities in the region.
Time series CO2 Xianghe in July-August 2019
(a) Example time series of observed (red) and simulated (black) column CO2 concentrations at Xianghe in July-August 2019. The period highlighted in light grey indicates an event with increased CO2 concentrations. Panel (b) shows the corresponding contribution of the different components that together with the background (not shown) make up the total concentrations simulated by the model, while panel (c) shows the simulated 2m temperature at the site. These figures reveal that the high CO2 levels coincide with upper winds from the west (arrows at the bottom of panel (a)), a weaker CO2 uptake by the biosphere (green line in panel (b)) and higher temperatures (panel (c)). It was caused by advection of a hot and CO2-rich air mass from the Gobi desert, resulting in a heatwave.