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Updated: Dec 17, 2025
Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace
Published on: September 6, 2018
Re-estimating methane emissions from Chinese paddy fields based on a regional empirical model and
Jianfei Sun1, Minghui Wang1, Xiangrui Xu1
1Institute of Resource, Ecosystem and Environment of Agriculture, and Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu, 210095, China.
Accurate methane (CH4) emission modeling from paddy fields is crucial. Region-specific models, driven by detailed environmental data, significantly improve methane emission estimations compared to national models.
Area of Science:
- Agricultural Science
- Environmental Science
- Climate Science
Background:
- Quantifying methane (CH4) emissions from paddy fields is vital for assessing agricultural environmental risks.
- Improving the accuracy of CH4 emission models is a key challenge in paddy rice production research.
Purpose of the Study:
- To develop and evaluate region-specific models for estimating CH4 emissions from paddy fields.
- To identify key environmental and management factors influencing CH4 emissions.
- To estimate total CH4 emissions from China's paddy fields using a refined model.
Main Methods:
- Utilized a database of 835 field measurements for model development (70%) and evaluation (30%).
- Established both single national and region-specific models incorporating environmental factors and management patterns.
- Employed high-resolution spatial data for key drivers to estimate CH4 emissions.
Main Results:
- Region-specific models demonstrated superior performance over the national model, with R² values ranging from 0.15-0.70 and efficiency values from 11-60%.
- Paddy rice type, water regime, organic amendment, latitude, soil pH, and bulk density were identified as primary drivers.
- Estimated China's total paddy field CH4 emissions in 2015 at 4.75 Tg (95% CI: 4.19–5.61 Tg).
Conclusions:
- Region-specific models significantly enhance the accuracy of CH4 emission estimations from paddy fields.
- High-resolution spatial data integration is critical for driving accurate regional emission models.
- The findings provide a more precise assessment of CH4 emissions from China's rice cultivation.
