| Sumario: | Rice production is a major source of agricultural greenhouse gas (GHG) emissions in China. In particular, methane emissions from paddy fields account for a substantial share, making rice systems a key point for achieving mitigation targets in the agricultural sector. In recent years, with the advancement of China’s carbon peaking and carbon neutrality strategies, low-carbon rice cultivation technologies have attracted growing attention. Across regions, a range of low-methane practices, such as alternate wetting and drying (AWD), optimized fertilizer management, improved straw utilization, direct seeding, and rice–upland crop rotation, have been promoted and adopted. However, systematic quantification remains limited regarding the differences across technologies in mitigation effectiveness, agroecological suitability, and economic costs. This gap constrains the identification of cost-effective mitigation pathways and the design of targeted policies. Meanwhile, much of the existing evidence relies on aggregate emission factors or region-level scenario analyses, and thus provides insufficient empirical evidence on the costs, benefits, and mitigation outcomes of these practices under farmers’ production conditions.
This study draws on primary survey data collected from four rice-growing areas, Taijiang (Guizhou), Mashan (Guangxi), Hongze (Jiangsu), and Jiangshan (Zhejiang), covering 499 rice farming entities in 2019 and 2024, with a total of 1,005 plots. The dataset includes detailed information on plot-level biophysical conditions, cropping systems, fertilizer and pesticide use, water management, straw management, labor inputs, mechanization, and production costs, enabling a nuanced characterization of management heterogeneity across agroecological zones. For emissions accounting, we employ the DNDC (Denitrification–Decomposition) process-based model to simulate plot-scale methane (CH₄) emissions, nitrous oxide (N₂O) emissions, and changes in soil organic carbon (SOC). We further integrate emissions from on-farm energy use (fuel combustion) and upstream emissions embodied in agricultural inputs, thereby constructing a rice GHG inventory within a “cradle-to-farm-gate” system boundary. Compared with IPCC Tier 1 and Tier 2 approaches, DNDC can more explicitly capture how management variables, such as water depth, flooding duration, straw treatment, and fertilizer practices, affect CH₄ and N₂O emissions, thus better reflecting farmers’ actual management conditions.
Building on these data and methods, we develop a six-step analytical framework for assessing the cost-effectiveness of rice methane mitigation measures: (1) define the system boundary for accounting; (2) identify emission sources within the boundary; (3) identify candidate methane mitigation measures in rice production; (4) determine the GHG accounting method; (5) compile data and estimate emissions and costs; and (6) evaluate the cost-effectiveness of mitigation measures. The empirical analysis in this report is conducted following this framework.
The results show substantial differences across the four rice-growing areas in terms of the structure of farming entities, farmland conditions, cropping systems, sowing methods, and water management behaviors. These structural features jointly determine emission levels, cost structures, and the applicability of different technologies. Taijiang (Guizhou) and Mashan (Guangxi) are dominated by smallholder farmers; plots are fragmented and steeper, irrigation and drainage infrastructure are weak, and implementation capacity of mitigation measures is clearly constrained. In contrast, Hongze (Jiangsu) and Jiangshan (Zhejiang) have a higher share of family farms, larger operational scales, and more developed mechanization and agricultural service systems, providing a stronger foundation for implementing multiple low-carbon practices. Cropping systems display clear regional differentiation. Guizhou is characterized mainly by rice–fish co-cultivation and single-season rice. Guangxi is dominated by double-cropping rice. Jiangsu is centered on rice–wheat rotation, and Zhejiang features multiple coexisting systems. Sowing methods show a stepwise upgrading path from on-farm nursery raising to centralized nursery raising and then to direct seeding. Water management practices exhibit an improvement trend from continuous flooding to drainage at the end of tillering and further toward alternate wetting and drying (AWD). These features lead to regional differences in water-holding capacity, labor requirements, and infrastructure conditions, which are ultimately reflected in emissions and cost performance. In terms of emissions, paddy-field greenhouse gas emissions differ markedly across the four provinces. Taijiang (Guizhou) and Mashan (Guangxi) have significantly higher methane emissions than Hongze (Jiangsu) and Jiangshan (Zhejiang), due to steeper terrain, longer flooding periods, and a higher share of double-cropping rice. Hongze (Jiangsu) records the lowest emissions because of well-leveled fields, well-developed canal systems, and a mature rotation system. Jiangshan (Zhejiang), although with undulating terrain, exhibits intermediate emission levels thanks to more refined management.
With respect to the adoption of mitigation measures, the suitability and adoption levels of each technology show pronounced regional differences. AWD is most prevalent in Jiangsu and Zhejiang, supported by flatter fields and stronger water-level control capacity. In Taijiang (Guizhou) and Mashan (Guangxi), however, large slopes and weaker canal systems make large-scale implementation difficult. Direct seeding and rice–upland rotation have expanded rapidly in the eastern regions alongside mechanization. Guizhou also shows some uptake, while Guangxi, constrained by weed pressure and hilly terrain, has the lowest share of direct seeding among the four provinces. Owing to its double-cropping rice system, Mashan (Guangxi) has the highest adoption rate of short and medium duration rice varieties. Straw-return technologies are common in all four provinces but display clear regional patterns. Taijiang and Mashan mainly adopt straw mulching technology, whereas Jiangsu and Zhejiang predominantly adopt straw chopping and return to the field. No-tillage adoption is low across all four areas. Looking at farmers’ combinations of mitigation measures, farmers generally tend to stack 2–4 measures on a given plot rather than relying on a single technology. While combinations are diverse, “water management + straw return” remains the core pattern. Among them, the “AWD + straw chopping and return + direct seeding + crop rotation” package accounts for the largest share of observations.
Mitigation effects also differ significantly across technologies. Direct seeding significantly reduces greenhouse gas emissions from rice production. Compared with conventional nursery raising and transplanting, the mitigation amount is about 16.6 t CO₂-eq/ha, and the effect mainly comes from a substantial reduction in paddy methane emissions. The methane reduction from direct seeding is primarily related to water management, unlike transplanted rice that maintains flooded conditions, direct-seeded fields are generally kept moist rather than continuously inundated. This moist condition not only supports early seedling establishment and root growth, but also allows more air to enter the soil, thereby reducing methane emissions. Straw chopping and return to the field, straw surface mulching, rice–upland rotation, and straw incorporation into soil mainly deliver large mitigation effects by significantly increasing soil organic carbon (SOC) stocks, with carbon mitigation amounts of 13.0 t CO₂-eq/ha, 12.9 t CO₂-eq/ha, 11.5 t CO₂-eq/ha, and 8.8 t CO₂-eq/ha, respectively. Compared with traditional continuous flooding, AWD can reduce greenhouse gas emissions from rice paddies (13.6 t CO₂-eq/ha), but under current farming practices, irrigation and drainage conditions, and actual implementation intensity, its mitigation effect is not robust. Short and medium duration rice varieties show a tendency to reduce emissions. No-tillage and rice–fish farming increase paddy-field greenhouse gas emissions, but the results are not statistically significant.
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