Accounting for Land Use Carbon Emissions Considering Differences in Wetland Types to Support the Achievement of SDG 13.2.2

Abstract

In recent years, the relentless rise in global greenhouse gas (GHG) emissions has escalated climate change. Land‐use changes, particularly those involving wetlands, significantly impact GHG emissions. However, previous studies on land‐use carbon emissions often overlooked the specific contributions of different wetland types. This study aims to assess these differential contributions and explore strategies for managing GHG emissions (SDG 13.2.2) within the United Nation's sustainable development goals. The study used the Demonstration Zone of Green and Integrated Ecological Development of the Yangtze River Delta (demonstration area) in China as a case study to accurately classify wetland types from 2016 to 2022. Wetland classification was achieved using Sentinel‐2 remote sensing imagery and parameters such as NDVI and NDWI with the application of machine learning algorithms. To explore effective carbon management strategies, a scenario analysis method was employed to simulate future carbon emission trends under various management measures based on current emission status. The results revealed significant differences in carbon emissions among wetland types. From 2016 to 2022, ponds exhibited the highest total and growth rate of carbon emissions among all wetland types, while paddy fields alone showed a decreasing trend. Through enhanced natural wetland protection, optimized management, and reduced use of chemical fertilizers and pesticides, direct carbon emissions in the demonstration area were reduced by 2.61 × 105 t. Accurate wetland classification and differentiated management are crucial for carbon accounting and formulating effective reduction strategies. This study offers new insights into the sustainable development of the Yangtze River Delta.