LCA Assessment Data on the Carbon Emission Reduction Potential of Livestock and Poultry Manure Management in Ecologically Sensitive Areas: A Case Study of Danjiangkou City

This dataset supports the academic research entitled “LCA-based assessment of carbon mitigation potential of livestock manure management in ecologically sensitive areas: A case study of Danjiangkou City”. The core research hypothesis is that implementing a county-wide promotion project for manure resource utilization in Danjiangkou City—a key water source area for the South-to-North Water Diversion Central Route—can achieve significant synergistic greenhouse gas emission reductions through technological upgrades across the entire “excretion, cleaning, storage, treatment, and utilization” chain. The dataset contains the complete inventory data and results for the Life Cycle Assessment (LCA), mainly include： Activity Level Data: Foundational inventory data for Danjiangkou City, including herd sizes, feeding days, live weights, and nitrogen excretion rates for swine, beef cattle, laying hens, and goats at both county and township levels (2023). Emission Factor Parameters: CH4 and N2O emission factors (both direct and indirect), calibrated based on the IPCC 2019 Guidelines, national/provincial inventory lists, and localized studies. Key Findings and Data Interpretation: Data analysis confirms that the project is projected to achieve an overall system-wide carbon emission reduction of 40.83%. The data clearly reveals that the choice of technology model is decisive: the Sedimentation-Crop Model shows the highest reduction rate (61.50%), primarily due to the synergistic effect of its closed-pipeline manure removal and biochemical cracking technology. In contrast, the Raised-Bedding Composting Model, which relies on front-end manual scraping, shows a lower reduction rate (27.70%), highlighting the limitations of single end-of-pipe upgrades in decentralized farming systems. Sensitivity analysis data identifies the CH4 emission factor as the primary source of uncertainty in the system’s reduction potential. Data Usage Instructions: Researchers can use this dataset to validate, reproduce, or extend related LCA models. The data can be directly applied to assess the carbon mitigation efficacy of livestock manure management technologies in similar ecologically sensitive areas (especially water source conservation zones) within subtropical and temperate regions of China, providing quantitative evidence for regional agricultural green development planning and “Dual Carbon” policy formulation. When applying the data, emission factors should be appropriately calibrated according to the specific geographical and climatic conditions of the case study.本数据集支撑题为《基于生命周期评估（Life Cycle Assessment，LCA）的生态敏感区畜禽粪便管理碳减排潜力评估——以丹江口市为例》的学术研究。本研究核心假说为：作为南水北调中线工程核心水源区的丹江口市，若在全市范围内推进畜禽粪便资源化利用项目，可通过打通“排泄、清粪、储存、处理与利用”全链条的技术升级，实现温室气体减排的显著协同效应。 本数据集包含完整的生命周期评估清单数据及结果，主要包括： 1. 活动水平数据：丹江口市2023年县域及乡镇级的畜禽养殖基础清单数据，涵盖猪、肉牛、蛋鸡、山羊的存栏规模、饲养天数、活体体重及氮排泄率。 2. 排放因子参数：基于IPCC 2019年指南、国家/省级排放清单及本地化研究校准得到的甲烷（Methane, CH4）与氧化亚氮（Nitrous Oxide, N2O）直接及间接排放因子。 核心研究结果与数据解读： 数据分析证实，该项目预计可实现全系统范围内40.83%的碳减排。数据清晰表明，技术模式的选择具有决定性作用：沉淀-种植模式（Sedimentation-Crop Model）的减排率最高，达61.50%，这主要得益于其封闭式管道清粪与生化裂解技术的协同效应。与之相对，依赖前端人工刮粪的垫料堆肥模式（Raised-Bedding Composting Model）的减排率仅为27.70%，这凸显了分散养殖体系中单一端治理升级的局限性。敏感性分析数据显示，甲烷（CH4）排放因子是系统减排潜力不确定性的主要来源。 数据使用说明： 研究人员可利用本数据集验证、复现或拓展相关生命周期评估模型。该数据可直接应用于中国亚热带与温带地区同类生态敏感区（尤其是水源涵养区）的畜禽粪便管理技术碳减排效能评估，为区域农业绿色发展规划及“双碳”政策制定提供量化依据。在使用该数据时，需结合研究案例的具体地理与气候条件对排放因子进行适当校准。