| 摘要: |
| 开展村落尺度温室气体排放源识别及核算是科学应对气候变化并实现低碳城乡建设的重要前提。以河南省邑西里村为研究对象，基于问卷调查和实际走访并结合文献检索建立村落温室气体核算数据库，设计了村落尺度温室气体排放核算框架，从农业生产、畜禽养殖、居民生活和基础设施等四个方面展开了村落尺度温室气体核算，实现以自然村为基本单元的村落温室气体排放的精准评估。结果表明：（1）2020年人均温室气体排放量为5.20 t（以CO2计，余同），户均排放量为20.01 t。（2）居民生活排放占比为84.80%；其次分别为基础设施、农业生产和畜禽养殖，占比依次为8.46%、6.45%和0.29%。（3）直接和间接排放的温室气体分别为852 t及7153 t，分别占10.64%和89.36%。研究成果有助于推进城乡低碳建设进而实现双碳目标，为基于高时空分辨率的城乡温室气体治理提供支撑。 |
| 关键词: 村落尺度 温室气体排放源 低碳发展 人地关系 |
| DOI：10.7515/JEE222072 |
| CSTR：32259.14.JEE222072 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41971166）；中国科学院区域发展青年学者计划（2021-003）；中国科学院战略性先
导科技专项（XDA2307050305） |
| 英文基金项目:National Natural Science Foundation of China (41971166); Young Scholars Program for Regional Development of
Chinese Academy of Sciences (2021-003); Strategic Priority Research Program of the Chinese Academy of Sciences
(XDA2307050305) |
|
| Village-scale greenhouse gas emission accounting methodology and empirical study: a case of Yixili Village in Henan Province |
|
XU Yueping, HAN Bin, LI Hongqing, ZHANG Lihua, XUE Bing
|
1. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. College of Geography and Environment, Shandong Normal University, Jinan 250358, China
|
| Abstract: |
| Background, aim, and scope The study of greenhouse gas (GHG) emission at the village-scale plays an essential fundamental role in promoting low-carbon management and sustainable development in urban and rural areas. However, the current research on village-scale GHG emission accounting is still relatively blank, mainly due to the lack of integrated analysis methodology and research paradigms. Materials and methods The data were obtained mainly from on-site surveys, statistical yearbooks, and periodical literature. For the collection of micro-level data, based on IPCC national greenhouse gases emission inventory and provincial greenhouse gases inventory, the corresponding greenhouse gas emission sources were identified. Then, the village-level greenhouse gases emission sources were divided into seven categories, including industrial activities, agricultural production, tertiary industry, household, livestock breeding, infrastructure, and fisheries. With one year as the time unit, the life cycle assessment method was adopted to study the greenhouse gas emission accounting and structure of the surveyed village. Results The main activity of greenhouse gas emission consisted of agricultural production, livestock breeding, household, and infrastructure, and both direct emission and indirect emissions were considered. The per capita GHG emissions in 2020 were 5.20 t, and the average household emissions were 20.01 t. The residential emissions account for 84.80%, followed by infrastructure, agricultural production, and livestock breeding, accounting for 8.46%, 6.45%, and 0.29%, respectively. The direct and indirect GHG emissions were 852 t and 7153 t, accounting for 10.64% and 89.36%, respectively. Discussion We argue that a more complete and systematic accounting framework for village GHG emissions needs to be constructed to account for GHG emissions more accurately at the village-scale. However, because the study villages mainly rely on agricultural cultivation and outworking as their livelihoods, the specific GHG emission processes related to rural industries and tertiary industries were not considered when conducting the accounting. We also stated that there are still different degrees of differences in the selection of emission coefficients due to various influencing factors such as region and time and space, and the refinement of coefficients should be strengthened in the future. Conclusions Based on identifying GHG emission sources in the Yixili Village, an accounting framework for GHG emission sources at the village-scale was designed, and the 2020 emissions of the case village were accounted for. Carrying out the GHG emission accounting study in villages can help to understand the sources and structural composition of GHG emissions and provide scientific ideas for rural low-carbon governance at high spatial and temporal resolutions. Recommendations and perspectives Rural areas are emerging greenhouse gases emission growth points in China. To achieve more accurate dynamic accounting, statistics, and research on human activity data in village and town areas should be strengthened, an extensive database should be established, and research on emission factors should be enhanced to improve the accuracy of calculations. It also strengthens rural low-carbon governance and promotes green transformation. |
| Key words: village-scale GHG emission sources low carbon development human-natural relationship |
