关键词: 低碳乡村, 碳图谱, 时空特征, 长三角地区

Abstract: Countryside is an integral part of China's social and economic system. For a long time, the continuous growth of rural carbon emissions has led to a series of social, economic and ecological consequences. Carbon emission reductions have become the critical content of rural revitalisation and sustainable development in China. Existing studies on low-carbon assessment mainly focus on urban areas, resulting in limited studies on rural areas. Most of the planning strategies for low-carbon villages are also based on subjective evaluation and qualitative analysis, lacking quantitative simulation support. Combining relevant theories, the concept of a rural "carbon atlas" was proposed in this study. The current rural carbon emissions and mathematics, graphics, and rationals of the temporal-spatial evolutionary characteristics were investigated using the GIS system as the technical platform for information storage and processing. The spatial domain of carbon emission units based on microscopic residential sites, factories and markets was defined and investigated. Carbon emissions of each unit were estimated according to energy consumptions for life, production and transportation. Later, carbon emissions were expressed and presented visually within the "atlas". Meanwhile, temporal and spatial distribution patterns of carbon emissions in various rural types dominated by different industries were analysed to provide resources and guidelines for building and planning low-carbon countrysides and villages.
　　An empirical study was undertaken on four different village types, dominated by different industries in the Yangtze River Delta. Results show that the rural carbon atlas has apparent characteristics of tendentiously distributing, periodically changing, and typified structures: (1) Different village types have different regional tendencies of high carbon emission. The industrial villages are the most significant, where high carbon emission areas mostly appear in large factories or family workshops with large homestead areas. Traditional fishing and agricultural villages are the least obvious because rural industries are mainly small fishing and agricultural families, and the industrial relevance among families is weak. (2) Due to the industry's cyclical nature, the volatility of carbon emissions in different types of villages is significantly different. Since the leisure tourism industry is greatly affected by festivals and seasons, the carbon emissions in leisure tourism villages fluctuate the most. Carbon emission of professional markets is the most stable, which is attributed to free affection by seasonal and climatic changes. (3) The rural carbon emission map has prominent typified structural characteristics, including the scattered homogeneous pattern (traditional fishing and agricultural village), the group infiltration pattern (industrial production village), the dissipative fragmentation pattern (leisure tourism village), and the kernel domain recursive pattern (professional market village). Different industrial types lead to noticeable regional differences in the temporal-spatial characteristics and trends of carbon atlas. Hence, there is an urgent need to develop an overall optimisation strategy and mechanism model. The outcomes from the current study explore the method and practical application of a rural carbon emission atlas, however more extensive research exploring various facets of the atlas are still required. 

Key words: low-carbon villages, carbon atlas, spatial-temporal characteristic, the Yangtze River Delta