Abstract

Countryside is an integral part of China's social and economic systems. For a long time, the continuous growth of rural carbon emissions has led to a series of social, economic and ecological consequences. Carbon emission reduction has become a critical task for rural revitalization and sustainable development in China. Existing studies on low-carbon assessment mainly focus on urban areas, resulting in limited studies on rural areas. What's more, most of the planning strategies for low-carbon villages are also based on subjective evaluation and qualitative analysis, lacking support from quantitative simulation. Combining relevant theories, the concept of a rural "carbon atlas" was proposed in this study. The current rural carbon emissions and mathematics, graphics, and rationales 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 types of rural areas dominated by different industries were analyzed to provide resources and guidelines for building and planning low-carbon countryside 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 tendentious distribution, periodical changes, and typified structures:(1) Different village types have different regional tendencies of high carbon emission. This phenomenon is most evident in industrial villages, where most of the carbon emissions happen in large factories or family workshops with large homestead areas. Traditional fishing and agricultural villages are the least representative in this regard because rural industries are mainly small fishing and agricultural families, and the industrial link among families is weak. (2) Due to the industry's cyclical nature, the fluctuation 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 their immunity to 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 optimization strategy and mechanism model. The outcomes from the current study explore the method and practical application of a rural carbon emission atlas, yet more extensive research exploring various facets of the atlas are still required.

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