A study on the correlation of agricultural carbon emissions in Liaoning Province based on the Spearman correlation coefficient

Abstract

With the rapid development in the field of modern agriculture, an in-depth investigation into various types of agricultural carbon emissions provides essential insights into understanding the spatial patterns and evolving trends of agricultural carbon emissions in China. Taking Liaoning Province as a case study, this paper collects historical monitoring data on agricultural carbon emissions from all provinces and direct-controlled municipalities in China from 2000 to 2020. The data undergoes preprocessing, with missing values addressed using the nearest-neighbor imputation method. Subsequently, based on the IPCC carbon emission coefficient method, the paper calculates the annual agricultural carbon emissions for various categories in Liaoning Province. The study employs scatter plots to make preliminary judgments on the correlation between different carbon emission categories. Finally, an in-depth analysis is conducted using the Spearman correlation coefficient method to explore the relationships among different carbon sources. The research reveals a high correlation among certain carbon sources, providing scientific guidance for reducing agricultural carbon emissions.