{"title":"农业能源转型路径:印度细粮和粗粮对温室气体排放的差异影响","authors":"Smily Thakur , Baljinder Kaur Sidana , Sunny Kumar , Ramandeep Kumar Sharma , Meetpal Singh Kukal , Samanpreet Kaur , Asim Biswas","doi":"10.1016/j.nexus.2025.100484","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding how agricultural energy use and cereal production choices—particularly between fine and coarse cereals—shape greenhouse gas (GHG) emissions is crucial for designing effective mitigation strategies in light of agriculture’s major contribution to national emissions and growing climate-induced productivity concerns. This study investigates the dynamic relationships between these factors in India using an Autoregressive Distributed Lag (ARDL) model on data spanning 1975–2019. Pre-analysis (Unit root, an ideal lag length, and co-integration testing) and post-analysis (serial correlation, heteroscedasticity, and recursive residuals) assumptions for ARDL model estimation were tested which came aligned with the research questions. The model robustness statistical diagnostic tests CUSUM (cumulative sum), CUSUMSQ (cumulative sum of squares), and variance decomposition testing were carried out and found to be satisfactory. The study aimed to provide comprehensive analysis of how different cereal types i.e. fine versus coarse cereals influence agricultural energy-emissions relationship and their long run effects on agricultural production-emission scenario of India. Our analysis reveals significant differences in the emissions impacts of different cereal types: while rice and wheat production contribute positively to emissions in the short run (0.06 % and 0.01 % respectively), coarse cereals demonstrate a substantial negative impact (−2.08 %) in the long run. The energy-emissions relationship shows increasing coupling over time, with elasticity rising from 0.02 % in the short run to 1.06 % in the long run. Variance decomposition analysis identifies rice production as the dominant contributor to emissions variability, accounting for 34.43 % of future fluctuations. These findings suggest that strategic crop diversification, particularly increased cultivation of coarse cereals, could significantly reduce agricultural emissions while maintaining food security. The study recommends a three-pronged approach i.e., investing in energy-efficient agricultural technologies, developing policy frameworks to incentivize coarse cereal adoption, and strengthening institutional mechanisms for technology transfer. These insights contribute to the development of targeted policies for sustainable agricultural energy transition in India.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100484"},"PeriodicalIF":8.0000,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agricultural energy transition pathways: Differential impacts of fine and coarse cereals on GHG emissions in India\",\"authors\":\"Smily Thakur , Baljinder Kaur Sidana , Sunny Kumar , Ramandeep Kumar Sharma , Meetpal Singh Kukal , Samanpreet Kaur , Asim Biswas\",\"doi\":\"10.1016/j.nexus.2025.100484\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Understanding how agricultural energy use and cereal production choices—particularly between fine and coarse cereals—shape greenhouse gas (GHG) emissions is crucial for designing effective mitigation strategies in light of agriculture’s major contribution to national emissions and growing climate-induced productivity concerns. This study investigates the dynamic relationships between these factors in India using an Autoregressive Distributed Lag (ARDL) model on data spanning 1975–2019. Pre-analysis (Unit root, an ideal lag length, and co-integration testing) and post-analysis (serial correlation, heteroscedasticity, and recursive residuals) assumptions for ARDL model estimation were tested which came aligned with the research questions. The model robustness statistical diagnostic tests CUSUM (cumulative sum), CUSUMSQ (cumulative sum of squares), and variance decomposition testing were carried out and found to be satisfactory. The study aimed to provide comprehensive analysis of how different cereal types i.e. fine versus coarse cereals influence agricultural energy-emissions relationship and their long run effects on agricultural production-emission scenario of India. Our analysis reveals significant differences in the emissions impacts of different cereal types: while rice and wheat production contribute positively to emissions in the short run (0.06 % and 0.01 % respectively), coarse cereals demonstrate a substantial negative impact (−2.08 %) in the long run. The energy-emissions relationship shows increasing coupling over time, with elasticity rising from 0.02 % in the short run to 1.06 % in the long run. Variance decomposition analysis identifies rice production as the dominant contributor to emissions variability, accounting for 34.43 % of future fluctuations. These findings suggest that strategic crop diversification, particularly increased cultivation of coarse cereals, could significantly reduce agricultural emissions while maintaining food security. The study recommends a three-pronged approach i.e., investing in energy-efficient agricultural technologies, developing policy frameworks to incentivize coarse cereal adoption, and strengthening institutional mechanisms for technology transfer. These insights contribute to the development of targeted policies for sustainable agricultural energy transition in India.</div></div>\",\"PeriodicalId\":93548,\"journal\":{\"name\":\"Energy nexus\",\"volume\":\"19 \",\"pages\":\"Article 100484\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy nexus\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772427125001251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy nexus","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772427125001251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Agricultural energy transition pathways: Differential impacts of fine and coarse cereals on GHG emissions in India
Understanding how agricultural energy use and cereal production choices—particularly between fine and coarse cereals—shape greenhouse gas (GHG) emissions is crucial for designing effective mitigation strategies in light of agriculture’s major contribution to national emissions and growing climate-induced productivity concerns. This study investigates the dynamic relationships between these factors in India using an Autoregressive Distributed Lag (ARDL) model on data spanning 1975–2019. Pre-analysis (Unit root, an ideal lag length, and co-integration testing) and post-analysis (serial correlation, heteroscedasticity, and recursive residuals) assumptions for ARDL model estimation were tested which came aligned with the research questions. The model robustness statistical diagnostic tests CUSUM (cumulative sum), CUSUMSQ (cumulative sum of squares), and variance decomposition testing were carried out and found to be satisfactory. The study aimed to provide comprehensive analysis of how different cereal types i.e. fine versus coarse cereals influence agricultural energy-emissions relationship and their long run effects on agricultural production-emission scenario of India. Our analysis reveals significant differences in the emissions impacts of different cereal types: while rice and wheat production contribute positively to emissions in the short run (0.06 % and 0.01 % respectively), coarse cereals demonstrate a substantial negative impact (−2.08 %) in the long run. The energy-emissions relationship shows increasing coupling over time, with elasticity rising from 0.02 % in the short run to 1.06 % in the long run. Variance decomposition analysis identifies rice production as the dominant contributor to emissions variability, accounting for 34.43 % of future fluctuations. These findings suggest that strategic crop diversification, particularly increased cultivation of coarse cereals, could significantly reduce agricultural emissions while maintaining food security. The study recommends a three-pronged approach i.e., investing in energy-efficient agricultural technologies, developing policy frameworks to incentivize coarse cereal adoption, and strengthening institutional mechanisms for technology transfer. These insights contribute to the development of targeted policies for sustainable agricultural energy transition in India.
Energy nexusEnergy (General), Ecological Modelling, Renewable Energy, Sustainability and the Environment, Water Science and Technology, Agricultural and Biological Sciences (General)