{"title":"Unveiling the dynamic flows and spatial inequalities arising from agricultural methane and nitrous oxide emissions","authors":"Fan Zhang , Yuping Bai , Xin Xuan , Ying Cai","doi":"10.1016/j.ecoinf.2024.102863","DOIUrl":null,"url":null,"abstract":"<div><div>Tracing the spatial transfer and heterogeneity of agricultural methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O) emissions in China is a prerequisite for the sustainable transformation of agricultural systems. In this study, we established a research framework for evaluating agricultural CH<sub>4</sub> and N<sub>2</sub>O flows and convergence. Using this framework, we established an inventory of China's agricultural CH<sub>4</sub> and N<sub>2</sub>O emissions calculated according to the IPCC inventory guidelines, built a food trade model to simulate the spatial transfer, and revealed the regional differences. Finally, we analyzed the influence mechanism by combining extended Kaya identity and the logarithmic mean divisia index (LMDI) model. We found that inter-regional transfer of agricultural CH<sub>4</sub> and N<sub>2</sub>O emissions in China have intensified, increasing from 56.14 % of total transfers in 2000 to 67.28 % in 2019. The spatial inequalities of agricultural CH<sub>4</sub> and N<sub>2</sub>O increased, and emission intensity varied more within regions than between regions, with per capita emissions showing a club convergence with “intragroup convergence and intergroup divergence”. Although the contribution of agricultural CH<sub>4</sub> and N<sub>2</sub>O emissions varies across provinces, controlling emissions intensity and land use intensity while maintaining GDP per capita is the key to emission mitigation. Our study provides theoretical support for prioritizing policies to mitigate agricultural CH<sub>4</sub> and N<sub>2</sub>O emissions.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"84 ","pages":"Article 102863"},"PeriodicalIF":5.8000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954124004059","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Tracing the spatial transfer and heterogeneity of agricultural methane (CH4) and nitrous oxide (N2O) emissions in China is a prerequisite for the sustainable transformation of agricultural systems. In this study, we established a research framework for evaluating agricultural CH4 and N2O flows and convergence. Using this framework, we established an inventory of China's agricultural CH4 and N2O emissions calculated according to the IPCC inventory guidelines, built a food trade model to simulate the spatial transfer, and revealed the regional differences. Finally, we analyzed the influence mechanism by combining extended Kaya identity and the logarithmic mean divisia index (LMDI) model. We found that inter-regional transfer of agricultural CH4 and N2O emissions in China have intensified, increasing from 56.14 % of total transfers in 2000 to 67.28 % in 2019. The spatial inequalities of agricultural CH4 and N2O increased, and emission intensity varied more within regions than between regions, with per capita emissions showing a club convergence with “intragroup convergence and intergroup divergence”. Although the contribution of agricultural CH4 and N2O emissions varies across provinces, controlling emissions intensity and land use intensity while maintaining GDP per capita is the key to emission mitigation. Our study provides theoretical support for prioritizing policies to mitigate agricultural CH4 and N2O emissions.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.