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The growing demand for food has led to overuse of land, exacerbating the environmental sustainability of agrifood systems. Insufficient coordination and coupling within agrifood systems (soil-crop-animal-food consumption) reduce material cycle efficiency and limit the system's carbon reduction potential. Given the lack of global research on the impact of system coupling on carbon reduction, the value of regional practice cases is particularly evident. To address this issue, we propose a systematic, integrated multiple-methods framework-agrifood systems carbon and nitrogen (AFS-CN)-that considers the feedback mechanisms between system coupling, carbon balance, and nitrogen management. This framework is applied to a typical county in Zhejiang Province, China, which is characterized by a high level of economic development and diverse agricultural production patterns. The results indicate that the AFS-CN framework can link subsystem coupling coordination with soil carbon sequestration and crop-animal-food consumption carbon emissions. The crop subsystem is the primary emission source, accounting for 72 %-83 % of total carbon emissions, followed by the food consumption subsystem, while the soil subsystem plays a minor role in carbon sequestration. As agrifood systems coupled coordination degree (CCD) increases, carbon emissions initially decrease rapidly before gradually flattening out. When the CCD exceeds 0.6, the trend of carbon emissions reduction begins to slow down. The soil subsystem indirectly exerts a net positive influence on the food consumption subsystem through the crop subsystem. This study provides new perspectives and methods for understanding the coupling coordination mechanisms of the agrifood systems and formulating carbon emissions reduction strategies.
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http://dx.doi.org/10.1016/j.jenvman.2025.127156 | DOI Listing |
Environ Monit Assess
September 2025
Department of Environment and Life Science, KSKV Kachchh University, Bhuj, Gujarat, 370 001, India.
India's energy demand increased by 7.3% in 2023 compared to 2022 (5.6%), primarily met by coal-based thermal power plants (TPPs) that contribute significantly to greenhouse gas emissions.
View Article and Find Full Text PDFLight Sci Appl
September 2025
Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031, Hefei, China.
Marine vessels play a vital role in the global economy; however, their negative impact on the marine atmospheric environment is a growing concern. Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment. Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions.
View Article and Find Full Text PDFWaste Manag
September 2025
Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, School of Environmental Science & Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address:
As one of the major sources of greenhouse gas (GHG) emissions, the municipal solid waste (MSW) management system was regarded as a key contributor to the construction of a low-carbon society. Understanding the evolution of waste treatment facilities and the corresponding GHG emissions was essential for assessing the low-carbon competitiveness of local communities. In this study, facility-level data were used to estimate GHG emissions from the waste management system in the Yangtze River Delta (YRD) and analyze their temporal and spatial variations.
View Article and Find Full Text PDFMar Environ Res
August 2025
Departamento de Biología Animal, Edafología y Geología. Facultad de Ciencias. Sección Biología. Universidad de La Laguna, Tenerife, Canary Islands, Spain.
Anthropogenic CO emissions drive ocean acidification (OA), which reduces seawater pH and carbonate ion availability, threatening calcifying organisms such as sea urchins. This study examines the long-term effects of OA on Arbacia lixula using a natural volcanic CO vent at Fuencaliente, La Palma (Canary Islands) as an analogue of future conditions. We analyzed the external morphology, skeletal strength, mineralogy, and growth of A.
View Article and Find Full Text PDFJ Environ Manage
September 2025
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Dissolved oxygen (DO) is a key water quality indicator reflecting river health. Modeling and understanding the spatiotemporal dynamics of DO and its influencing factors are crucial for effective river management. Machine learning (ML) models have gained popularity in water quality prediction; however, their accuracy strongly depends on the predictor variables.
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