{"title":"中国池塘甲烷排放加剧:变暖、富营养化和深度变化的相互作用","authors":"Mingquan Lv, Ping Huang, Xin Gao, Jilong Chen, Shengjun Wu","doi":"10.1016/j.watres.2025.123576","DOIUrl":null,"url":null,"abstract":"<div><div>Ponds are significant contributors to global methane (CH<sub>4</sub>) emissions. However, accurately estimating their historical or future CH<sub>4</sub> emissions remains challenging, particularly under dynamic environmental changes such as eutrophication, sedimentation-driven shallowing, and global warming. We synthesized 674 observations of CH₄ emission rates to identify key drivers and develop a process-based predictive model. We present a framework for spatially explicit estimation of pond CH₄ emissions in China from 1960 to 2020, accounting for factors such as temperature dependence, depth, nutrient levels, and pond area. Our findings show that pond CH₄ emissions are strongly temperature-dependent, characterized by a high average activation energy (0.834 eV). Notably, ebullitive emissions exhibit greater temperature sensitivity than diffusive emissions. Nitrogen concentrations and water column depth emerged as critical predictors of total CH₄ fluxes. Over the past six decades, CH₄ emissions from Chinese ponds increased approximately 9-fold, from 0.16 Tg CH₄ yr<sup>−1</sup> in 1960 to 1.53 Tg CH₄ yr⁻¹ by 2020, emphasizing their growing role in global methane emissions. Notably, half of these emissions occur during summer, with ebullition accounting for 66 % of the total CH₄ flux. This increase was primarily driven by the interactions of warming, nutrient enrichment, declining water depth, and pond expansion. Our results underscore the growing role of ponds in CH₄ emissions and highlight the urgent need for mitigation measures, such as reducing nutrient loading and implementing periodic dredging management. This study provides a robust foundation for improving CH₄ emission estimates and developing sustainable management practices for ponds in the context of global environmental change.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"281 ","pages":"Article 123576"},"PeriodicalIF":12.4000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intensifying methane emissions in Chinese Ponds: The interplay of warming, eutrophication, and depth changes\",\"authors\":\"Mingquan Lv, Ping Huang, Xin Gao, Jilong Chen, Shengjun Wu\",\"doi\":\"10.1016/j.watres.2025.123576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Ponds are significant contributors to global methane (CH<sub>4</sub>) emissions. However, accurately estimating their historical or future CH<sub>4</sub> emissions remains challenging, particularly under dynamic environmental changes such as eutrophication, sedimentation-driven shallowing, and global warming. We synthesized 674 observations of CH₄ emission rates to identify key drivers and develop a process-based predictive model. We present a framework for spatially explicit estimation of pond CH₄ emissions in China from 1960 to 2020, accounting for factors such as temperature dependence, depth, nutrient levels, and pond area. Our findings show that pond CH₄ emissions are strongly temperature-dependent, characterized by a high average activation energy (0.834 eV). Notably, ebullitive emissions exhibit greater temperature sensitivity than diffusive emissions. Nitrogen concentrations and water column depth emerged as critical predictors of total CH₄ fluxes. Over the past six decades, CH₄ emissions from Chinese ponds increased approximately 9-fold, from 0.16 Tg CH₄ yr<sup>−1</sup> in 1960 to 1.53 Tg CH₄ yr⁻¹ by 2020, emphasizing their growing role in global methane emissions. Notably, half of these emissions occur during summer, with ebullition accounting for 66 % of the total CH₄ flux. This increase was primarily driven by the interactions of warming, nutrient enrichment, declining water depth, and pond expansion. Our results underscore the growing role of ponds in CH₄ emissions and highlight the urgent need for mitigation measures, such as reducing nutrient loading and implementing periodic dredging management. This study provides a robust foundation for improving CH₄ emission estimates and developing sustainable management practices for ponds in the context of global environmental change.</div></div>\",\"PeriodicalId\":443,\"journal\":{\"name\":\"Water Research\",\"volume\":\"281 \",\"pages\":\"Article 123576\"},\"PeriodicalIF\":12.4000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0043135425004890\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0043135425004890","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Intensifying methane emissions in Chinese Ponds: The interplay of warming, eutrophication, and depth changes
Ponds are significant contributors to global methane (CH4) emissions. However, accurately estimating their historical or future CH4 emissions remains challenging, particularly under dynamic environmental changes such as eutrophication, sedimentation-driven shallowing, and global warming. We synthesized 674 observations of CH₄ emission rates to identify key drivers and develop a process-based predictive model. We present a framework for spatially explicit estimation of pond CH₄ emissions in China from 1960 to 2020, accounting for factors such as temperature dependence, depth, nutrient levels, and pond area. Our findings show that pond CH₄ emissions are strongly temperature-dependent, characterized by a high average activation energy (0.834 eV). Notably, ebullitive emissions exhibit greater temperature sensitivity than diffusive emissions. Nitrogen concentrations and water column depth emerged as critical predictors of total CH₄ fluxes. Over the past six decades, CH₄ emissions from Chinese ponds increased approximately 9-fold, from 0.16 Tg CH₄ yr−1 in 1960 to 1.53 Tg CH₄ yr⁻¹ by 2020, emphasizing their growing role in global methane emissions. Notably, half of these emissions occur during summer, with ebullition accounting for 66 % of the total CH₄ flux. This increase was primarily driven by the interactions of warming, nutrient enrichment, declining water depth, and pond expansion. Our results underscore the growing role of ponds in CH₄ emissions and highlight the urgent need for mitigation measures, such as reducing nutrient loading and implementing periodic dredging management. This study provides a robust foundation for improving CH₄ emission estimates and developing sustainable management practices for ponds in the context of global environmental change.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.