Hongqiao Chen , Hengyu Pan , Shijiang Xiao , Shihuai Deng
{"title":"从2020年到2060年,中国水电水库的温室气体排放主要是一氧化二氮","authors":"Hongqiao Chen , Hengyu Pan , Shijiang Xiao , Shihuai Deng","doi":"10.1016/j.watres.2025.123420","DOIUrl":null,"url":null,"abstract":"<div><div>China is ambitious to increase its hydropower share to mitigate climate changes. The greenhouse gas (GHG) emissions from hydroelectric reservoirs may hinder the climate goal. The spatio-temporal patterns of such emissions under future climate changes at the national scale are not clearly addressed. In this study, we evaluate these emissions from 79 hydroelectric reservoirs across China (61.22 % of the national hydropower generation) in 2020, covering carbon dioxide (CO<sub>2</sub>), methane (CH<sub>4</sub>), and nitrous oxide (N<sub>2</sub>O), using the G-res (Greenhouse Gas Reservoir) tool and Integrated Model to Assess the Global Environment–Dynamic Global Nutrient Model (IMAGE-DGNM). A random forest (RF) model is also used to project the emissions in the period of 2020 to 2060 under Shared Socioeconomic Pathway (SSP) scenarios. The results indicate that the carbon intensity (CI) and areal flux varied largely. The reservoirs located in low-altitude areas and older reservoirs generally have higher CIs. N<sub>2</sub>O contributed with more than 80 % of the total GHG emission, in which the NH<sub>4</sub><sup>+</sup> concentration is a key factor influencing the N<sub>2</sub>O emissions. The projection shows that these emissions will increase by 1.30 %, 6.63 %, and 17.33 % in 2060 compared to 2020 under the SSP119, SSP245, and SSP585 scenarios, respectively, in which CH<sub>4</sub> has the largest growth. Finally, implications toward reduction in such emissions are discussed.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123420"},"PeriodicalIF":12.4000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nitrous oxide dominates greenhouse gas emissions from hydropower's reservoirs in China from 2020 to 2060\",\"authors\":\"Hongqiao Chen , Hengyu Pan , Shijiang Xiao , Shihuai Deng\",\"doi\":\"10.1016/j.watres.2025.123420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>China is ambitious to increase its hydropower share to mitigate climate changes. The greenhouse gas (GHG) emissions from hydroelectric reservoirs may hinder the climate goal. The spatio-temporal patterns of such emissions under future climate changes at the national scale are not clearly addressed. In this study, we evaluate these emissions from 79 hydroelectric reservoirs across China (61.22 % of the national hydropower generation) in 2020, covering carbon dioxide (CO<sub>2</sub>), methane (CH<sub>4</sub>), and nitrous oxide (N<sub>2</sub>O), using the G-res (Greenhouse Gas Reservoir) tool and Integrated Model to Assess the Global Environment–Dynamic Global Nutrient Model (IMAGE-DGNM). A random forest (RF) model is also used to project the emissions in the period of 2020 to 2060 under Shared Socioeconomic Pathway (SSP) scenarios. The results indicate that the carbon intensity (CI) and areal flux varied largely. The reservoirs located in low-altitude areas and older reservoirs generally have higher CIs. N<sub>2</sub>O contributed with more than 80 % of the total GHG emission, in which the NH<sub>4</sub><sup>+</sup> concentration is a key factor influencing the N<sub>2</sub>O emissions. The projection shows that these emissions will increase by 1.30 %, 6.63 %, and 17.33 % in 2060 compared to 2020 under the SSP119, SSP245, and SSP585 scenarios, respectively, in which CH<sub>4</sub> has the largest growth. Finally, implications toward reduction in such emissions are discussed.</div></div>\",\"PeriodicalId\":443,\"journal\":{\"name\":\"Water Research\",\"volume\":\"279 \",\"pages\":\"Article 123420\"},\"PeriodicalIF\":12.4000,\"publicationDate\":\"2025-03-01\",\"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/S0043135425003331\",\"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/S0043135425003331","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}
Nitrous oxide dominates greenhouse gas emissions from hydropower's reservoirs in China from 2020 to 2060
China is ambitious to increase its hydropower share to mitigate climate changes. The greenhouse gas (GHG) emissions from hydroelectric reservoirs may hinder the climate goal. The spatio-temporal patterns of such emissions under future climate changes at the national scale are not clearly addressed. In this study, we evaluate these emissions from 79 hydroelectric reservoirs across China (61.22 % of the national hydropower generation) in 2020, covering carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), using the G-res (Greenhouse Gas Reservoir) tool and Integrated Model to Assess the Global Environment–Dynamic Global Nutrient Model (IMAGE-DGNM). A random forest (RF) model is also used to project the emissions in the period of 2020 to 2060 under Shared Socioeconomic Pathway (SSP) scenarios. The results indicate that the carbon intensity (CI) and areal flux varied largely. The reservoirs located in low-altitude areas and older reservoirs generally have higher CIs. N2O contributed with more than 80 % of the total GHG emission, in which the NH4+ concentration is a key factor influencing the N2O emissions. The projection shows that these emissions will increase by 1.30 %, 6.63 %, and 17.33 % in 2060 compared to 2020 under the SSP119, SSP245, and SSP585 scenarios, respectively, in which CH4 has the largest growth. Finally, implications toward reduction in such emissions are discussed.
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.