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This research addressed the issue of low-carbon development in hydropower, provided a review of the key factors influencing the carbon footprint of hydropower and the regional variations in these footprints. The findings of this research indicated an increasing global focus on research into the carbon footprint of hydropower. Case studies revealed that the primary contributors to the hydropower carbon footprint were the manufacture of construction materials and engineering activities during the construction phase, as well as energy consumption by equipment during the operation and maintenance phase. This research identified key factors affecting hydropower carbon emissions, including the type of hydropower, installed capacity, water storage volume, reservoir area, and life cycle stages. Furthermore, from a geographical perspective, it explored the regional variation in hydropower carbon emissions, highlighting the impact of differences in climate, precipitation, and ecological environment due to geographical location on the hydropower carbon footprint.

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面向水电低碳发展问题,对水电碳足迹关键影响因素及水电碳足迹区域化差异进行综述研究.结果表明,全球范围内对现有水电碳足迹研究的关注度不断增高.通过案例研究发现,水电碳足迹主要由建设阶段的建材制造和工程施工,以及运行维护阶段的设备运行耗能产生.总结了影响水电碳排放的关键因素:水电类型、装机量、蓄水量、蓄水区面积和生命周期阶段等,并从地理空间的视角对水电碳排放进行了区域化研究,指出因地理位置不同导致的气候、降水量、生态环境等差异对水电碳足迹的影响.

, correspAuthors=张高翔, authorNote=null, correspAuthorsNote=
* 责任作者,硕士,科研助理,
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李朋(1986-),男,湖北仙桃人,高级工程师,博士.主要从事能源与环保领域、绿色供应链相关研究.发表论文20余篇..

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李朋(1986-),男,湖北仙桃人,高级工程师,博士.主要从事能源与环保领域、绿色供应链相关研究.发表论文20余篇..

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李朋(1986-),男,湖北仙桃人,高级工程师,博士.主要从事能源与环保领域、绿色供应链相关研究.发表论文20余篇..

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The provincial hydrological bureau compiled and issued the "2022 Yunnan Hydrological Situation Report"_Yunnan Provincial Department of Water Resources [EB/OL]. http://wcb.yn.gov.cn/html/2023/yewuzhuanlan_0315/56088.html.2023/2024-06-20., articleTitle=The provincial hydrological bureau compiled and issued the "2022 Yunnan Hydrological Situation Report"_Yunnan Provincial Department of Water Resources, refAbstract=null), Reference(id=1241408736808456913, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, doi=null, pmid=null, pmcid=null, year=2011, volume=36, issue=11, pageStart=2799, pageEnd=2808, url=null, language=null, rfNumber=[63], rfOrder=81, authorNames=Pascale A, Urmee T, Moore A, journalName=Renewable Energy, refType=null, unstructuredReference=Pascale AUrmee TMoore A. Life cycle assessment of a community hydroelectric power system in rural Thailand [J]. 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基于检索式1,2

, figureFileSmall=MJUKTJuNRvLkQZV8UlesfQ==, figureFileBig=gEhIqAkYgwfQ263JBCYBLQ==, tableContent=null), ArticleFig(id=1241408722820452798, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=EN, label=Fig.2, caption=Visualization of keywords of domestic and foreign publications, figureFileSmall=MDkkZWx8GUTYsiRQ0seicQ==, figureFileBig=ItDJfjtnFvuPVf4ZgmOdBg==, tableContent=null), ArticleFig(id=1241408722912727500, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=CN, label=图2, caption=国内外出版物关键词可视化., figureFileSmall=MDkkZWx8GUTYsiRQ0seicQ==, figureFileBig=ItDJfjtnFvuPVf4ZgmOdBg==, tableContent=null), ArticleFig(id=1241408723042750938, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=EN, label=Table 1, caption=

Summary of the review articles on hydropower carbon footprint

, figureFileSmall=null, figureFileBig=null, tableContent=
GHG主要影响因素主要内容存在问题参考文献
水电建设、蓄水区植被淹没、备用电力系统、总静头(进水口与涡轮之间的距离)高度、电力生产能力和现有水利基础设施的利用使用分类指数对水电系统进行统计评估,水电系统的GHG排放受建设活动、淹没植被和备用电力系统等因素的影响,结果将有助于制定减少GHG排放的能源政策水电生命周期系统边界划分不一致;缺乏统一的功能单位;GHG排放研究方法不统一;水电碳排放差异受地域性影响较大[5]
水库特性(库容量、使用年限、位置等)、建设阶段、运行和维护阶段、退役阶段(大坝拆除和废弃回收)研究水电生命周期内的GHG排放,重点分析不同类型水电(如水库型和径流式水电)的排放差异数据不一致、缺乏标准化;LCA不确定性分析不足;区域化分析缺乏[8]
水温、溶解氧含量、有机碳输入、水温的热分层、水库使用年限、平均深度、季节变化探讨了水电生命周期内GHG排放的多样性和影响因素.指出蓄水水库相关的GHG排放是主要的驱动因素,而径流水电项目的排放相对较低数据有限且不一致;LCA模型和方法不一致;局限于某些地理区域,如印度的热带和亚热带[6]
蓄水区生物质分解、运营排放、基础设施建设、拆除和废弃回收对比水电和其他发电技术在GHG排放方面的差异,从生命周期角度分析水电的建设和运营过程中产生的排放.水电的碳排放量低于火电,但由于建设过程中生物质分解和基础设施建设等原因,水电仍会产生显著的GHG排放碳排放核算方法缺乏标准化;模型不确定性较高;数据不足[7]
), ArticleFig(id=1241408723231494639, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=CN, label=表1, caption=

水电碳足迹中英文综述文章概要

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GHG主要影响因素主要内容存在问题参考文献
水电建设、蓄水区植被淹没、备用电力系统、总静头(进水口与涡轮之间的距离)高度、电力生产能力和现有水利基础设施的利用使用分类指数对水电系统进行统计评估,水电系统的GHG排放受建设活动、淹没植被和备用电力系统等因素的影响,结果将有助于制定减少GHG排放的能源政策水电生命周期系统边界划分不一致;缺乏统一的功能单位;GHG排放研究方法不统一;水电碳排放差异受地域性影响较大[5]
水库特性(库容量、使用年限、位置等)、建设阶段、运行和维护阶段、退役阶段(大坝拆除和废弃回收)研究水电生命周期内的GHG排放,重点分析不同类型水电(如水库型和径流式水电)的排放差异数据不一致、缺乏标准化;LCA不确定性分析不足;区域化分析缺乏[8]
水温、溶解氧含量、有机碳输入、水温的热分层、水库使用年限、平均深度、季节变化探讨了水电生命周期内GHG排放的多样性和影响因素.指出蓄水水库相关的GHG排放是主要的驱动因素,而径流水电项目的排放相对较低数据有限且不一致;LCA模型和方法不一致;局限于某些地理区域,如印度的热带和亚热带[6]
蓄水区生物质分解、运营排放、基础设施建设、拆除和废弃回收对比水电和其他发电技术在GHG排放方面的差异,从生命周期角度分析水电的建设和运营过程中产生的排放.水电的碳排放量低于火电,但由于建设过程中生物质分解和基础设施建设等原因,水电仍会产生显著的GHG排放碳排放核算方法缺乏标准化;模型不确定性较高;数据不足[7]
), ArticleFig(id=1241408723340546561, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=EN, label=Table 2, caption=

Global hydropower carbon footprint cases based on LCA method

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序号水电设施名称区域气候水电设施类型装机容量水电设施等级发电量/面积/总发电量方法单位发电碳足迹寿命周期碳排放参考文献
1溪洛渡水电站四川省、云南省交界中国西南部亚热带季风性湿润气候双曲拱坝13860MW大(1)型水电站575.5亿kW⋅h/a133.65km²LCA3.83kgCO2eq/(MW•h)生命周期碳排放量为1.10×1010kg[36]
2庄河抽水蓄能电站辽宁省,中国东北部暖温带季风气候抽水蓄能电站1000MW大(2)型水电站12亿kW·h/a35.4万m2(上水库)143.97万m2(下水库)EIO-LCA、PA-LCA43.46gCO2eq/(kW•h)2.09×106tCO2eq[32]
3隔河岩水电站湖北省中国中部亚热带季风气候蓄水式水电站121.2万kW大(1)型水电站30.4亿kW·h/a72km2EIO-LCA、PA-LCA33.22gCO2eq/(kW•h)1.01×107tCO2eq[37]
4金沙江水电基地金沙江中游前段:乌东德水电站亚热带季风性湿润气候梯级水电站10200MW大(1)型水电站38.93TW·h/a127.1km²EIO-LCA、LCA7.22gCO2eq/(kW•h)2.81×107tCO2eq[15]
金沙江中游后段:白鹤滩水电站16000MW62.52TW·h/a216.49km²9.14gCO2eq/(kW•h)5.72×107tCO2eq
金沙江下游前段:溪洛渡水电站12600MW57.12TW·h ~64.06TW·h/a133.65km²4.39gCO2eq/(kW•h)2.51×107tCO2eq
金沙江下游后段:向家坝水电站6400MW30.88TW·h /a95.6km²6.32gCO2eq/(kW•h)1.94×107tCO2eq
5通城县外环大桥拦河闸枢纽水电站湖北省中国中部亚热带季风气候河床式水电站900kW小(2)型水电站374.5万kW·h/a703km2LCA251.35gCO2eq/(kW·h)1.88×104tCO2eq[30]
6可渡河阿都水电站贵州省中国西南部亚热带温湿季风气候水库型水电站60MW中型水电站2.72亿kW·h/a66.8万m2EIO-LCA13.05gCO2eq/(kW·h)1.77×105tCO2eq[38]
7犬木塘水利工程湖南省中国南部亚热带季风气候蓄水式水电站34MW小(1)型水电站1.15亿kW·h/a(暂无水库水域面积)EIO-LCA、PA-LCA12.80gCO2eq/(kW·h)4.78×105tCO2eq[18]
8伊泰普水电站巴西西南部与巴拉圭临近处亚热带气候蓄水式水电站12.6GW大(1)型水电站3.26E+11MJ(2007a)LCI1.56kgCO2/(MW·h)9.64×104tCO2/a[39]
9某土耳其河流蓄能式水力发电厂吉雷松省土耳其北部地中海气候河流蓄能式水力发电厂4MW小(2)型水电站7.43GW·h/a49.6km2LCI30.6kgCO2eq/(MW·h)[40]
10马扎尔-杜达斯水电项目厄瓜多尔中南部热带气候径流式水电站21MW小(1)型水电站125GW·h/aLCI2.6kgCO2eq/(MW·h)[41]
11巴巴水电站厄瓜多尔中西部沿海地区多用途水坝42MW小(1)型水电站161GW·h547kgCO2eq/(MW·h)8.8×106tCO2eq
12耶涯大坝彬乌伦缅甸中部790MW大(2)型水电站3550GW·h/a59.0km216.62kgCO2eq/(MW·h)5.9×1010kgCO2eq
13瑞丽江一级水电站木姐县缅甸东北600MW大(2)型水电站4022GW·h/a1.1km213.43kgCO2eq/(MW·h)5.41×1010kgCO2eq
14下邦朗大坝彬马那镇缅甸中南部热带季风气候.径流式水电站280MW中型水电站911GW·h/a17km2LCI8.14kgCO2eq/(MW·h)7.42×109kgCO2eq[35]
15达平河1水坝八莫市缅甸北部19MW小(1)型水电站1065GW·h/a0.4km27.31kgCO2eq/(MW·h)7.79×109kgCO2eq
16塔耶卡特2水电站东吁缅甸南部120MW中型水电站604GW·h/a13.8km28.19kgCO2eq/(MW·h)4.95×109kgCO2eq
17峡江水电站江西省吉安市峡江县巴邱镇中国东南部亚热带季风气候综合性水利枢纽工程360MW大(2)型水电站11.4亿kW·h/a119km2LCA32.63gCO2eq/(kW·h)3.72 × 106tCO2eq[31]
18库鲁阿-乌纳水电站圣塔伦市西南70公里巴西北部赤道(热带)雨林气候30.3MW小(1)型水电站8年内18MW,32年内28MW,60年内39MW102km2LCI、LCIA5.46kgCO2eq/(MW·h)[42]
19加拿大安大略省的水电站安大略省加拿大东部亚寒带气候LCA15.2gCO2eq/(kW·h)[17]
20糯扎渡水电站云南省南部澜沧江下游,向家坝之后中国西南部低热河谷地区,部分属热带气候心墙土石坝混凝土重力坝5850MW大(1)型水电站239.1×108kW·h/aEIO-LCA、PA-LCA8.36gCO2eq/(kW·h)8.8×106tCO2eq[43]
11.11gCO2eq/(kW·h)1.17×107tCO2eq
21长江上游34座水电站四川省中国西南部亚热带气候79GWTES-LCA28.76gCO2eq/(kW·h)(LHP);9.82gCO2eq/(kW·h)(SHP)[33]
22直孔水电站西藏自治区拉萨河中下游中国西南部温带半干旱季风气候区100MW中型水电4.07×108kW·h/aEIO-LCA195gCO2eq/(kW·h)3.97×1012gCO2eq[44]
23三峡大坝长江中国西南部亚热带季风性湿润气候22500MW大(1)型水电站EIO-LCA17.8gCO2eq/(kW·h)[16]
向家坝水电站溪洛渡水电站金沙江下游河段上中国西南部金沙江中国西南部6400MW大(1)型水电站
12600MW大(1)型水电站
白鹤滩水电站金沙江中国西南部16000MW大(1)型水电站7.4gCO2eq/(kW·h)
乌东德水电项目云南省金沙江中国西南部10200MW大(1)型水电站9.3gCO2eq/(kW·h)
24A公司的水电站利马市东北秘鲁西侧沙漠草原气候径流式水电站迷你径流式水电站172MW中型水电站小(1)型水电站837GW·h/aLCA2.06gCO2eq/(kW·h)8.46×104tCO2eq/a[45]
B公司的一号水电利马市东南秘鲁西侧220MW1100GW·h/a2.42gCO2eq/(kW·h)1.26×105tCO2eq/a
B公司的二号水电18.4MW147GW·h/a2.33gCO2eq/(kW·h)1.72×104tCO2eq/a
25巴西某水电站巴西热带气候.87789MW517TW·h,2021年LCA0.0509kgCO2eq/(kW·h)2.1×1010kgCO2eq/2021年[46]
26美国某抽水储能水电站美国抽水储能水电站31~2100MWLCA-EIO5.6gCO2eq/(kW·h)[47]
27图库鲁伊水电站巴西热带气候.4000MW大(1)型水电站18TWh/aLCA237gCO2eq/(kW·h)4.26×106tCO2eq[48]
28克莱德达曼德水电站.新西兰北部为亚热带气候;南部为温带气候.432MW大(2)型水电站186 ×109kW/100aLCA4.6gCO2eq/(kW·h)8.61 × 108kgCO2[49]
29威尔德格-布鲁格水电站瑞士海洋性气候径流式水电站50MW小(1)型水电站300GW·h/aLCA3.1gCO2eq/(kW·h)[50]
30恩布雷茨瀑布水电站挪威温带海洋性气候.径流式水电站285.736.000kW·h/a2.19gCO2eq/(kW·h)[51]
31蓄水式水电站径流式水电站蓄水式水电站径流式水电站1,000MW100MW大(2)型水电站中型水电站15gCO2eq/(kW·h)5.0gCO2eq/(kW·h)[52]
32印度尼西亚某微型水电站印度尼西亚热带气候.径流式水电站9MW小(2)型水电站3312GW·h/50a180000m2LCA1.2kgCO2eq/(MW·h)[53]
33比利时某抽水储能电站比利时温带海洋性气候.非高山地区抽水蓄能电站190GW·h/aLCA5.46gCO2eq/(kW·h)[54]
34威尔士某微型水电站英国温带海洋性气候.70kW85kW90kW100kW小(2)型水电站LCA7.19±3.09gCO2eq/(kW·h)[55]
35佩尼·塞芬水处理工程;瓦特里水库及水处理厂;斯特拉塔弗洛里达水处理厂英国温带海洋性气候.15kW90kW140kW小(3)型水电站LCA2.14gCO2eq/(kW·h)
4.36gCO2eq/(kW·h)2.78g
CO2eq/(kW·h)
[56]
), ArticleFig(id=1241408723499930127, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408713899168674, language=CN, label=表2, caption=

基于LCA方法的全球范围内水电碳足迹案例

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序号水电设施名称区域气候水电设施类型装机容量水电设施等级发电量/面积/总发电量方法单位发电碳足迹寿命周期碳排放参考文献
1溪洛渡水电站四川省、云南省交界中国西南部亚热带季风性湿润气候双曲拱坝13860MW大(1)型水电站575.5亿kW⋅h/a133.65km²LCA3.83kgCO2eq/(MW•h)生命周期碳排放量为1.10×1010kg[36]
2庄河抽水蓄能电站辽宁省,中国东北部暖温带季风气候抽水蓄能电站1000MW大(2)型水电站12亿kW·h/a35.4万m2(上水库)143.97万m2(下水库)EIO-LCA、PA-LCA43.46gCO2eq/(kW•h)2.09×106tCO2eq[32]
3隔河岩水电站湖北省中国中部亚热带季风气候蓄水式水电站121.2万kW大(1)型水电站30.4亿kW·h/a72km2EIO-LCA、PA-LCA33.22gCO2eq/(kW•h)1.01×107tCO2eq[37]
4金沙江水电基地金沙江中游前段:乌东德水电站亚热带季风性湿润气候梯级水电站10200MW大(1)型水电站38.93TW·h/a127.1km²EIO-LCA、LCA7.22gCO2eq/(kW•h)2.81×107tCO2eq[15]
金沙江中游后段:白鹤滩水电站16000MW62.52TW·h/a216.49km²9.14gCO2eq/(kW•h)5.72×107tCO2eq
金沙江下游前段:溪洛渡水电站12600MW57.12TW·h ~64.06TW·h/a133.65km²4.39gCO2eq/(kW•h)2.51×107tCO2eq
金沙江下游后段:向家坝水电站6400MW30.88TW·h /a95.6km²6.32gCO2eq/(kW•h)1.94×107tCO2eq
5通城县外环大桥拦河闸枢纽水电站湖北省中国中部亚热带季风气候河床式水电站900kW小(2)型水电站374.5万kW·h/a703km2LCA251.35gCO2eq/(kW·h)1.88×104tCO2eq[30]
6可渡河阿都水电站贵州省中国西南部亚热带温湿季风气候水库型水电站60MW中型水电站2.72亿kW·h/a66.8万m2EIO-LCA13.05gCO2eq/(kW·h)1.77×105tCO2eq[38]
7犬木塘水利工程湖南省中国南部亚热带季风气候蓄水式水电站34MW小(1)型水电站1.15亿kW·h/a(暂无水库水域面积)EIO-LCA、PA-LCA12.80gCO2eq/(kW·h)4.78×105tCO2eq[18]
8伊泰普水电站巴西西南部与巴拉圭临近处亚热带气候蓄水式水电站12.6GW大(1)型水电站3.26E+11MJ(2007a)LCI1.56kgCO2/(MW·h)9.64×104tCO2/a[39]
9某土耳其河流蓄能式水力发电厂吉雷松省土耳其北部地中海气候河流蓄能式水力发电厂4MW小(2)型水电站7.43GW·h/a49.6km2LCI30.6kgCO2eq/(MW·h)[40]
10马扎尔-杜达斯水电项目厄瓜多尔中南部热带气候径流式水电站21MW小(1)型水电站125GW·h/aLCI2.6kgCO2eq/(MW·h)[41]
11巴巴水电站厄瓜多尔中西部沿海地区多用途水坝42MW小(1)型水电站161GW·h547kgCO2eq/(MW·h)8.8×106tCO2eq
12耶涯大坝彬乌伦缅甸中部790MW大(2)型水电站3550GW·h/a59.0km216.62kgCO2eq/(MW·h)5.9×1010kgCO2eq
13瑞丽江一级水电站木姐县缅甸东北600MW大(2)型水电站4022GW·h/a1.1km213.43kgCO2eq/(MW·h)5.41×1010kgCO2eq
14下邦朗大坝彬马那镇缅甸中南部热带季风气候.径流式水电站280MW中型水电站911GW·h/a17km2LCI8.14kgCO2eq/(MW·h)7.42×109kgCO2eq[35]
15达平河1水坝八莫市缅甸北部19MW小(1)型水电站1065GW·h/a0.4km27.31kgCO2eq/(MW·h)7.79×109kgCO2eq
16塔耶卡特2水电站东吁缅甸南部120MW中型水电站604GW·h/a13.8km28.19kgCO2eq/(MW·h)4.95×109kgCO2eq
17峡江水电站江西省吉安市峡江县巴邱镇中国东南部亚热带季风气候综合性水利枢纽工程360MW大(2)型水电站11.4亿kW·h/a119km2LCA32.63gCO2eq/(kW·h)3.72 × 106tCO2eq[31]
18库鲁阿-乌纳水电站圣塔伦市西南70公里巴西北部赤道(热带)雨林气候30.3MW小(1)型水电站8年内18MW,32年内28MW,60年内39MW102km2LCI、LCIA5.46kgCO2eq/(MW·h)[42]
19加拿大安大略省的水电站安大略省加拿大东部亚寒带气候LCA15.2gCO2eq/(kW·h)[17]
20糯扎渡水电站云南省南部澜沧江下游,向家坝之后中国西南部低热河谷地区,部分属热带气候心墙土石坝混凝土重力坝5850MW大(1)型水电站239.1×108kW·h/aEIO-LCA、PA-LCA8.36gCO2eq/(kW·h)8.8×106tCO2eq[43]
11.11gCO2eq/(kW·h)1.17×107tCO2eq
21长江上游34座水电站四川省中国西南部亚热带气候79GWTES-LCA28.76gCO2eq/(kW·h)(LHP);9.82gCO2eq/(kW·h)(SHP)[33]
22直孔水电站西藏自治区拉萨河中下游中国西南部温带半干旱季风气候区100MW中型水电4.07×108kW·h/aEIO-LCA195gCO2eq/(kW·h)3.97×1012gCO2eq[44]
23三峡大坝长江中国西南部亚热带季风性湿润气候22500MW大(1)型水电站EIO-LCA17.8gCO2eq/(kW·h)[16]
向家坝水电站溪洛渡水电站金沙江下游河段上中国西南部金沙江中国西南部6400MW大(1)型水电站
12600MW大(1)型水电站
白鹤滩水电站金沙江中国西南部16000MW大(1)型水电站7.4gCO2eq/(kW·h)
乌东德水电项目云南省金沙江中国西南部10200MW大(1)型水电站9.3gCO2eq/(kW·h)
24A公司的水电站利马市东北秘鲁西侧沙漠草原气候径流式水电站迷你径流式水电站172MW中型水电站小(1)型水电站837GW·h/aLCA2.06gCO2eq/(kW·h)8.46×104tCO2eq/a[45]
B公司的一号水电利马市东南秘鲁西侧220MW1100GW·h/a2.42gCO2eq/(kW·h)1.26×105tCO2eq/a
B公司的二号水电18.4MW147GW·h/a2.33gCO2eq/(kW·h)1.72×104tCO2eq/a
25巴西某水电站巴西热带气候.87789MW517TW·h,2021年LCA0.0509kgCO2eq/(kW·h)2.1×1010kgCO2eq/2021年[46]
26美国某抽水储能水电站美国抽水储能水电站31~2100MWLCA-EIO5.6gCO2eq/(kW·h)[47]
27图库鲁伊水电站巴西热带气候.4000MW大(1)型水电站18TWh/aLCA237gCO2eq/(kW·h)4.26×106tCO2eq[48]
28克莱德达曼德水电站.新西兰北部为亚热带气候;南部为温带气候.432MW大(2)型水电站186 ×109kW/100aLCA4.6gCO2eq/(kW·h)8.61 × 108kgCO2[49]
29威尔德格-布鲁格水电站瑞士海洋性气候径流式水电站50MW小(1)型水电站300GW·h/aLCA3.1gCO2eq/(kW·h)[50]
30恩布雷茨瀑布水电站挪威温带海洋性气候.径流式水电站285.736.000kW·h/a2.19gCO2eq/(kW·h)[51]
31蓄水式水电站径流式水电站蓄水式水电站径流式水电站1,000MW100MW大(2)型水电站中型水电站15gCO2eq/(kW·h)5.0gCO2eq/(kW·h)[52]
32印度尼西亚某微型水电站印度尼西亚热带气候.径流式水电站9MW小(2)型水电站3312GW·h/50a180000m2LCA1.2kgCO2eq/(MW·h)[53]
33比利时某抽水储能电站比利时温带海洋性气候.非高山地区抽水蓄能电站190GW·h/aLCA5.46gCO2eq/(kW·h)[54]
34威尔士某微型水电站英国温带海洋性气候.70kW85kW90kW100kW小(2)型水电站LCA7.19±3.09gCO2eq/(kW·h)[55]
35佩尼·塞芬水处理工程;瓦特里水库及水处理厂;斯特拉塔弗洛里达水处理厂英国温带海洋性气候.15kW90kW140kW小(3)型水电站LCA2.14gCO2eq/(kW·h)
4.36gCO2eq/(kW·h)2.78g
CO2eq/(kW·h)
[56]
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水电碳足迹关键影响因素及区域化研究趋势
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李朋 1 , 白孝轩 1 , 丁宁 2 , 赵思琪 2 , 李超 1 , 周卫青 1 , 张高翔 2, *
中国环境科学 | 碳排放控制 2025,45(4): 2251-2263
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中国环境科学 | 碳排放控制 2025, 45(4): 2251-2263
水电碳足迹关键影响因素及区域化研究趋势
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李朋1 , 白孝轩1, 丁宁2, 赵思琪2, 李超1, 周卫青1, 张高翔2, *
作者信息
  • 1.国网冀北电力有限公司电力科学研究院,北京 100045
  • 2.中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085
  • 李朋(1986-),男,湖北仙桃人,高级工程师,博士.主要从事能源与环保领域、绿色供应链相关研究.发表论文20余篇..

通讯作者:

* 责任作者,硕士,科研助理,
Key factors influencing hydropower carbon footprint assessment and geo-regional research trends
Peng LI1 , Xiao-xuan BAI1, Ning DING2, Si-qi ZHAO2, Chao LI1, Wei-qing ZHOU1, Gao-xiang ZHANG2, *
Affiliations
  • 1.State Grid Jibei Electric Power Co., Ltd. Electric Power Research Institute, Beijing 100045, China
  • 2.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
出版时间: 2025-04-20
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面向水电低碳发展问题,对水电碳足迹关键影响因素及水电碳足迹区域化差异进行综述研究.结果表明,全球范围内对现有水电碳足迹研究的关注度不断增高.通过案例研究发现,水电碳足迹主要由建设阶段的建材制造和工程施工,以及运行维护阶段的设备运行耗能产生.总结了影响水电碳排放的关键因素:水电类型、装机量、蓄水量、蓄水区面积和生命周期阶段等,并从地理空间的视角对水电碳排放进行了区域化研究,指出因地理位置不同导致的气候、降水量、生态环境等差异对水电碳足迹的影响.

水电  /  碳足迹  /  生命周期评估  /  碳排放  /  区域化分析

This research addressed the issue of low-carbon development in hydropower, provided a review of the key factors influencing the carbon footprint of hydropower and the regional variations in these footprints. The findings of this research indicated an increasing global focus on research into the carbon footprint of hydropower. Case studies revealed that the primary contributors to the hydropower carbon footprint were the manufacture of construction materials and engineering activities during the construction phase, as well as energy consumption by equipment during the operation and maintenance phase. This research identified key factors affecting hydropower carbon emissions, including the type of hydropower, installed capacity, water storage volume, reservoir area, and life cycle stages. Furthermore, from a geographical perspective, it explored the regional variation in hydropower carbon emissions, highlighting the impact of differences in climate, precipitation, and ecological environment due to geographical location on the hydropower carbon footprint.

hydropower  /  carbon footprint  /  life cycle assessment  /  carbon emissions  /  regionalization analysis
李朋, 白孝轩, 丁宁, 赵思琪, 李超, 周卫青, 张高翔. 水电碳足迹关键影响因素及区域化研究趋势. 中国环境科学, 2025 , 45 (4) : 2251 -2263 .
Peng LI, Xiao-xuan BAI, Ning DING, Si-qi ZHAO, Chao LI, Wei-qing ZHOU, Gao-xiang ZHANG. Key factors influencing hydropower carbon footprint assessment and geo-regional research trends[J]. China Environmental Science, 2025 , 45 (4) : 2251 -2263 .
水电是被广泛认可的清洁能源之一,中国拥有全球最大的水电装机和生产规模[1].国际能源署发布《水力发电市场报告》,预测全球水力发电量将在2021~2030年增长17%,并主要由中国、印度、土耳其与埃塞俄比亚带动[2].随着中国水电开发加速,装机容量从1978年的1.7亿kW增长至2020年的3.7亿kW[3].《2030年前碳达峰行动方案》中指出,要因地制宜开发水电;积极推进水电建设,推动金沙江上游、澜沧江上游、黄河上游等已纳入规划,符合生态保护要求的水电项目开工建设,并推动小水电绿色发展[4].水电是中国“碳达峰十大行动”中能源绿色低碳转型行动所重点倡议的清洁能源类型.
作为可持续性能源,水电碳足迹计算和水电减排对于减缓气候变化至关重要.2024年6月,中国提出产品碳足迹管理体系建设方案.水电碳足迹计算能够从全生命周期评估水电碳排放,是水电绿色低碳转型的基础. Kadiyala等[5]指出水电生命周期温室气体(GHG)排放量与水电装机容量和类型有关,即同类型水电中,大型(装机容量大)水电生命周期GHG排放量大于小型(装机容量小)水电(SHP);同体积情况下,蓄水水电生命周期GHG排放量大于径流式水电.然而,Kumar等人[6]认为小型水电所造成的单位碳排放和环境影响远远大于大型水电.还有综述研究从核算方法、系统边界、数据局限性等方面提出问题[7-8],但对影响水电碳足迹的关键影响因素尚缺乏系统梳理.
此外,由于水电碳足迹计算使用了不同的生命周期评估(life cycle assessment,LCA)方法、计算缺乏统一标准,导致计算结果存在差异.根据国际水电协会披露的结果,水电生命周期温室气体排放的中值为23gCO2eq/(kW·h),与IPCC的研究结果一致[9].有研究估计,水电碳足迹的全球平均排放量为85gCO2eq/(kW·h)和3gCH4eq/(kW·h),而非洲北部法属圭亚那地区的热带水电碳排放量甚至达到1550gCO2eq/(kW·h),远高于燃煤发电[10].因此,对于水电是否为清洁能源存在争议,需要进一步构建碳足迹核算方法和关键影响因素解析,为水电降碳提供支撑.
综上所述,当前水电开发潜力较大,符合减碳和发展清洁能源的政策目标,但在碳足迹核算方面仍存在优化空间.本研究基于Web of Science (WOS )和中国知网(CNKI)两个国内外主流期刊数据库,分别对全球和国内水电碳足迹和水电LCA相关出版物进行数据收集和梳理,利用CiteSpace进行可视化分析,探索该领域当下研究热点、高频关键词以及主要研究机构.本研究通过对全球范围内多个水电碳足迹研究案例进行气候、水电类型、装机容量、碳足迹计算方法等多角度分析,将详细讨论不同因素对水电碳足迹的影响,探索水电碳足迹区域性差异及研究趋势,弥补现有研究对水电碳排放区域化分析不足的问题,旨在全面解析水电碳排放影响因素,为后续研究提供理论依据.
CiteSpace主要被运用于分析和显示一个学科或者某一研究方向某一时间段的学术成果的发展趋势与动向,形成若干研究前沿领域的发展历程[11],可以实现对大量的文献进行快速的关键词、合作机构、作者、研究热点等信息进行可视化成图并进一步进行分析讨论[12].本文的文献计量将基于CNKI和WOS为数据库,使用CiteSpace对水电的碳足迹主题的文献进行信息可视化处理.
设定检索式1为“SU=“水电” AND TKA=“碳足迹” OR “SU=“水电”AND TKA=“生命周期””,在CNKI中文数据库中进行专业检索,时间范围为2014年至2023年.
设置检索式2为“(TS=(carbon emission) AND(TS=(hydropower) OR TS=(hydroelectricity))) AND(AB=(life cycle assessment) OR AB=(carbon emission))”,时间范围为1991年至2023年,出版物类型为Web of Science核心集.
将CNKI和WOS的结果分别导出为“refworks”和“纯文本文件”格式,插入CiteSpace进行可视化分析.
当前,水电碳足迹研究数量较多,但仍存在生命周期系统边界划分不一致、计算方法不统一和数据获取有局限性等问题(表1).因此,需对现有水电碳足迹研究案例进行计量分析,以确定未来研究方向.如图1所示,基于检索式1内容的出版物数量为303篇,其中学术期刊和学位论文共计195篇.由于其他类型文章包含新闻报道、政府政策宣传等,缺乏学术性,因此只使用学术期刊和学位论文作为参考.根据图1结果可知,从2014至2023年,国内“水电”和“碳足迹”以及“生命周期”相关的出版物数量呈先上升后下降的趋势.2014年全年中文相关出版物共计2篇,2017年年出版物数量达到最高峰,共计38篇.而2018年和2019年,相关出版物年度数量出现下滑趋势,分别为19篇和17篇.2020年全年,该主题相关出版物数量再次出现上升趋势,共计27篇.2021年下滑至20篇,2022年小幅增长至25篇.而2023年全年相关文章数量仅有12篇.由此可见,该领域的中文研究数量有先急速加剧到放缓平稳的趋势.
在WOS英文数据库中进行专业检索,基于检索式2的出版物共有555篇.由图1可知,在2000年以前,与检索式2相关的年度英文出版物数量属于相对稳定的趋势.而自2001年开始,全球范围内相关课题的出版物数量开始增加.2001年全年相关英文出版物共计1篇,而到2020年则增长至51篇.由于《巴黎协定》的促进作用,以及各个主要国家相关碳中和、净零碳排放政策的落实,2020年以后相关领域出版物数量年度增长速度再度提升,截止2023年,当年英文出版物共计99篇.
根据图2(a)可知,目前国内出版物高频关键词为“生命周期”、“碳足迹”、“水电工程”、“小水电”、“成本控制”、“环境管理”等.其主要原因是,水电的碳足迹和LCA是对已有水电进行生命周期碳排放计算和数学模型建设,并对水电整个运行周期进行碳排放因素评估和管理优化.从生命周期视角来看,“成本控制”与水电建设有关,“绿色管理”与水电运营有关,因此可知水电碳排放与水电建设和水电运营密切相关.除此之外,一些研究中提及了关键词“小水电”,因此,后续研究中应聚焦水电体积和水电碳排放之间的关系研究.
图2(b)所示,国际出版物关键词主要集中在“life cycle assessment”、“hydropower reservoirs”、“greenhouse gas emission”、“storage”等方面.由此表明,水电碳足迹相关的英文出版物中,水电水库、水电容量等关键词出现频率较高,可作为后续研究的重点.虽然发达国家对于水电的建设和使用较早,但也有学者质疑,在陈旧的技术和运行管理体系下,水电虽作为清洁型能源,其运营过程和生命周期并没有做到净零碳排或是低碳[13].因此,在全球2050净零碳排放的政策背景下,各国科学家亦开始根据不同的水电地理位置以及运行条件,结合碳足迹追踪和LCA等方法对水电进行进一步的绿色设计和规划[14].
目前,水电碳足迹计算方法主要包括LCA、混合生命周期评估方法(投入产出与LCA结合,EIO-LCA)和生态足迹分析法.对于同一水电站采用不同计算方法,所得碳足迹结果也不相同.例如杜海龙[15]等使用EIO-LCA方法,对位于金沙江的白鹤滩水电单位发电碳足迹计算结果为9.14gCO2eq/(kW·h),而Li等[16]利用LCA对该水电的计算结果为7.4gCO2eq/(kW·h).因此,目前水电碳足迹不同核算方法存在计算结果差异较大的问题.
水电全生命周期阶段一般包括原材料开采、材料制造、建设安装、运行维护、拆除和回收阶段[17].黄跃群等[18]利用LCA对中国湖南省犬木塘水电站进行研究表明,材料制造阶段是犬木塘水电寿命周期主要贡献者,排放量为229777.3tCO2e,主要原因是钢筋、水泥材料的生产和电、柴油等能源的消耗.Zhang等[19]通过LCA方法指出,中国大陆地区水电的建筑材料成本占建设阶段总成本的38%,远低于机械设备成本(53%);然而,建筑材料制造消耗的能源占比高达69%.另有学者对中国境内水电评价显示,水电运行和维护阶段的碳排放最大,占比87.36%,其次是建设阶段,占比8.35%[20].因此,对于水电的低碳优化需关注降低建造阶段碳排放、优化水电站结构设计、选取绿色建材和加强运行维护阶段的管理[19,21].
然而,使用LCA方法进行水电碳排放评估具有局限性,缺少对景观变化、土地和水生生态等环境因素的考量.同时,缺少对经济和社会因素的掌控,如旅游业因景观淹没而产生的潜在损失或收益,人口迁移和定居指标等[20].因此,将不同维度影响因素纳入水电评价研究,对水电LCA方法进行优化,提高水电生命周期碳管理,具有重要的研究价值.
利用LCA方法核算水电碳足迹存在系统边界不统一、数据获取困难等问题,同时还受到地理、环境因素和水电运行差异的影响.EIO-LCA方法基于经济数据矩阵,利用投入产出模型,反映生命周期各个阶段的生产活动与其环境影响关联.通过添加经济参数修正,能够有效减少传统LCA中常见的截断误差[22].在对印度多座径流式SHP的碳排放研究中,通过EIO-LCA方法计算碳足迹范围为35.29~74.88gCO2eq/(kW·h),而传统LCA方法的计算结果可能由于数据质量和系统边界的限制而产生误差[23].另有学者对印度三种不同类型的SHP:径流式(run-over-the-river)、渠道式(Canal-Based)和坝趾式(Dam-Toe SHP),使用EIO-LCA进行碳足迹计算得出,径流式SHP单位发电碳足迹为35.29~74.88gCO2eq/(kW·h);渠道式SHP为25.14~45.73gCO2eq/(kW·h);坝趾式SHP为50.39~58.69gCO2eq/(kW·h).EIO-LCA方法在水电碳足迹计算中的准确性,通过与印度钢铁和铝材生产的能耗数据进行比较,发现误差仅在10%以内[24].
水库水坝建设需要庞大的占地面积,从而导致水电站建设过程中会征用并淹没大量土地、耕地、动物栖息地或森林等.在水库淹没土地后,原有生物质分解导致蓄水区域GHG排放,并对生态环境造成破坏[10,25].因此,在对水电进行碳排放核算时,忽略人为因素对区域环境和生态系统服务功能的影响是不全面的[26].
Lu等[27]对水电开发过程进行了生态足迹和碳减排之间的关联分析.研究表明,水电开发过程中化石能源的消耗呈逐年上升的趋势,由1949年消耗1700t标准煤增长至2010年884000t标准煤,带来碳排放的相应上升;1949年淹没土地的生态足迹为2600hm2,2010年增加至142万hm2.由此可见,生态足迹分析可以从自然资源消耗的角度对不同水电项目的可持续性做出评估.同时,利用生态足迹分析法计算碳排放可以从更宏观的角度判断水电建设带来的物质和能源消耗,便于掌握碳排放的总体趋势[28].
本节将对碳足迹计算结果以及影响因素进行分析,以期得到影响水电碳足迹的关键要素,为未来水电低碳优化提供理论基础.
表2总结了全球范围内35个水电碳足迹研究案例,研究表明,水电单位碳足迹范围为2.06~251.35gCO2eq/(kW·h),主要产生碳排放的阶段包括水库建设(建设工程和材料制造)和运行维护(水电力发电机等机械耗能和蓄水区碳释放)阶段[29].此外,不同水电案例在不同生命周期阶段碳足迹贡献存在差异,除计算方法不同外,导致水电碳排放区域间差异的影响因素包括地理位置、地理环境、水库淹没面积等.
表2中的案例可知,在水电生命周期的各个阶段中,建设阶段和运行维护阶段的碳排放占比最大.湖北省某SHP的寿命周期碳排放量为1.88×104tCO2eq,建设阶段碳排放量占总量的84.8%,运行阶占比4.7%,报废拆除阶段占比10.5%.因此,该水电寿命周期碳排放主要由建设阶段产生[30];另有研究表明,位于江西的峡江水电寿命周期碳排放量为3.72×106tCO2eq,运行维护阶段碳排放量占其总排放量的70.49%,建设阶段的碳排放量占总体的27.42%[31];侯公羽等[32]的研究表明,辽宁省庄河抽水蓄能水电的寿命周期碳排放为2.09×106tCO2eq,运营阶段碳排放量占总比59%,建设阶段碳排放量占总比41%.由此可知,建设阶段和运行维护阶段在水电寿命周期碳排放中占比较大.
除此之外,水电建设和水电运行阶段的碳排放亦与水电规模密切相关.多数研究中,SHP在建设和运营阶段的碳足迹明显小于大型水电[33].SHP在建设运营阶段的碳排放范围在4.33~16.01gCO2eq/(kW·h)之间,平均值为8.36gCO2eq/(kW·h).根据上述案例可得,水电建设阶段的碳排放主要来自建设过程中水泥、混凝土等材料的生产和材料运输、工程修建所产生的废气;水电运行阶段的碳排放来源为水电维持自身设备运行和水库蓄水区碳排放等.
美国能源部水力发电技术办公室指出,在水电蓄水区域中因淹没地区的生物质水下分解产生CO2和CH4排放,从而改变了河流系统中碳的排放和储存方式[34].Aung等[35]的研究表明,缅甸的耶涯大坝和瑞丽江一级大坝在装机量、水电类型均为径流式水电以及自然环境相近的情况下,耶涯大坝的蓄水面积为59.0km2,大于瑞丽江大坝的蓄水面积为1.1km2.因此,耶涯大坝的单位发电碳足迹为16.62kgCO2eq/(MW·h),高于瑞丽江水电站单位发电碳足迹13.43kgCO2eq/(MW·h).由此可知,水库蓄水面积越大,所造成的蓄水区域碳排放越多.
Steinhurst等[7]的研究同样表明水电蓄水区域是水电碳排放的影响因素,地理位置差异会导致蓄水区的生物分解排放值不同.例如,在热带雨林地区的水电蓄水区,由于蓄水前原有树木密集,提供的碳截存较多;但在淹没后,树林碳截存功能被取缔,同时淹没区有机物生物质分解产生的碳排放量较大.因此,位于北美热带地区的水电水库的碳排放率高达1300~3000kgCO2eq/(MW·h).而位于非热带北部地区的水库蓄水区,由于原有树木密度较低,提供的碳截存较少,淹没后生物质分解产生的碳排放较少,因此,该地区水电碳排放率仅有0.5~152kgCO2eq/(MW·h).所以,水电的碳排放量与蓄水区面积有关.
水电碳足迹与水源的蓄水量关系密切,水电蓄水量规模直接影响其总发电量[58].以溪洛渡水电站为例,LCA研究所得单位发电碳足迹为3.83kgCO2eq/(MW·h)[36].杜海龙等[37]使用EIO-LCA和LCA方法也对该水电进行了计算,所得单位发电碳足迹为4.39gCO2eq/(kW·h).二者研究结果出现差异的主要原因:(1)方法论不同,LCA和EIO-LCA方法底层计算逻辑具有差异;(2)区域降水量差异,四川省2022年平均降水量较2017年减少96.65mm,占总比约10.27%[59-60].云南省2022年平均降水量较2017年减少178.6mm,占比约13.21%[61-62].因此,在年降水量减少的情况下,水电的单位发电碳足迹也随之减少.由此可知,水电蓄水量是水电碳排放影响因素之一,而当地的气候条件会对蓄水量产生直接影响.
2022年,云南省溪洛渡水电的装机容量为13860MW,较2017年的容量12600MW增加了1260MW.根据DL5180-2003水电枢纽工程等级划分及设计安全标准,装机量大于等于1200MW的水库均属于大(1)型水电[57].由此可知,在2017年到2022年之间,溪洛渡水电站的装机容量增长量相当于在原有基础上增加了一个大(1)型水电.装机量的增多在运行维护阶段会产生更多的碳排放[20],从而导致水电生命周期碳排放量增加.因此,2022年溪洛渡水电站总碳排放量为3.83×107tCO2eq,2017年的总碳排放量为2.51×107tCO2eq.Verán-Leigh等[45]对秘鲁两座装机量分别为172和220MW的中型水电和一座装机量为18.4MW小(1)型水电的碳排放进行对比分析.其水电单位发电量碳足迹分别为2.06,2.42和2.33gCO2eq/(kW·h).结果表明,在种类均为径流式水电和相同地理环境的情况下,水电规模越小,其单位发电碳足迹就越高.上述分析以不同地区的案例印证了Pascale等[63]的结论,即水电装机量(水电等级)是碳排放的影响因素之一.
此外,水电的碳足迹还和项目规模有关.Pascale等[63]以泰国农村地区为例,对比3kW水电、电网以及7kVA柴油发电机的全球变暖潜值(Global warming potential,GWP).研究结果表明,7kVA的柴油发电机的GWP为27,泰国国家电网的GWP为18.5,3kW水电的GWP为18.与大型水电相比,SHP通常为偏远或贫困地区居民提供电力,具有自身优势.例如,SHP具有可用资源丰富、易于安装等优势[64].Pang等[65]对中国SHP碳排放进行研究,结果表明水电运行阶段和建设阶段产生的GHG最大.因此,SHP的碳减排与水电装机量密切相关.
水电类型包括蓄水式水电和径流式水电等.结合加拿大安大略省的多个水电案例分析得知,在相似地理位置下,径流式水电规模较蓄水式水电占地面积偏小,装机量在10~52MW之间.蓄水式水电装机量在40~1499MW之间.规模较小的径流式水电的平均单位发电碳足迹为1.5tCO2eq/(GW·h),体积较大的蓄水式水电的平均单位发电碳足迹为22.5tCO2eq/(GW·h)[66].由此可知,在地理环境相似的情况下,径流式水电装机量较小,其对环境的影响和释放的GHG远小于体积较大的蓄水式水电.
不同类型的水电建造方式也是导致碳排放差异的因素.有学者对位于中国云南省南部澜沧江流域的糯扎渡水电系统中两种不同水电类型碳足迹进行对比分析.研究表明,在装机量同为5850MW时,土芯堆石坝(ECRD)的单位发电碳足迹为8.36gCO2eq/(kW·h),寿命周期总碳排放为8.8MtCO2eq;混凝土重力坝(CGD)的单位发电碳足迹为11.11gCO2eq/(kW·h),寿命周期碳排放为11.69Mt CO2eq.可知,CGD的碳排放大于ECRD.二者碳足迹研究中,最显著的差别是在材料生产阶段,ECRD系统对钢材、水泥和木材等高排放建筑材料的消耗较少,且材料与GCD相比多来自于本地,因此ECRD方案的二氧化碳排放量比GCD系统低46%[43].因此,不同类型水电建设材料的种类和来源是水电减碳的影响因素之一.
通过本文对水电碳足迹主题出版物的文献计量可知,目前对于水电碳足迹计算的研究关注度逐渐升高,相关出版物数量呈逐年上升的趋势.相关研究主要集中在水电工程、成本控制、环境管理和水电生命周期评估等方向,并且,现有出版物对于水电碳排放区域化差异的研究较为不足.
为了更好地研究水电的碳足迹影响因素,考虑到不同水电的地理环境以及人为原因所造成的差异,一些学者开展了水电碳排放区域差异研究.刘宇等[29]在研究中指出,中国水电碳排放存在区域差距较大的问题.中国平均水电碳排放为16.76g/(kW·h),9个省份比平均值低60%以上,6个省份比平均值低20%~60%,然而大于等于平均值±20%以上的仍有11个省市.其中,碳排放最大值为36.1g/(kW·h),最小值为2.5g/(kW·h).水电碳排放的区域化差异主要由该地区水资源多少以及气候环境导致.虽然水电数量和种类同样会起到影响作用,但从空间层面来看,并非主要原因.例如,在中国大陆地区,水电主要集中在以东南、中部和西南为主的水资源丰富、降水量充足的南方地带.因此,湖南、湖北、广西、云南等地的水电碳足迹较低.相反,干旱、少雨的新疆、西藏、辽宁、北京和河北等北方城市,水电碳足迹较高.
本文在对水电碳足迹范围及影响因素的分析中也多次提及水电碳足迹区域化差异的特点.首先,在生命周期阶段,如果水电的选址地与材料产地距离间隔较小,且交通便利,则在建设阶段的碳排放会因交通运输产生的碳排放减少而降低.其次,位于热带地区和生物多样性程度较高、生物分布密度较大地区的水电蓄水区,通常会因为淹没区原有有机物数量大,生物分解GHG排放较多,从而产生比其他地区更多的碳排放,并且,水电蓄水区碳排放通常被归类为水电运营阶段碳排放.Barros等[67]指出,假设水电水库面积增加5000km2,且该水电位于北温带和寒带地区,则碳排放可能会增加1~2Tg C/a.然而,在热带地区(非亚马逊河流域)对同样的水电水库扩建,则因蓄水区生物质GHG排放多于北温带和寒温带地区,每年的碳排放量可能会增加4Tg C/a.而亚马逊河流域的水电碳排放量则进一步增加到7Tg C/a.所以,水电碳足迹与水电地理位置和环境有关.
同时,导致水电碳足迹区域差异的还有气候因素.在湿润多雨的地区,水电蓄水量通常高于干燥缺雨地区的水电蓄水量.因此,这些湿润地区的水电装机量和实际产能更为吻合,有效减少了装机量过剩的情况,从而避免了需要额外能源来维持机械运作的问题.相比之下,干燥缺雨地区由于水电蓄水量较低,可能会面临装机量过剩的问题,这不仅浪费资源,还会因为需要额外的能源来维持机械运转而导致更高的碳足迹.因此,气候因素在不同区域的水电碳足迹差异中起着关键作用,湿润多雨的地区具有显著的碳足迹优势.
总之,水电碳足迹的区域化差异是显著的,在进行水电规划和建造时,为了降低碳排放,应充分考量水电的区域化差异.然而,当前关于水电碳足迹区域化差异的文献较少,未来根据水电碳足迹的影响因素可以进一步从空间分布和地理位置的角度进行研究.
尽管水电在世界范围内得到大力推广,然而,IPCC虽然认为水电属于可再生能源,但同时指出,由于水电的环境影响较大,其是否是绿色能源的定义至今仍待明确[68-69].在关于可再生能源和减缓气候变化的特别报告中,IPCC将关于水电大坝碳排放的结论总结为对于水库是净排放还是净吸收还没有达成共识[38].该报告将水电定义为每千瓦时发电产生的环境影响仅占包括风能和太阳能在内的任何其他能源的一半或更少[39].该结论表明水电是优质的可再生能源,其环境危害较小.但由于在热带地区水电碳排放值极高,也有学者对水电是绿色能源的结论提出质疑.Fearnside[70]指出,尽管IPCC报告中的汇总表明该研究使用了来自热带水坝的三个值,但其中罗列的来自不同气候带的11个水坝均不位于热带地区,对热带水电碳足迹案例举证较为缺乏.因此,对于水电低碳的性质仍存在争议.
由于水电碳足迹计算边界很难界定,许多研究存在对生命周期系统边界不统一而导致结果不精确的问题.譬如,巴西第一份国家温室气体排放清单中的估算忽略了水电涡轮机和溢洪道的碳排放[40];Abril等[71]指出水库中树木、木材在水上腐烂产生的二氧化碳常被忽视,且该情况在亚马逊水库中格外严重;Chu等[72]指出,水电运行阶段化石能源使用统计不完整是影响中国水电碳足迹计算误差的主要原因之一.
尽管各国开始对水电全生命周期中的碳排放进行评估,但由于计算方法的差异、通用的数据库、多变的环境,以及水电自身因素(如淹没地区大小、淹没地区GHG吸收能力、蓄水区域的生物GHG释放等),目前还无法实现对水电碳排放进行统一的研究和优化管理.在世界范围内,对于水电完整的碳排放量计算研究还有待完善.
4.1 对水电碳排放产生影响的主要因素有:水电碳足迹计算方法差异、水电生命周期中的建造阶段和运行阶段、水电蓄水区域气候条件、水电蓄水量多少、水电装机量以及水电类型等.
4.2 水电具有蓄水面积越大,碳排放越多;装机量越多,维护和运行阶段因能源消耗产生的碳排放越多;气候越湿润的地方(热带雨林地区除外)产生的碳排放越少;热带雨林地区水电碳排放较多;径流式水电碳排放小于蓄水式水电站等特点.
4.3 水电地理位置、周边环境和所处地气候等区域性问题亦对水电碳排放产生突出的影响,从而改变了水电生命周期碳排放计算结果.
4.4 当前对水电碳排放区域化差异的研究较为缺少.在未来的研究中,可以国家为范围,对境内所有水电碳排放计算结果使用GIS技术进行地理信息建模,结合区域化差异,从地理空间位置的角度对水电碳排放问题进行进分析,从而对现有水电碳排放因素有更全面的理解.加强现有水电碳排放优化,在未来实现水电净零碳排放设计、管理和运行.
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2025年第45卷第4期
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  • 接收时间:2024-09-30
  • 首发时间:2026-03-19
  • 出版时间:2025-04-20
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  • 收稿日期:2024-09-30
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国家电网有限公司总部科技项目资助(5200-202314489A-3-2-ZN)
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    1.国网冀北电力有限公司电力科学研究院,北京 100045
    2.中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085

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2种不同金属材料的力学参数

Family
属数
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genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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