Article(id=1304921527565181696, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1304921526004904728, articleNumber=null, orderNo=null, doi=10.16790/j.cnki.1009-9239.im.2026.03.002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752336000000, receivedDateStr=2025-07-13, revisedDate=1756051200000, revisedDateStr=2025-08-25, acceptedDate=null, acceptedDateStr=null, onlineDate=1789047136441, onlineDateStr=2026-09-10, pubDate=1773936000000, pubDateStr=2026-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789047136441, onlineIssueDateStr=2026-09-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789047136441, creator=13701087609, updateTime=1789047136441, updator=13701087609, issue=Issue{id=1304921526004904728, tenantId=1146029695717560320, journalId=1149653034449285133, year='2026', volume='59', issue='3', pageStart='1', pageEnd='154', issueExtLink='null', onlineDate='null', pubDate='1773936000000', pubDateStr='2026-03-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789047136068, creator='13701087609', updateTime=1789118116024, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1305219237560217894, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1304921526004904728, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1305219237560217895, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1304921526004904728, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=9, endPage=18, ext={EN=ArticleExt(id=1304921527758119681, articleId=1304921527565181696, tenantId=1146029695717560320, journalId=1149653034449285133, language=EN, title=Carbon footprint and environmental impact assessment of an 800 kVA epoxy cast dry-type transformer, columnId=1304921526780850970, journalTitle=Insulating Materials, columnName=Special Issue on Low-carbon Environmental Protection Advanced Insulation Materials, runingTitle=null, highlight=null, articleAbstract=

The environmental impact of greenhouse gases has garnered widespread global attention, and the low-carbon transformation of power equipment is of great significance for achieving the carbon peaking and carbon neutrality goals. Based on the life cycle assessment (LCA) method, we focused on the raw material acquisition, product manufacturing, and waste disposal stages of an 800 kVA epoxy cast dry-type transformer, and evaluated its carbon footprint and environmental impact from a material perspective. The Monte Carlo simulation method based on the triangular distribution and Sobol sequence was adopted to conduct uncertainty analysis on the carbon footprint results, so as to assess the uncertainty of carbon emissions from key resources. Based on two environmental impact assessment methods CML-IA baseline 2001 and ReCiPe 2016, the environmental impact degree of transformer at each stage was comprehensively evaluated. The results show that the total carbon footprint of the transformer is 8 996.25 kgCO2e, with the raw material acquisition stage contributing the most to the product carbon footprint, reaching 7 186.51 kgCO2e. Copper, silicon steel sheets, and epoxy resin are the main carbon sources, accounting for 42.87%, 31.17%, and 23.93%, respectively. Both sensitivity analysis methods are consistent with the actual situation, but the 95% confidence interval obtained by the Sobol sequence method is significantly wider than the [8 691.92, 9 311.68] kgCO2e of the triangular distribution, demonstrating a more sufficient ability to express uncertainty. The first-order sensitivity indices of the two key resources, epoxy resin and power consumption, calculated by the two methods are 0.460 and 0.499, respectively, indicating that they have the most obvious impact on the carbon footprint of the transformer. The environmental impact assessment results of CML-IA baseline 2001 and ReCipe 2016 show that the raw material acquisition stage dominates all environmental damage categories, with the most significant impact on marine ecotoxicity. The core causes are the heavy metal emissions during the mining and processing of copper and silicon steel sheets, as well as the organic pollutants released during the synthesis of epoxy resin.

, authors=Shuangshuang TIAN1, Yingyu WU1, Yunjian WU1, Chao GAO2, Jiahe YU2, Xiaoxing ZHANG1, *, authorsList=Shuangshuang TIAN, Yingyu WU, Yunjian WU, Chao GAO, Jiahe YU, Xiaoxing ZHANG, authorCompany=null, correspAuthors=Xiaoxing ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1304921529087714056, articleId=1304921527565181696, tenantId=1146029695717560320, journalId=1149653034449285133, language=CN, title=800 kVA环氧浇注干式变压器碳足迹与环境影响评估, columnId=1304921527053480732, journalTitle=绝缘材料, columnName=低碳环保先进绝缘材料专题, runingTitle=null, highlight=null, articleAbstract=

温室气体对环境的影响已引起全球关注,而电力装备的低碳化转型对于实现“双碳”目标具有重要意义。本文基于全生命周期评估(life cycle assessment,LCA)方法,聚焦于800 kVA环氧浇注干式变压器的原材料获取、产品制造及废弃物处理阶段,重点从材料视角评价其碳足迹与环境影响。采用基于三角分布和Sobol序列的蒙特卡洛模拟方法对碳足迹结果进行不确定性分析,以评估关键资源碳排放的不确定性。基于CML-IA baseline 2001和ReCiPe 2016两种环境影响评估方法,对变压器各阶段的环境影响程度进行综合评估。结果表明:该变压器总碳足迹为8 996.25 kgCO2e,其中原材料获取阶段对产品碳足迹贡献最大,达到7 186.51 kgCO2e,铜、硅钢片以及环氧树脂为主要碳源,在该阶段分别有着42.87%、31.17%、23.93%的占比;两种敏感性分析方法均与实际情况相符,但Sobol序列方法得出的95%置信区间显著宽于三角分布的[8 691.92,9 311.68] kgCO2e,具备更充分的不确定性表达能力;两种方法计算出环氧树脂和电力消耗两种关键资源的一阶敏感性指数分别为0.460和0.499,说明二者对变压器碳足迹的影响最为明显;CML-IA baseline 2001与ReCipe 2016两种环境影响评估结果均表明原材料获取阶段在所有环境损害类别中均占据主导地位,其中对海水生态毒性影响最为明显,其核心诱因是铜与硅钢片开采加工过程中的重金属排放,以及环氧树脂合成阶段释放的有机污染物。

, authors=田双双1, 吴影宇1, 伍云健1, 高超2, 余家赫2, 张晓星1, *, authorsList=田双双, 吴影宇, 伍云健, 高超, 余家赫, 张晓星, authorCompany=null, correspAuthors=张晓星, authorNote=

田双双(1989-),女(汉族),山东泰安人,副教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究

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张晓星(1972-),男(汉族),湖北潜江人,教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究。
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田双双(1989-),女(汉族),山东泰安人,副教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究

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Zhenjiang: Jiangsu University of Science and Technology,2022., articleTitle=Corrosion behavior and law of copper in organic acid environment, refAbstract=null), Reference(id=1304921537765729162, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, doi=null, pmid=null, pmcid=null, year=2024, volume=40, issue=11, pageStart=25, pageEnd=34, url=null, language=null, rfNumber=35, rfOrder=55, authorNames=张绪振, 褚宏宪, 孔令号, journalName=海洋地质前沿, refType=null, unstructuredReference=张绪振,褚宏宪,孔令号,.莱州湾表层海水重金属分布特征及生态环境评价[J].海洋地质前沿,2024,40(11):25-34., articleTitle=莱州湾表层海水重金属分布特征及生态环境评价, refAbstract=null), Reference(id=1304921537841226635, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, doi=null, pmid=null, pmcid=null, year=2024, volume=40, issue=11, pageStart=25, pageEnd=34, url=null, language=null, rfNumber=35, rfOrder=56, authorNames=ZHANG Xuzhen, CHU Hongxian, KONG Linghao, journalName=Marine Geology Frontiers, refType=null, unstructuredReference=ZHANG Xuzhen, CHU Hongxian, KONG Linghao, et al. 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Marine Geology Frontiers,2024,40(11):25-34., articleTitle=Distribution and ecological environment assessment of heavy metals in surface seawater of Laizhou Bay, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1304921529330983689, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, xref=1, ext=[AuthorCompanyExt(id=1304921529339372298, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, companyId=1304921529330983689, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, Hubei University of Technology, Wuhan 430068, China), AuthorCompanyExt(id=1304921529347760907, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, companyId=1304921529330983689, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1湖北工业大学 新能源及电网装备安全监测湖北省工程研究中心,湖北 武汉 430068)]), AuthorCompany(id=1304921529419064076, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, xref=2, ext=[AuthorCompanyExt(id=1304921529427452685, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, companyId=1304921529419064076, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2CSG Electric Power Research Institute Co., Ltd., Guangzhou 510663, China), AuthorCompanyExt(id=1304921529435841294, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, companyId=1304921529419064076, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2南方电网科学研究院有限责任公司,广东 广州 510663)])], figs=[ArticleFig(id=1304921531507827511, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Fig.1, caption=Carbon footprint accounting boundaries and process flows, figureFileSmall=1YlgHndol3HKRFng20Eklw==, figureFileBig=4kHbgby0TuhahTSBzzwjZA==, tableContent=null), ArticleFig(id=1304921531587519288, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=图1, caption=碳足迹核算边界及工艺流程, figureFileSmall=1YlgHndol3HKRFng20Eklw==, figureFileBig=4kHbgby0TuhahTSBzzwjZA==, tableContent=null), ArticleFig(id=1304921531751097145, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Fig.2, caption=Sensitivity analysis results, figureFileSmall=RmHfG3cXGyk5zdM1zbtOGA==, figureFileBig=U17NreWoCMc+xdRAj8AcTw==, tableContent=null), ArticleFig(id=1304921531809817402, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=图2, caption=敏感性分析结果, figureFileSmall=RmHfG3cXGyk5zdM1zbtOGA==, figureFileBig=U17NreWoCMc+xdRAj8AcTw==, tableContent=null), ArticleFig(id=1304921531872731963, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Fig.3, caption=Standardized results of different evaluation methods, figureFileSmall=cCEuujQQ+y7+6ewKACWvdA==, figureFileBig=hwrWTgQzG/+NvbC7zaVNNw==, tableContent=null), ArticleFig(id=1304921531960812348, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=图3, caption=不同评价方法标准化结果, figureFileSmall=cCEuujQQ+y7+6ewKACWvdA==, figureFileBig=hwrWTgQzG/+NvbC7zaVNNw==, tableContent=null), ArticleFig(id=1304921532032115517, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 1, caption=

Key data list of raw material acquisition stage

, figureFileSmall=null, figureFileBig=null, tableContent=
物料消耗量材料运输距离/km汽车载重/t
硅钢片1 360 kg硅钢14010
铜箔(绕组)575 kg25020
铜线110 kg15020
环氧树脂195 kg环氧树脂5020
紧固件1个93020
温控器1个15010
风机6个15010
外壳1个铝合金15010
铜排8 mm厚,1.20 m长,φ=80 mm13510
5 mm厚,1.35 m长,φ=50 mm13510
紫铜管1.5 mm厚,4 m长,φ=16 mm13510
热缩管6 m长,φ=12 mm聚烯烃16010
网格板1.2 m长,0.6 m宽玻璃纤维43010
), ArticleFig(id=1304921532116001598, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表1, caption=

原材料获取阶段主要数据清单

, figureFileSmall=null, figureFileBig=null, tableContent=
物料消耗量材料运输距离/km汽车载重/t
硅钢片1 360 kg硅钢14010
铜箔(绕组)575 kg25020
铜线110 kg15020
环氧树脂195 kg环氧树脂5020
紧固件1个93020
温控器1个15010
风机6个15010
外壳1个铝合金15010
铜排8 mm厚,1.20 m长,φ=80 mm13510
5 mm厚,1.35 m长,φ=50 mm13510
紫铜管1.5 mm厚,4 m长,φ=16 mm13510
热缩管6 m长,φ=12 mm聚烯烃16010
网格板1.2 m长,0.6 m宽玻璃纤维43010
), ArticleFig(id=1304921532208276287, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 2, caption=

Key data list of product during production stage

, figureFileSmall=null, figureFileBig=null, tableContent=
生产阶段生产装置耗电量/(kW·h)
绕线模烘炉1 152
内筒绝缘QC12K-4*2500剪板机0.4
低压绕线RJS-1000箔绕机150
低压干燥烘炉192
高压绕线GRS-800绕线机36
外包处理3T行车0.55
装模3T行车0.55
高压预干燥加热炉840
浇注浇注罐255
干燥加热炉600
脱模3T行车1.1
表面高低压打磨打磨机0.71
装配3T行车1.1
装夹件垫块压钉3T行车0.55
低压引线制作

DMX-303多工位母线加工机

01B-FF-2000热风机

0.568 5
高压凸台焊接高压引线制作01B-FF-2000热风机0.041 7
电阻测试直流电阻测试仪16.667
变压比侧试变比测试仪2.25
空载损耗调压器28.833
高低压耐压变压器26.25
负载损耗调压器8.333
阻抗电压Y2-225S-4三相异步电机1.5
装外壳3T行车0.55
清洁整理YE2-132M-4空压机0.375
), ArticleFig(id=1304921532279579456, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表2, caption=

产品生产阶段主要数据清单

, figureFileSmall=null, figureFileBig=null, tableContent=
生产阶段生产装置耗电量/(kW·h)
绕线模烘炉1 152
内筒绝缘QC12K-4*2500剪板机0.4
低压绕线RJS-1000箔绕机150
低压干燥烘炉192
高压绕线GRS-800绕线机36
外包处理3T行车0.55
装模3T行车0.55
高压预干燥加热炉840
浇注浇注罐255
干燥加热炉600
脱模3T行车1.1
表面高低压打磨打磨机0.71
装配3T行车1.1
装夹件垫块压钉3T行车0.55
低压引线制作

DMX-303多工位母线加工机

01B-FF-2000热风机

0.568 5
高压凸台焊接高压引线制作01B-FF-2000热风机0.041 7
电阻测试直流电阻测试仪16.667
变压比侧试变比测试仪2.25
空载损耗调压器28.833
高低压耐压变压器26.25
负载损耗调压器8.333
阻抗电压Y2-225S-4三相异步电机1.5
装外壳3T行车0.55
清洁整理YE2-132M-4空压机0.375
), ArticleFig(id=1304921532363465537, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 3, caption=

Key data list for waste disposal stage

, figureFileSmall=null, figureFileBig=null, tableContent=
阶段名称操作质量/kg
废弃物处理阶段环氧树脂焚烧195
铜回收557.86
硅钢回收816
), ArticleFig(id=1304921532451545922, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表3, caption=

废弃物处理阶段主要数据清单

, figureFileSmall=null, figureFileBig=null, tableContent=
阶段名称操作质量/kg
废弃物处理阶段环氧树脂焚烧195
铜回收557.86
硅钢回收816
), ArticleFig(id=1304921532527043395, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 4, caption=

Major activity units and its carbon emission factors

, figureFileSmall=null, figureFileBig=null, tableContent=
活动单位碳排放因子
硅钢/(kgCO2e/kg)1.647 1
铜/(kgCO2e/kg)3.900 5
环氧树脂/(kgCO2e/kg)8.820 5
铝合金/(kgCO2e/kg)5.128 5
铁/(kgCO2e/kg)1.442 0
玻璃纤维/(kgCO2e/kg)2.516 6
电力/(kgCO2e/kWh)1.088 8
运输/(kgCO2e/(t·km))0.257 7
), ArticleFig(id=1304921532589957956, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表4, caption=

主要活动单位及其对应碳排放因子

, figureFileSmall=null, figureFileBig=null, tableContent=
活动单位碳排放因子
硅钢/(kgCO2e/kg)1.647 1
铜/(kgCO2e/kg)3.900 5
环氧树脂/(kgCO2e/kg)8.820 5
铝合金/(kgCO2e/kg)5.128 5
铁/(kgCO2e/kg)1.442 0
玻璃纤维/(kgCO2e/kg)2.516 6
电力/(kgCO2e/kWh)1.088 8
运输/(kgCO2e/(t·km))0.257 7
), ArticleFig(id=1304921532661261125, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 5, caption=

Carbon footprint distribution of epoxy cast dry-type transformers

, figureFileSmall=null, figureFileBig=null, tableContent=
生命周期阶段碳排放量/kgCO2e占比/%
原材料获取7 186.5179.89
产品生产3 609.7240.12
废弃物处理-1 799.98-20.01
), ArticleFig(id=1304921532753535814, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表5, caption=

环氧浇注干式变压器碳足迹分布

, figureFileSmall=null, figureFileBig=null, tableContent=
生命周期阶段碳排放量/kgCO2e占比/%
原材料获取7 186.5179.89
产品生产3 609.7240.12
废弃物处理-1 799.98-20.01
), ArticleFig(id=1304921532816450375, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 6, caption=

Carbon footprint distribution of raw material acquisition stage

, figureFileSmall=null, figureFileBig=null, tableContent=
类别碳排放量/kgCO2e占比/%
硅钢片2240.0631.17
铜(绕组)2242.7931.21
铜(引线)429.065.97
环氧树脂1720.0023.93
紧固件7.210.10
铜排1371.005.16
铜排226.660.37
紫铜管11.720.16
网格版9.740.14
铝合金外壳30.200.42
原材料运输97.931.36
), ArticleFig(id=1304921532887753544, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表6, caption=

原材料获取阶段碳足迹分布

, figureFileSmall=null, figureFileBig=null, tableContent=
类别碳排放量/kgCO2e占比/%
硅钢片2240.0631.17
铜(绕组)2242.7931.21
铜(引线)429.065.97
环氧树脂1720.0023.93
紧固件7.210.10
铜排1371.005.16
铜排226.660.37
紫铜管11.720.16
网格版9.740.14
铝合金外壳30.200.42
原材料运输97.931.36
), ArticleFig(id=1304921532967445321, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 7, caption=

Carbon footprint distribution of product production stage

, figureFileSmall=null, figureFileBig=null, tableContent=
生产过程碳排放量/kgCO2e占比/%生产过程碳排放量/kgCO2e占比/%
绕线模1254.3034.75装配1.20
内筒绝缘0.44装夹件垫块压钉0.60
低压绕线163.324.52低压引线制作0.62
低压干燥209.055.79高压引线制作0.05
高压绕线39.201.10电阻测试18.150.50
外包处理0.60变压比侧试2.450.10
装模0.600空载损耗31.390.90
高压预干燥914.5925.34高低压耐压28.580.80
浇注277.647.69负载损耗9.070.30
干燥653.2818.10阻抗电压1.63
脱模1.20装外壳0.60
表面处理(高低压打磨)0.77清洁整理0.41
), ArticleFig(id=1304921533042942794, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表7, caption=

产品生产阶段碳足迹分布

, figureFileSmall=null, figureFileBig=null, tableContent=
生产过程碳排放量/kgCO2e占比/%生产过程碳排放量/kgCO2e占比/%
绕线模1254.3034.75装配1.20
内筒绝缘0.44装夹件垫块压钉0.60
低压绕线163.324.52低压引线制作0.62
低压干燥209.055.79高压引线制作0.05
高压绕线39.201.10电阻测试18.150.50
外包处理0.60变压比侧试2.450.10
装模0.600空载损耗31.390.90
高压预干燥914.5925.34高低压耐压28.580.80
浇注277.647.69负载损耗9.070.30
干燥653.2818.10阻抗电压1.63
脱模1.20装外壳0.60
表面处理(高低压打磨)0.77清洁整理0.41
), ArticleFig(id=1304921533122634571, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 8, caption=

Sensitivity of carbon emissions from major materials

, figureFileSmall=null, figureFileBig=null, tableContent=
消耗品碳排放变化量/kgCO2e灵敏度/%
硅钢片89.6020.996
54.3990.611
环氧树脂343.9993.866
铝合金37.0990.417
0.7210.008
玻璃纤维3.0240.034
原材料运输9.8100.110
电力360.9734.057
), ArticleFig(id=1304921533193937740, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表8, caption=

主要材料碳排放量灵敏度

, figureFileSmall=null, figureFileBig=null, tableContent=
消耗品碳排放变化量/kgCO2e灵敏度/%
硅钢片89.6020.996
54.3990.611
环氧树脂343.9993.866
铝合金37.0990.417
0.7210.008
玻璃纤维3.0240.034
原材料运输9.8100.110
电力360.9734.057
), ArticleFig(id=1304921533265240909, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 9, caption=

CML-IA baseline characterization results

, figureFileSmall=null, figureFileBig=null, tableContent=
影响类别原材料获取产品生产废弃物处理
非生物矿产资源消耗/kgSbeq1.310.0019-1.03
非生物化石能源消耗/MJ8.2×1043.12×104-1.05×104
全球变暖影响/kgCO2e7.13×1033.53×103-1.85×103
臭氧层破坏/kgCFC-11eq0.000 32.62×10-5-0.0002
人体毒性/kg1,4-DBeq1.1×1051.25×103-8.58×104
淡水生态毒性/kg1,4-DBeq5.29×1041.4×103-3.99×104
海水生态毒性/kg1,4-DBeq1.4×1085.69×106-1.1×108
陆地生态毒性/kg1,4-DBeq15813.2-113
光化学臭氧/kgC2H4eq11.60.59-8.45
酸化/kgSO2eq27215.8-206
水体富营养化/kgNeq1943.6-151
), ArticleFig(id=1304921533332349774, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表9, caption=

CML-IA baseline特征化结果

, figureFileSmall=null, figureFileBig=null, tableContent=
影响类别原材料获取产品生产废弃物处理
非生物矿产资源消耗/kgSbeq1.310.0019-1.03
非生物化石能源消耗/MJ8.2×1043.12×104-1.05×104
全球变暖影响/kgCO2e7.13×1033.53×103-1.85×103
臭氧层破坏/kgCFC-11eq0.000 32.62×10-5-0.0002
人体毒性/kg1,4-DBeq1.1×1051.25×103-8.58×104
淡水生态毒性/kg1,4-DBeq5.29×1041.4×103-3.99×104
海水生态毒性/kg1,4-DBeq1.4×1085.69×106-1.1×108
陆地生态毒性/kg1,4-DBeq15813.2-113
光化学臭氧/kgC2H4eq11.60.59-8.45
酸化/kgSO2eq27215.8-206
水体富营养化/kgNeq1943.6-151
), ArticleFig(id=1304921533399458639, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 10, caption=

ReCipe 2016 midpoint characterization results

, figureFileSmall=null, figureFileBig=null, tableContent=
影响类别原材料获取产品生产废弃物处理
全球变暖/kgCO2e7.36×1033.64×103-1.81×103
臭氧层消耗/kgCFC11eq0.00760.000 8-0.005 8
电离辐射/kBqCo-60eq28157.2-198
臭氧形成,人类健康/kgNOxeq40.310.1-24.7
细颗粒物形成/kgPM2.5eq80.95.62-61.1
光化学臭氧形成,生态系统/kgNOxeq41.210.1-25.3
陆地酸化/kgSO2eq22712.6-173
淡水富营养化/kgPeq59.80.719-47.3
海洋富营养化/kgNeq3.290.0445-2.62
陆地生态毒性/kg1,4-DCB1.47×1063.26×103-1.17×106
淡水生态毒性/kg1,4-DCB1.09×104115-8.43×103
海洋生态毒性/kg1,4-DCB1.57×104147-1.22×104
人类致癌毒性/kg1,4-DCB4.29×103112-2.97×103
人类非致癌毒性/kg1,4-DCB3.93×1051.15×103-3.12×105
土地利用/m2a crop eq32044.3-242
矿场资源稀缺/kgCueq9471.96-723
化石资源耗竭/kgCueq1.87×103708-283
水消耗/m31348.9922
), ArticleFig(id=1304921533491733328, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表10, caption=

ReCipe 2016中点特征化结果

, figureFileSmall=null, figureFileBig=null, tableContent=
影响类别原材料获取产品生产废弃物处理
全球变暖/kgCO2e7.36×1033.64×103-1.81×103
臭氧层消耗/kgCFC11eq0.00760.000 8-0.005 8
电离辐射/kBqCo-60eq28157.2-198
臭氧形成,人类健康/kgNOxeq40.310.1-24.7
细颗粒物形成/kgPM2.5eq80.95.62-61.1
光化学臭氧形成,生态系统/kgNOxeq41.210.1-25.3
陆地酸化/kgSO2eq22712.6-173
淡水富营养化/kgPeq59.80.719-47.3
海洋富营养化/kgNeq3.290.0445-2.62
陆地生态毒性/kg1,4-DCB1.47×1063.26×103-1.17×106
淡水生态毒性/kg1,4-DCB1.09×104115-8.43×103
海洋生态毒性/kg1,4-DCB1.57×104147-1.22×104
人类致癌毒性/kg1,4-DCB4.29×103112-2.97×103
人类非致癌毒性/kg1,4-DCB3.93×1051.15×103-3.12×105
土地利用/m2a crop eq32044.3-242
矿场资源稀缺/kgCueq9471.96-723
化石资源耗竭/kgCueq1.87×103708-283
水消耗/m31348.9922
), ArticleFig(id=1304921533579813713, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=EN, label=Table 11, caption=

ReCipe 2016 endpoint impact results

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损害类别原材料获取产品生产废弃物处理
人类健康0.1620.007 58-0.121
生态系统损耗0.000 1451.53×10-5-9.97×10-5
资源损耗70770.9-152
), ArticleFig(id=1304921533655311186, tenantId=1146029695717560320, journalId=1149653034449285133, articleId=1304921527565181696, language=CN, label=表11, caption=

ReCipe 2016终点影响结果

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人类健康0.1620.007 58-0.121
生态系统损耗0.000 1451.53×10-5-9.97×10-5
资源损耗70770.9-152
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800 kVA环氧浇注干式变压器碳足迹与环境影响评估
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田双双 1 , 吴影宇 1 , 伍云健 1 , 高超 2 , 余家赫 2 , 张晓星 1, *
绝缘材料 | 低碳环保先进绝缘材料专题 2026,59(3): 9-18
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绝缘材料 |低碳环保先进绝缘材料专题 2026 , 59 (3) : 9 -18
800 kVA环氧浇注干式变压器碳足迹与环境影响评估
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田双双(1989-),女(汉族),山东泰安人,副教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究

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田双双(1989-),女(汉族),山东泰安人,副教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究

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田双双1, 吴影宇1, 伍云健1, 高超2, 余家赫2, 张晓星1, *
作者信息
  • 1湖北工业大学 新能源及电网装备安全监测湖北省工程研究中心,湖北 武汉 430068
  • 2南方电网科学研究院有限责任公司,广东 广州 510663
通讯作者:
张晓星(1972-),男(汉族),湖北潜江人,教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究。
作者简介:

田双双(1989-),女(汉族),山东泰安人,副教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究

Carbon footprint and environmental impact assessment of an 800 kVA epoxy cast dry-type transformer
Shuangshuang TIAN1, Yingyu WU1, Yunjian WU1, Chao GAO2, Jiahe YU2, Xiaoxing ZHANG1, *
Affiliations
  • 1Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, Hubei University of Technology, Wuhan 430068, China
  • 2CSG Electric Power Research Institute Co., Ltd., Guangzhou 510663, China
出版时间: 2026-03-20 doi: 10.16790/j.cnki.1009-9239.im.2026.03.002
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温室气体对环境的影响已引起全球关注,而电力装备的低碳化转型对于实现“双碳”目标具有重要意义。本文基于全生命周期评估(life cycle assessment,LCA)方法,聚焦于800 kVA环氧浇注干式变压器的原材料获取、产品制造及废弃物处理阶段,重点从材料视角评价其碳足迹与环境影响。采用基于三角分布和Sobol序列的蒙特卡洛模拟方法对碳足迹结果进行不确定性分析,以评估关键资源碳排放的不确定性。基于CML-IA baseline 2001和ReCiPe 2016两种环境影响评估方法,对变压器各阶段的环境影响程度进行综合评估。结果表明:该变压器总碳足迹为8 996.25 kgCO2e,其中原材料获取阶段对产品碳足迹贡献最大,达到7 186.51 kgCO2e,铜、硅钢片以及环氧树脂为主要碳源,在该阶段分别有着42.87%、31.17%、23.93%的占比;两种敏感性分析方法均与实际情况相符,但Sobol序列方法得出的95%置信区间显著宽于三角分布的[8 691.92,9 311.68] kgCO2e,具备更充分的不确定性表达能力;两种方法计算出环氧树脂和电力消耗两种关键资源的一阶敏感性指数分别为0.460和0.499,说明二者对变压器碳足迹的影响最为明显;CML-IA baseline 2001与ReCipe 2016两种环境影响评估结果均表明原材料获取阶段在所有环境损害类别中均占据主导地位,其中对海水生态毒性影响最为明显,其核心诱因是铜与硅钢片开采加工过程中的重金属排放,以及环氧树脂合成阶段释放的有机污染物。

生命周期评价  /  干式变压器  /  碳足迹  /  敏感性分析  /  环境影响

The environmental impact of greenhouse gases has garnered widespread global attention, and the low-carbon transformation of power equipment is of great significance for achieving the carbon peaking and carbon neutrality goals. Based on the life cycle assessment (LCA) method, we focused on the raw material acquisition, product manufacturing, and waste disposal stages of an 800 kVA epoxy cast dry-type transformer, and evaluated its carbon footprint and environmental impact from a material perspective. The Monte Carlo simulation method based on the triangular distribution and Sobol sequence was adopted to conduct uncertainty analysis on the carbon footprint results, so as to assess the uncertainty of carbon emissions from key resources. Based on two environmental impact assessment methods CML-IA baseline 2001 and ReCiPe 2016, the environmental impact degree of transformer at each stage was comprehensively evaluated. The results show that the total carbon footprint of the transformer is 8 996.25 kgCO2e, with the raw material acquisition stage contributing the most to the product carbon footprint, reaching 7 186.51 kgCO2e. Copper, silicon steel sheets, and epoxy resin are the main carbon sources, accounting for 42.87%, 31.17%, and 23.93%, respectively. Both sensitivity analysis methods are consistent with the actual situation, but the 95% confidence interval obtained by the Sobol sequence method is significantly wider than the [8 691.92, 9 311.68] kgCO2e of the triangular distribution, demonstrating a more sufficient ability to express uncertainty. The first-order sensitivity indices of the two key resources, epoxy resin and power consumption, calculated by the two methods are 0.460 and 0.499, respectively, indicating that they have the most obvious impact on the carbon footprint of the transformer. The environmental impact assessment results of CML-IA baseline 2001 and ReCipe 2016 show that the raw material acquisition stage dominates all environmental damage categories, with the most significant impact on marine ecotoxicity. The core causes are the heavy metal emissions during the mining and processing of copper and silicon steel sheets, as well as the organic pollutants released during the synthesis of epoxy resin.

life cycle assessment  /  dry-type transformer  /  carbon footprint  /  sensitivity analysis  /  environmental impacts
田双双, 吴影宇, 伍云健, 高超, 余家赫, 张晓星. 800 kVA环氧浇注干式变压器碳足迹与环境影响评估. 绝缘材料, 2026 , 59 (3) : 9 -18 . DOI: 10.16790/j.cnki.1009-9239.im.2026.03.002
Shuangshuang TIAN, Yingyu WU, Yunjian WU, Chao GAO, Jiahe YU, Xiaoxing ZHANG. Carbon footprint and environmental impact assessment of an 800 kVA epoxy cast dry-type transformer[J]. Insulating Materials, 2026 , 59 (3) : 9 -18 . DOI: 10.16790/j.cnki.1009-9239.im.2026.03.002
由于工业化的快速发展,温室气体排放已导致全球变暖、海平面上升等一系列环境问题。我国提出的“碳达峰、碳中和”目标[1-3],为全球应对气候变化提供了重要指引。作为能源生产和消耗大户,电力行业的碳足迹与环境影响量化,以及针对性低碳转型策略的制定,对于提前实现“双碳”目标具有至关重要的意义[4-5]
全生命周期评价(life cycle assessment,LCA)已成为量化电力行业碳足迹与环境影响的重要工具[6-10]。作为电力行业的核心设备,电力装备的LCA研究为推动行业低碳转型提供了关键突破口[11-14]。周玮等[15]对分布式风力发电机全生命周期碳排放量进行核算,结果表明其碳排放主要集中在生产运输和建设施工阶段。付鲁军等[16]对比分析了12 kV SF6与空气绝缘环网开关设备中断路器原材料获取阶段和制造阶段的碳排放量,结果表明在原材料获取阶段干燥空气绝缘断路器碳排放量高于SF6绝缘断路器。D F D SOUZA等[17]建立了电动机LCA模型,定量评估其各个阶段对环境的影响,结果表明使用阶段的影响最显著,占生命周期影响的90%以上。丁讯[18]利用LCA法明确了大型水平轴风力发电机的环境影响,得到对环境影响突出的指标有不可再生能源消耗、全球气候变暖和空气中无机粉尘排放。以上研究结果为不同电力装备提供了低碳转型思路。
变压器作为电力装备的重要组成部分[19-20],其LCA研究为电力装备低碳转型技术的发展提供了重要支撑[21]。张益兵等[22]基于LCA法建立了非晶油浸式配电变压器生命周期评价模型,计算了其碳足迹结果并使用泰勒级数对结果进行敏感性分析以及不确定性分析,结果表明使用阶段在全生命周期碳足迹占比高达99.45%,并且不确定性较低。WANG Y等[23]对200 kVA油浸式配电变压器进行碳足迹评价,结果同样表明产品在使用阶段的碳足迹占比远高于其他阶段,并且通过敏感性分析发现硅钢片和变压器油对该变压器碳足迹影响最为显著。毕子健等[24]利用LCA法计算了不同容量下10 kV油浸式与干式变压器从资源开采到运输再到用户端之前的碳排放,得到不同类型、不同容量变压器的碳足迹组成,为实现产品的低碳化提供数据参考。综合以上分析,现有的变压器LCA研究主要集中在油浸式变压器碳足迹的量化分析上,目前对干式变压器的LCA研究和环境影响评估仍然较为匮乏,导致变压器低碳设计路径尚未明确。
本研究基于LCA方法,聚焦材料角度,构建额定容量为800 kVA的环氧浇注式干式变压器的碳足迹与环境影响评估模型。通过量化变压器全生命周期各阶段的碳足迹,结合Sobol序列估计方法和基于三角分布的蒙特卡洛模拟方法对碳足迹计算结果进行敏感性分析。同时,采用CML-IA baseline和ReCipe 2016两种环境影响评价方法,明确各生命周期阶段的环境影响。希望研究结果能为新型绿色电力设备的开发和工业应用提供科学依据和参考,推动电力行业实现低碳转型和可持续发展。
本文研究的环氧浇注干式变压器的所有数据均来源于供应商。系统核算边界根据LCA方法划分为3个阶段:原材料获取阶段、产品生产阶段以及废弃物处理阶段[25-27]。每个阶段所涉及的主要资源和工艺流程如图1所示。样品总质量为2 515 kg,额定高压侧电压为10 kV,低压侧电压为0.4 kV,额定容量为800 kVA,额定频率为50 Hz,基准寿命为25年。结合实际情况和系统核算边界,本文建立了各阶段的主要清单数据,分别如表13所示。
根据变压器全生命周期系统边界的划分,该变压器碳足迹模型如式(1)所示。
E t=E y+E s+E f
式(1)中:Et为变压器碳足迹;Ey为变压器原材料获取阶段碳足迹;Es为变压器生产阶段碳足迹;Ef为变压器废弃物处理阶段碳足迹。碳足迹单位均为kgCO2e,表示各个生命周期阶段产生的CO2总量。
对该干式变压器全生命周期阶段碳足迹进行量化,如式(2)所示。
E=i=1nAi×Ei
式(2)中:E为变压器各生命周期阶段碳足迹,kgCO2e;Ai为第i种活动单位消耗量,kg、kWh或t·km;Ei为第i种活动单位的碳排放因子,kgCO2e/kg、kgCO2e/kWh或kgCO2e/(t·km)。
结合上述数据清单,该干式变压器主要活动单位及其碳排放因子如表4所示,数据均来源于Ecoinvent 3数据库。其中电力碳排放因子选取了中国武汉地区的区域电网碳排放因子,以更贴近设备制造过程中的实际电力来源情况;考虑到中国各地原材料生产差异相对较小,且部分国内数据缺乏公开可靠来源,因此其他材料碳排放因子采用了Ecoinvent 3中代表全球平均或中国通用情境的碳排放因子。
本文首先对所有资源消耗量进行+10%的浮动,以评估各输入参数波动对总碳排放量的影响,并筛选出影响较大的关键资源。进一步采用两种典型的蒙特卡洛模拟方法进行敏感性分析:一是基于三角分布的传统随机采样方法,二是基于Sobol序列的准随机采样方法。Sobol序列方法是一种基于方差分解的全局敏感性分析方法,通过蒙特卡洛抽样计算敏感性分析系数,区分各个参数的贡献及其交互作用,从而得出全局敏感性指标(f(x))。设 f(x)可积,且xi在[0,1]服从均匀分布,f(x)的表达式如式(3)所示[28-31]
f(x)=f(x1,xi)
总方差D可以分解为各个参数及其相互作用的组合,如式(4)所示。
D=iDi+i<jDij+i<j<kDijk++D12m
式(4)中:Di是由第i个参数xi引起的方差;Dij是由参数xixj之间的相互作用引起的方差;Dijk是3个参数共同作用时的交互贡献;D12m是所有参数全域耦合的交互贡献。
结果评价指标包括一阶敏感性指数Si和总敏感性指数STi,分别如式(5)和式(6)所示。
Si=DiD
STi=1-D~iD
式(5)~(6)中:Si为参数xi单独作用的敏感度;STi为参数xi单独及其与其他参数相互作用的敏感度;D~i为除参数xi外其他参数引起的方差。
针对前期筛选出的关键资源参数,本文在两种不同的敏感性分析方法中分别设定了参数的分布形式与波动范围:在三角分布中,假设各敏感参数的消耗量服从三角分布,其最小值为基准值的90%,最大值为基准值的110%,而最可能值即为基准消耗量。在基于Sobol序列的全局敏感性分析中,则假设所有敏感参数在基准值的±10%区间内服从均匀分布,并通过准随机采样全面探索输入空间,从而获得更稳健的全局敏感性指标。
为了全面反映变压器在全生命周期各阶段对环境的影响程度,本研究选择国际上广泛应用的CML-IA baseline与ReCiPe 2016评价方法对变压器各阶段的环境影响进行评估[32-33]。CML-IA baseline 方法主要考虑的中点环境影响评价指标包括全球变暖潜势、酸化潜势、人类毒性潜势、非生物资源枯竭潜势、光化学臭氧生成潜势、臭氧层耗竭潜势、淡水生态毒性潜势、陆地生态毒性潜势、海水生态毒性潜势以及富营养化潜势,共10种指标。这些指标能够从不同维度全面评估产品生命周期内对环境的潜在负面影响。ReCiPe 2016方法在CML模型的基础上进行了扩展,除了涵盖CML中的中点影响类型外,还将影响类型拓展至18种,并且增加了终点类型的评估,包括生态系统损耗、人体健康和资源耗竭等三大类终点影响。
对该环氧浇注干式变压器全生命周期碳足迹的量化结果进行分析,各阶段的碳排放量分布如表5所示,该产品碳足迹为8 996.25 kgCO2e。从表5可以看出,原材料获取阶段对干式变压器碳足迹的贡献最大,碳排放量达到7 186.51 kgCO2e。这一阶段的碳排放主要来源于铜、硅钢片以及环氧树脂3种关键材料的使用,其碳足迹的分布及占比见表6。从表6具体来看,铜的碳排放量占比为42.87%,硅钢片为31.17%,而环氧树脂为23.93%。铜的消耗量在所有原材料中仅次于硅钢片,铜的碳排放主要源自矿石冶炼和电解精炼过程,这一过程需要大量电力和化石燃料,因此其碳排放量较高。硅钢片的使用量在变压器中远高于其他材料,导致硅钢片的碳排放量占比较大。虽然环氧树脂的使用量远低于铜和硅钢片,但环氧树脂是石油基化工产品,其原料含碳量较高,因此环氧树脂的碳排放量虽然较少,但单体材料的碳排放较为显著。
在产品生产阶段,所有工序产生的碳排放量都来源于消耗的电能,表2已经给出产品生产阶段各工序设计的设备耗电量,各工序的碳足迹分布及占比如表7所示。从表7可以看出,绕线模、高压预干燥、干燥、浇注、低压干燥以及低压绕线对该阶段碳排放贡献占比较高,分别为34.75%、25.34%、18.10%、7.69%、5.79%以及4.52%,其余18个工序加起来对该阶段的碳排放贡献仅有3.81%。
废弃物处理阶段中环氧树脂均采用焚烧处理,会额外产生碳排放,而铜与硅钢片可以回收利用进而减少碳排放,因此废弃物处理阶段在产品全生命周期碳足迹的贡献为-1 799.98 kgCO2e。由此可见,使用高回收率的铜、高效硅钢片以及可降解循环利用的环氧树脂,并优化材料用量以及能源结构,可以有效减少变压器的碳足迹。
为了筛选出关键材料对产品碳足迹的影响程度,本研究对主要消耗品的用量进行了+10%的浮动,并计算了相应的碳排放变化量及灵敏度,具体数据见表8
表8可以看出,硅钢片、铜、环氧树脂、铝合金以及电力消耗对变压器碳足迹的灵敏度较高,其中电力消耗对碳足迹的变化最为敏感,灵敏度达到4.057%。尽管硅钢片和铜在全生命周期阶段的碳足迹贡献率高于环氧树脂,但考虑到这两种材料在废弃物处理阶段能够通过回收利用显著降低碳排放,而环氧树脂则在废弃物处理阶段完全通过焚烧方式处置,这一过程反而会产生额外的碳排放。因此环氧树脂的碳足迹灵敏度较硅钢和铜更为显著。
为全面评估材料消耗的不确定性对产品碳排放的影响,利用基于三角分布与Sobol序列两种典型的蒙特卡洛模拟方法进行敏感性分析,结果如图2所示。从图2(a)2(b)可以明显看出,Sobol序列方法中样本数据分布与标准正态分布基本吻合,并且95%的置信区间分布在8 436.538 8~9 556.572 5 kgCO2e,平均值为8 996.141 7 kgCO2e,说明计算结果能很好地反映实际碳足迹。对比图2(b)2(d)两种模拟结果可以看出,Sobol序列方法得出的95%置信区间显著宽于三角分布的8 691.92~9 311.68 kgCO2e,意味着Sobol序列方法具备更充分的不确定性表达能力。此外,Sobol序列方法可以进一步计算关键资源的敏感性指数,如图2(c)所示,其中环氧树脂和电力消耗的一阶敏感性指数分别为0.460和0.499,显著高于其他材料,进一步证明二者对变压器碳足迹的影响最为显著,与前述分析结果一致。
现有研究中,文献[20]仅能评估参数对结果的影响,并未考虑参数之间的影响,文献[21]中的单一三角分布仅输出概率区间。而本文构建的三角分布+Sobol序列模拟体系中,前者实现基础不确定性表征,后者不仅覆盖更宽的波动范围,还能通过一阶敏感性指数量化参数交互影响,解决传统方法的局限性。
利用CML-IA baseline方法对该干式变压器各类环境影响指数进行量化计算后,得到的特征化结果展示了各生命周期阶段在不同环境影响类别上的固有特征。对这些特征化结果进行标准化处理,从而进一步分析和比较各阶段在不同环境影响类别中的影响程度与参数大小。特征化与标准化结果分别见表9图3(a)
表9图3(a)可以看出,原材料获取阶段在11个环境影响类别中均占据最高的比例,且在非生物矿产资源消耗、人体毒性潜值、淡水生态毒性潜值以及海水生态毒性潜值等环境影响指标上表现出较大的影响。这主要是由于原材料获取阶段的碳排放贡献大部分来自于铜、硅钢片以及环氧树脂的使用,其中铜和硅钢片的生产涉及多个环节,导致大量能源、水资源和土地资源的消耗,并伴随砷等重金属的排放,这些物质通过空气、水和土壤进入环境。此外,金属材料在海水环境下腐蚀并释放金属离子,可能对海洋生物造成影响[34-35];环氧树脂在合成过程中会释放卤代烃、苯系物等有害物质,直接威胁从业人员和周围居民的健康。
ReCipe 2016中点法特征化与标准化结果分别如表10图3(b)所示,结果同样表明原材料获取阶段对各个环境影响类别有着最高的贡献,其中陆地生态毒性、淡水生态毒性、海洋生态毒性、人类致癌毒性以及人类非致癌毒性的影响较大。海洋生态毒性的影响明显高于其他部分,与上述分析相似,是由于金属材料在海水环境下易发生腐蚀并产生金属离子,进而间接或直接地影响海洋环境。淡水生态毒性较高的原因是铜、硅钢片、环氧树脂的生产过程中会有大量工业废水直接排入淡水系统,并且环氧树脂合成的有机污染物会严重影响淡水环境。表11展示了ReCipe 2016终点法特征化结果,将环境损害类别分成人体健康、生态系统损耗、资源损耗。从表11可以看出,原材料获取阶段同样在3种影响类别中有着最大的占比,这也与铜、硅钢片以及环氧树脂的使用有关。以上分析均表明,需要优化金属材料的使用率与回收率,并且使用可降解循环利用的环氧树脂,以有效减弱对环境的影响。
现有研究常分割碳足迹与环境影响[16],且材料的碳贡献模糊[21]。而本文既量化铜、硅钢片和环氧树脂的碳占比,又关联回收的减排效应,结合两种评价方法明确环境影响机制,为制造端提供精准优化依据。
本文基于LCA方法,聚焦于材料角度建立了环氧浇注干式变压器的碳足迹与环境影响评估模型,量化了变压器全生命周期各阶段以及主要材料的碳足迹,并利用蒙特卡洛模拟方法评估了变压器碳足迹的不确定性,最后基于CML-IA baseline与ReCipe 2016两种评价方法,对不同生命周期阶段的环境影响程度进行了综合评估,主要结论如下:
(1)该变压器全生命周期总碳足迹为8 996.25 kgCO2e;原材料获取阶段是核心贡献源,达到7 186.51 kgCO2e,铜、硅钢片、环氧树脂为关键碳源;产品生产阶段碳排放均由消耗的电能产生,为3 609.72 kgCO2e;废弃物处理阶段因铜、硅钢片回收呈-1 799.98 kgCO2e的负碳排放。
(2)Sobol序列法与三角分布所得结果均贴合实际,但Sobol法序列不确定性表达更充分,且明确环氧树脂、电力消耗的一阶敏感性指数分别为0.460、0.499,是碳足迹关键影响变量,与前期灵敏度分析结论一致。
(3)CML-IA baseline与 ReCiPe 2016验证结果表明,原材料获取阶段主导所有环境损害,其影响源于铜、硅钢片生产时的资源消耗与重金属排放,以及环氧树脂合成的有机污染物释放。

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2026年第59卷第3期
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doi: 10.16790/j.cnki.1009-9239.im.2026.03.002
  • 接收时间:2025-07-13
  • 首发时间:2026-09-10
  • 出版时间:2026-03-20
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  • 收稿日期:2025-07-13
  • 修回日期:2025-08-25
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    1湖北工业大学 新能源及电网装备安全监测湖北省工程研究中心,湖北 武汉 430068
    2南方电网科学研究院有限责任公司,广东 广州 510663

通讯作者:

张晓星(1972-),男(汉族),湖北潜江人,教授,主要从事气体绝缘设备在线检测与故障诊断以及环保型绝缘气体应用技术的研究。
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2种不同金属材料的力学参数

Family
属数
Number of
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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