基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究

邵鹏; 徐鹏博; 于志强; 薛凯旋; 李泽昆; 王雨竹

doi:10.19912/j.0254-0096.tynxb.2025-0703

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究

更新时间：2026-10-15

- 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究
- 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究
- 太阳能学报 2026年47卷第9期页码：260-268
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.19912/j.0254-0096.tynxb.2025-0703
  中图分类号： X758
- 网络首发：2026-10-10，
  
  纸质出版：2026
- 稿件说明：
移动端阅览
邵鹏, 徐鹏博, 于志强, 等. 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究[J]. 太阳能学报, 2026,47(9):260-268.

邵鹏, 徐鹏博, 于志强, et al. 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究[J]. 2026, 47(9): 260-268.
邵鹏, 徐鹏博, 于志强, 等. 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究[J]. 太阳能学报, 2026,47(9):260-268. DOI： 10.19912/j.0254-0096.tynxb.2025-0703.

邵鹏, 徐鹏博, 于志强, et al. 基于LCA-LEAP模型的单晶硅片生产过程碳排放及其减排潜力研究[J]. 2026, 47(9): 260-268. DOI： 10.19912/j.0254-0096.tynxb.2025-0703.

摘要

为评估光伏产品制造环节对环境的影响

该文采用生命周期评价（LCA）方法对生产1 kg单晶硅片进行碳排放的量化分析

包括贡献性分析、敏感性分析、改进分析和能量回收期分析。计算发现生产1 kg单晶硅片共排放397.6 kg（该文碳排放均以CO2计）。贡献性分析表明

单晶硅棒和切片生产碳排放最大

占比58.22%;多晶硅提纯次之

占比32.63%;工业硅冶炼碳排放最小

占比9.15%。敏感性分析表明

电力是影响整个环节碳排放最敏感的因素

敏感度高达37.66%。改进分析表明

使用可再生能源电力是显著的减排措施

将减少149.84 kg的碳排放。通过数据分析得出1 kg单晶硅片能量回收期为3.35 a。最后使用长期能源替代规划系统（LEAP）预测2025—2030年多种单一情景及其综合情景下生产1 kg单晶硅片的碳排放情况

发现以技术与能源结构减排相结合的潜力为最高

随后是能源结构减排情景

技术减排情景的潜力则相对最低。

Abstract

In order to evaluate the environmental impact of photovoltaic product manufacturing

the carbon emissions attributable to the production of 1 kg of monocrystalline silicon wafers were estimated using a life cycle assessment （LCA） methodology

including contribution analysis

sensitivity analysis

improvement analysis and energy payback period analysis. It is calculated that the production of 1 kg of monocrystalline silicon wafers emits a total of 397.6 kg（in this paper

carbon emissions are measured in carbon dioxide）. The contribution analysis showed that the CO emission of monocrystalline silicon rods and wafers was the largest

accounting for 58.22%; polysilicon purification was the second

accounting for 32.63%; industrial silicon smelting has the smallest CO emissions

accounting for 9.15%. Sensitivity analysis shows that electricity is the most sensitive factor affecting the carbon emissions of the entire process

with a sensitivity of 37.66%. The improvement analysis shows that the use of renewable electricity is a significant emission reduction measure

which will reduce carbon emissions by 149.84 kg. Through data analysis

the energy payback period of 1kg monocrystalline silicon wafer is 3.35 years. Finally

the long-range energy alternatives planning system （LEAP） is used to predict the carbon emissions of 1 kg monocrystalline silicon wafer production under multiple single scenarios and their comprehensive scenarios from 2025 to 2030

and it is found that the potential of combining technology and energy structure emission reduction is the highest

followed by the energy structure emission reduction scenario

and the potential of the technology emission reduction scenario is the lowest.

关键词

Keywords

references

Peng J Q, Lu L, Yang H X.Review on life cycle assessment of energy payback and greenhouse gas emission of solar photovoltaic systems[J]. Renewable and Sustainable Energy Reviews, 2013, 19: 255-274.

Liu F Y, Zeng Q, Li J J, et al.Emerging inorganic compound thin film photovoltaic materials: Progress, challenges and strategies[J]. Materials Today, 2020, 41: 120-142.

Olaleru S A, Kirui J K,Wamwangi D, et al.Perovskite solar cells: The new epoch in photovoltaics[J]. Solar Energy, 2020, 196: 295-309.

Heidari S M, Anctil A.Country-specific carbon footprint and cumulative energy demand of metallurgical grade silicon production for silicon photovoltaics[J]. Resources, Conservation and Recycling, 2022, 180: 106171.

Stylos N,Koroneos C.Carbon footprint of polycrystalline photovoltaic systems[J]. Journal of Cleaner Production, 2014, 64: 639-645.

Yang D, Liu J R, Yang J X, et al.Life-cycle assessment of China’s multi-crystalline silicon photovoltaic modules considering international trade[J]. Journal of Cleaner Production, 2015, 94: 35-45.

Sumper A, Robledo-García M,Villafáfila-Robles R, et al.Life-cycle assessment of a photovoltaic system in Catalonia (Spain)[J]. Renewable and Sustainable Energy Reviews, 2011, 15(8): 3888-3896.

Fu Y Y, Liu X, Yuan Z W.Life-cycle assessment of multi-crystalline photovoltaic (PV) systems in China[J]. Journal of Cleaner Production, 2015, 86: 180-190.

Hou G F, Sun H H, Jiang Z Y, et al.Life cycle assessment of grid-connected photovoltaic power generation from crystalline silicon solar modules in China[J]. Applied Energy, 2016, 164: 882-890.

Tao M,Fthenakis V, Ebin B, et al.Major challenges and opportunities in silicon solar module recycling[J]. Progress in Photovoltaics: Research and Applications, 2020, 28(10): 1077-1088.

Lim M S W, He D, Tiong J S M, et al. Experimental, economic and life cycle assessments of recycling end-of-life monocrystalline silicon photovoltaic modules[J]. Journal of Cleaner Production, 2022, 340: 130796.

傅银银. 中国多晶硅光伏系统生命周期评价[D]. 南京:南京大学, 2013.

李鹞,于随然. 中国光伏系统的生命周期评价[J]. 环境工程, 2014, 32(10): 119-124.

谢明辉,阮久莉,白璐,等. 太阳能级多晶硅生命周期环境影响评价[J]. 环境科学研究, 2015, 28(2): 291-296.

李兴盛,胡向然,郑淞生,等. 基于多晶硅金刚线切割工艺的光伏生命周期分析[J]. 太阳能学报, 2022, 43(3): 147-151.

Miao A K, Yuan Y, Wu H, et al.Pathway for China’s provincial carbon emission peak: a case study of the Jiangsu Province[J]. Energy, 2024, 298: 131417.

王君,解晓燕,刘文君,等. 多情景模拟的山东省交通运输碳达峰及减排潜力分析[J]. 环境污染与防治, 2026, 48(1): 140-147.

Balaras C A, Dascalaki E G, Patsioti M, et al.Carbon and greenhouse gas emissions from electricity consumption in European union buildings[J]. Buildings, 2024, 14(1): 71.

把哈尔古丽·帕塔尔, 张旭龙, 陈宁. 基于基础情景的新疆建筑领域碳排放预测方法研究[J]. 施工技术(中英文), 2024, 53(5): 139-145.

Zeng S Z, Gu J X, Peng X D.Low-carbon cities comprehensive evaluation method based on Fermatean fuzzy hybrid distance measure and TOPSIS[J]. Artificial Intelligence Review, 2023, 56(8): 8591-8607.

邢红. 碳达峰背景下江苏省能源需求影响因素及预测分析[J]. 数学的实践与认识, 2024, 54(2): 59-73.

O’Ryan R, Nasirov S, Osorio H. Assessment of the potential impacts of a carbon tax in Chile using dynamic CGE model[J]. Journal of Cleaner Production, 2023, 403: 136694.

柴麒敏. 美丽中国愿景下我国碳达峰、碳中和战略的实施路径研究[J]. 环境保护, 2022, 50(6): 21-25.

Susmaga R,Szczęch I, Brzezinski D.Towards explainable TOPSIS: Visual insights into the effects of weights and aggregations on rankings[J]. Applied Soft Computing, 2024, 153: 111279.

陆保一,明庆忠,史鹏飞,等. 基于DPSIR-SBM框架的旅游生态安全时空动态及影响路径:以云南省为例[J]. 地理与地理信息科学, 2023, 39(6): 134-142.

孙湫娟. “双碳”背景下中国钢铁行业二氧化碳排放情景模拟及减排路径研究[D]. 南昌:江西财经大学, 2023.

李姗姗,马雨晴,孔维龄,等. 基于LEAP模型的安徽省能源需求与碳排放预测[J]. 环境科学, 2025, 46(8): 4911-4922.

Zhao H L, Liu F, Liu H Q, et al.Comparative life cycle assessment of two ceramsite production technologies for reusing municipal solid waste incinerator fly ash in China[J]. Waste Management, 2020, 113: 447-455.

韩海忠,杨凤玲,孔卉茹,等. 生物质型煤与褐煤的生命周期评价对比研究[J]. 洁净煤技术, 2016, 22(2): 89-95, 101.

王姿怡. 光伏系统生命周期能效评价及应用规划研究[D]. 济南:山东大学, 2023.

Fan M Y, Yu Z Q, Ma W H, et al.Life cycle assessment of crystalline silicon wafers for photovoltaic power generation[J]. Silicon, 2021, 13(9): 3177-3189.

何津津. 基于生命周期评价的光伏发电碳排放研究[D]. 南京:南京航空航天大学, 2017.

Jiang K Z, Chen Z J, Ma W H.Research on LCA data and environmental impact of industrial silicon smelting and high purity crystal silicon purification[J]. Silicon, 2024, 16(2): 573-583.

庄园,温金城,卞与良,等. 晶体硅和钙钛矿光伏组件碳足迹研究[J]. 太阳能学报, 2023, 44(12): 41-46.

岳海霏. 工信部修订光伏制造行业规范条件[J]. 科技中国, 2015(4): 38-39.

刁周玮,石磊. 中国光伏电池组件的生命周期评价[J]. 环境科学研究, 2011, 24(5): 571-579.

于志强. 冶金法多晶硅及其光伏系统并网发电的生命周期评价研究[D]. 昆明:昆明理工大学, 2017.

Huang B J, Zhao J, Chai J Y, et al.Environmental influence assessment of China’s multi-crystalline silicon (multi-Si) photovoltaic modules considering recycling process[J]. Solar Energy, 2017, 143: 132-141.

单彤文,宋鹏飞,李又武,等. 制氢、储运和加注全产业链氢气成本分析[J]. 天然气化工(C1化学与化工), 2020, 45(1): 85-90, 96.

Yu Z Q, Ma W H, Xie K Q, et al.Life cycle assessment of grid-connected power generation from metallurgical route multi-crystalline silicon photovoltaic system in China[J]. Applied Energy, 2017, 185: 68-81.

Yang S Q, Yu Z Q, Ma W H, et al.Research on carbon emission of solar grade polysilicon produced by metallurgical route using digital simulation technology[J]. Silicon, 2023, 15(15): 6567-6578.

Yang Y C, Ma L, Ma W H, et al.Life cycle assessment of typical tower solar thermal power station in China[J]. Energy, 2024, 309: 133154.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

单晶硅光伏系统全生命周期评价

面向低碳目标的数据中心与含新能源电-水耦合系统联合规划

面向资源集群调控的园区共享储能分布鲁棒优化配置方法

计及绿证交易电网与区域映射的碳排放核算分析方法

电网调度视角下碳交易与低碳评价关键技术研究