Article(id=1154429041470854056, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1154429037721146272, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1656777600000, receivedDateStr=2022-07-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1753166931740, onlineDateStr=2025-07-22, pubDate=1710864000000, pubDateStr=2024-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753166931740, onlineIssueDateStr=2025-07-22, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753166931740, creator=13701087609, updateTime=1753166931740, updator=13701087609, issue=Issue{id=1154429037721146272, tenantId=1146029695717560320, journalId=1146119893612605453, year='2024', volume='42', issue='3', pageStart='284', pageEnd='426', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1753166930847, creator=13701087609, updateTime=1753694626061, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1156642351918469663, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1154429037721146272, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1156642351918469664, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1154429037721146272, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=284, endPage=292, ext={EN=ArticleExt(id=1154429041869312937, articleId=1154429041470854056, tenantId=1146029695717560320, journalId=1146119893612605453, language=EN, title=Research progress on optimization of fuel ethanol refining system and carbon emission reduction, columnId=null, journalTitle=Renewable Energy Resources, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Biomass is a rich and renewable carbon source. The efficient production of fuel ethanol with sugar, starch, straw cellulose or other biomass feedstocks can reduce the demand for fossil energy, among which the second generation fuel ethanol with lignocellulose as feedstock has broad prospects for development. Compared with fossil energy, fuel ethanol has the advantages of environmental protection, economy and renewable energy, but its production technology, economic benefits and environmental impact still need to be further studied. In recent years, through the optimization of fuel ethanol refining system and the study of the whole life cycle analysis, the progress of fuel ethanol technology has been effectively promoted, and the related research on carbon emission reduction of fuel ethanol has been promoted. This paper mainly discussed the development of fuel ethanol production technology in recent years, focused on the research progress of simulation optimization and carbon emission reduction of fuel ethanol system, and looked forward to the development trend of fuel ethanol, in order to provide reference for the sustainable development of fuel ethanol.

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生物质是丰富可再生的碳源,以糖、淀粉、秸秆纤维素或其他生物质原料高效生产燃料乙醇,可减少化石能源的需求,其中以木质纤维素为原料的第二代燃料乙醇具有广阔的发展前景。与化石能源相比,燃料乙醇具有环保、经济、可再生的优势,但其在生产工艺技术、经济效益和环境影响等方面仍需要深入研究。近年来,通过开展燃料乙醇炼制系统优化及全生命周期分析研究,有力地促进了燃料乙醇技术进步,推动了燃料乙醇碳减排相关研究。文章主要论述了近年来燃料乙醇生产技术的发展,重点对燃料乙醇系统的模拟优化和碳减排研究进展进行了总结,并对燃料乙醇发展趋势进行了展望,以期为燃料乙醇的可持续发展提供参考。

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常春(1973-),男,博士,教授,研究方向为生物质资源转化与利用。E-mail:
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燃料乙醇类型 主要原料 转化工艺 特点 文献
1G 含糖基和淀粉基的作物 (如甘蔗、玉米、甜菜等) 水解、发酵、蒸馏 生产工艺成熟且已实现商业化规模, 存在与人争粮的问题 [ 3 ]
2G 木质纤维素生物质 (Lignocellulosic Biomass, LCB) (森林树木、农业废弃物、林业废弃 物、工业和生活废弃物、能源作物等) 预处理、水解、 糖化发酵、蒸馏 原料来源广泛、价格低廉、不与人争粮,绿色可 持续, 但存在成本高、工艺路线 复杂等问题 [ 4, 5 ]
3G 藻类[单细胞(如微藻类)或 多细胞(如大型藻类) 水解、发酵、蒸馏 具有光合效率高、生产周期短、可吸收大气中 ${\mathrm{{CO}}}_{2}$ 等显著优势,但会使海洋富营养化,在转 化技术、生态和经济等方面具有挑战 [ 6 ]
4G 转基因植物和微生物 (如转基因微藻) 发酵或水解 复杂成本高, ${\mathrm{{CO}}}_{2}$ 固定中等,不适合大规模 生产 [ 7, 8 ]
), ArticleFig(id=1154429047271576556, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154429041470854056, language=CN, label=表 1, caption=四代不同燃料乙醇所用原料, figureFileSmall=null, figureFileBig=null, tableContent=
燃料乙醇类型 主要原料 转化工艺 特点 文献
1G 含糖基和淀粉基的作物 (如甘蔗、玉米、甜菜等) 水解、发酵、蒸馏 生产工艺成熟且已实现商业化规模, 存在与人争粮的问题 [ 3 ]
2G 木质纤维素生物质 (Lignocellulosic Biomass, LCB) (森林树木、农业废弃物、林业废弃 物、工业和生活废弃物、能源作物等) 预处理、水解、 糖化发酵、蒸馏 原料来源广泛、价格低廉、不与人争粮,绿色可 持续, 但存在成本高、工艺路线 复杂等问题 [ 4, 5 ]
3G 藻类[单细胞(如微藻类)或 多细胞(如大型藻类) 水解、发酵、蒸馏 具有光合效率高、生产周期短、可吸收大气中 ${\mathrm{{CO}}}_{2}$ 等显著优势,但会使海洋富营养化,在转 化技术、生态和经济等方面具有挑战 [ 6 ]
4G 转基因植物和微生物 (如转基因微藻) 发酵或水解 复杂成本高, ${\mathrm{{CO}}}_{2}$ 固定中等,不适合大规模 生产 [ 7, 8 ]
), ArticleFig(id=1154429047317713901, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154429041470854056, language=EN, label=Table 2, caption=Pretreatment technology, figureFileSmall=null, figureFileBig=null, tableContent=
预处理类型 方法 作用机理 特点 文献
物理法 机械粉碎、微波处理、热解、辐照、超 声法、球磨法等 增加木质纤维素对酶可及 性、减小颗粒尺寸、降低纤 维素结晶度或破坏木质纤 维素的顽抗结构 操作简单、污染较小,但能耗大、成本 高,经济可行性低 [ 11 , 12 ]
化学法 酸法(液体酸和固体酸)、碱法[如稀 碱(Dilute Alkali, DAH)]、有机溶剂 (Organic Solvent , OS) , ILs、 氧化处理、DESs 和 CELF 等 利用化学试剂,对木质纤维 素中的一种或几种化学成 分进行有效解聚, 降低纤维 素的结晶度和聚合度 反应效率高、操作时间短,但存在腐 蚀设备、用水量大等问题,其中 ILs 有较好的热稳定性和化学稳定性. 但成本较高, 有待进一步研究 [ 12 ]
物理化学法 HTP、蒸汽爆破处理(Steam Explosion Treatment, SE)、氨纤维爆 破(Ammonia Fiber Explosion , AFEX)、CO2爆破法等 破坏木质纤维素结构, 提高 生物可降解性 处理时间短、耗能较低,但成本较高 [ 12 ]
生物法 利用白腐菌、褐腐菌、软腐菌等微生 物或木质素降解过氧化物酶、锰过 氧化物酶和漆酶等选择性降解 木质素和半纤维素 产生降解性的酶,从而将 纤维素和半纤维素 转化成可发酵糖 具有能耗低、成本低、反应条件温和、 环境友好以及预处理过程不产生后 期单糖发酵抑制物等优点, 但水解 特异性差,预处理周期长 [ 13 ]
), ArticleFig(id=1154429047447737326, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154429041470854056, language=CN, label=表 2, caption=预处理技术, figureFileSmall=null, figureFileBig=null, tableContent=
预处理类型 方法 作用机理 特点 文献
物理法 机械粉碎、微波处理、热解、辐照、超 声法、球磨法等 增加木质纤维素对酶可及 性、减小颗粒尺寸、降低纤 维素结晶度或破坏木质纤 维素的顽抗结构 操作简单、污染较小,但能耗大、成本 高,经济可行性低 [ 11 , 12 ]
化学法 酸法(液体酸和固体酸)、碱法[如稀 碱(Dilute Alkali, DAH)]、有机溶剂 (Organic Solvent , OS) , ILs、 氧化处理、DESs 和 CELF 等 利用化学试剂,对木质纤维 素中的一种或几种化学成 分进行有效解聚, 降低纤维 素的结晶度和聚合度 反应效率高、操作时间短,但存在腐 蚀设备、用水量大等问题,其中 ILs 有较好的热稳定性和化学稳定性. 但成本较高, 有待进一步研究 [ 12 ]
物理化学法 HTP、蒸汽爆破处理(Steam Explosion Treatment, SE)、氨纤维爆 破(Ammonia Fiber Explosion , AFEX)、CO2爆破法等 破坏木质纤维素结构, 提高 生物可降解性 处理时间短、耗能较低,但成本较高 [ 12 ]
生物法 利用白腐菌、褐腐菌、软腐菌等微生 物或木质素降解过氧化物酶、锰过 氧化物酶和漆酶等选择性降解 木质素和半纤维素 产生降解性的酶,从而将 纤维素和半纤维素 转化成可发酵糖 具有能耗低、成本低、反应条件温和、 环境友好以及预处理过程不产生后 期单糖发酵抑制物等优点, 但水解 特异性差,预处理周期长 [ 13 ]
), ArticleFig(id=1154429047498068975, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154429041470854056, language=EN, label=Table 3, caption=Carbon reduction analysis of cellulosic ethanol from different raw materials, figureFileSmall=null, figureFileBig=null, tableContent=
生产原料 生产工艺 模型/方法 结果 文献
玉米秸秆、柳 枝稷和芒草 生化转化生产乙醇 GREET 模型 与传统汽油相比,芒草乙醇减排 GHG 的效果 最好,其余依次是玉米秸秆、柳枝稷乙醇 [ 33 ]
木薯秸秆 预处理、酶解、液化、 发酵和同时糖化发酵 (SSF) GaBi v8.7 模型 以纤维素 C5 糖为原料的木薯秸秆乙醇工艺性 能较好,其净能量比、可再生性和 GWP 分别为 ${0.94},{1.09}\mathrm{\;{kg}}$${2929}\mathrm{\;{kg}}$ [ 38 ]
芒草 预处理、水解、发酵、产品 提纯 $\text{、}{\mathrm{{CO}}}_{2}$ 压缩、运输和 注入 采用 ecoinvent 数据库, openLCA 模型 有助于减少交通领域的 GHG 排放,减少潜力 为 104%~138% [ 37 ]
玉米籽粒 $n$ 厂成熟纤维技术 GREET 模型 燃料乙醇全生命周期的 GHG 排放 (36~39 g/MJ)比汽油 (约 94 g/MJ )减少 60% [ 39 ]
芒草 预处理、糖化发酵、产品 提纯、废水处理、燃烧发电 ReCiPe 模型 芒草乙醇在交通运输领域具有减少 GHG 排放的潜力 [ 34 ]
玉米秸秆 生物化学转化制取燃料 乙醇 Gabi 模型 与汽油相比,燃料乙醇具有良好的环境表现 [ 35 ]
高粱 ILs 预处理、酶糖化和发酵 SuperPro Designer 模型 使用 CCS 技术,高粱乙醇具有减少约 70% GHG 排放的潜力, ${\mathrm{{CO}}}_{2}$ 减排量为 102 万 $\mathrm{t}/\mathrm{a}$ [ 36 ]
玉米芯 EXA(乙醇、木糖、胶粘剂) 生物炼制工艺 同时结合 WebLCA, Gabi, GREET 2018 模型 乙醇的全生命周期碳强度可达到 ${37.78}\mathrm{\;g}/\mathrm{{MJ}}$ . 与汽油 $\left( {{90.20}\mathrm{\;g}/\mathrm{{MJ}}}\right)$ 相比,温室气体减少 ${60}\%$ [ 40 ]
芒草、柳枝稷、 巨型芦苇、芦 苇金丝雀草、 刺菜蓟、杨树、 柳树和桉树 SE 预处理、酶水解、 SSF 法发酵 欧盟可再生能源指令 (RED II)的碳足迹方法 所有供应链均符合 RED II GHG 减排 65%的 要求, 利用来源于边际性土地的能源作物 生产的燃料乙醇可以减少 ${\mathrm{{CO}}}_{2}$ 排放 [ 41 ]
), ArticleFig(id=1154429047552594928, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154429041470854056, language=CN, label=表 3, caption=不同原料纤维乙醇碳减排分析, figureFileSmall=null, figureFileBig=null, tableContent=
生产原料 生产工艺 模型/方法 结果 文献
玉米秸秆、柳 枝稷和芒草 生化转化生产乙醇 GREET 模型 与传统汽油相比,芒草乙醇减排 GHG 的效果 最好,其余依次是玉米秸秆、柳枝稷乙醇 [ 33 ]
木薯秸秆 预处理、酶解、液化、 发酵和同时糖化发酵 (SSF) GaBi v8.7 模型 以纤维素 C5 糖为原料的木薯秸秆乙醇工艺性 能较好,其净能量比、可再生性和 GWP 分别为 ${0.94},{1.09}\mathrm{\;{kg}}$${2929}\mathrm{\;{kg}}$ [ 38 ]
芒草 预处理、水解、发酵、产品 提纯 $\text{、}{\mathrm{{CO}}}_{2}$ 压缩、运输和 注入 采用 ecoinvent 数据库, openLCA 模型 有助于减少交通领域的 GHG 排放,减少潜力 为 104%~138% [ 37 ]
玉米籽粒 $n$ 厂成熟纤维技术 GREET 模型 燃料乙醇全生命周期的 GHG 排放 (36~39 g/MJ)比汽油 (约 94 g/MJ )减少 60% [ 39 ]
芒草 预处理、糖化发酵、产品 提纯、废水处理、燃烧发电 ReCiPe 模型 芒草乙醇在交通运输领域具有减少 GHG 排放的潜力 [ 34 ]
玉米秸秆 生物化学转化制取燃料 乙醇 Gabi 模型 与汽油相比,燃料乙醇具有良好的环境表现 [ 35 ]
高粱 ILs 预处理、酶糖化和发酵 SuperPro Designer 模型 使用 CCS 技术,高粱乙醇具有减少约 70% GHG 排放的潜力, ${\mathrm{{CO}}}_{2}$ 减排量为 102 万 $\mathrm{t}/\mathrm{a}$ [ 36 ]
玉米芯 EXA(乙醇、木糖、胶粘剂) 生物炼制工艺 同时结合 WebLCA, Gabi, GREET 2018 模型 乙醇的全生命周期碳强度可达到 ${37.78}\mathrm{\;g}/\mathrm{{MJ}}$ . 与汽油 $\left( {{90.20}\mathrm{\;g}/\mathrm{{MJ}}}\right)$ 相比,温室气体减少 ${60}\%$ [ 40 ]
芒草、柳枝稷、 巨型芦苇、芦 苇金丝雀草、 刺菜蓟、杨树、 柳树和桉树 SE 预处理、酶水解、 SSF 法发酵 欧盟可再生能源指令 (RED II)的碳足迹方法 所有供应链均符合 RED II GHG 减排 65%的 要求, 利用来源于边际性土地的能源作物 生产的燃料乙醇可以减少 ${\mathrm{{CO}}}_{2}$ 排放 [ 41 ]
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燃料乙醇炼制系统优化与碳减排研究进展
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张欢欢 1 , 王圆圆 1 , 阎振丽 2 , 杜朝军 3 , 赵子高 2 , 陈玉洁 3 , 常春 1, 4
可再生能源 | 2024,42(3): 284-292
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可再生能源 | 2024, 42(3): 284-292
燃料乙醇炼制系统优化与碳减排研究进展
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张欢欢1, 王圆圆1, 阎振丽2, 杜朝军3, 赵子高2, 陈玉洁3, 常春1, 4
作者信息
  • 1 郑州大学 化工学院 河南 郑州 450001
  • 2 车用生物燃料技术国家重点实验室 南阳 473000
  • 3 南阳理工学院 郑州大学南阳研究院 南阳 473004
  • 4 河南省杰出外籍科学家工作室 河南 郑州 450001

通讯作者:

常春(1973-),男,博士,教授,研究方向为生物质资源转化与利用。E-mail:
Research progress on optimization of fuel ethanol refining system and carbon emission reduction
Huanhuan Zhang1, Yuanyuan Wang1, Zhenli Yan2, Chaojun Du3, Zigao Zhao2, Yujie Chen3, Chun Chang1, 4
Affiliations
  • 1 School of Chemical Engineering Zhengzhou University Zhengzhou 450001 China
  • 2 State Key Laboratory of Moto Vehicle Biofuel Technology Nanyang 473000 China
  • 3 Nanyang Research Institute of Zhengzhou University Nanyang Institute of Technology Nanyang 473004 China
  • 4 Henan Center for Outstanding Overseas Scientists Zhengzhou 450001 China
出版时间: 2024-03-20
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生物质是丰富可再生的碳源,以糖、淀粉、秸秆纤维素或其他生物质原料高效生产燃料乙醇,可减少化石能源的需求,其中以木质纤维素为原料的第二代燃料乙醇具有广阔的发展前景。与化石能源相比,燃料乙醇具有环保、经济、可再生的优势,但其在生产工艺技术、经济效益和环境影响等方面仍需要深入研究。近年来,通过开展燃料乙醇炼制系统优化及全生命周期分析研究,有力地促进了燃料乙醇技术进步,推动了燃料乙醇碳减排相关研究。文章主要论述了近年来燃料乙醇生产技术的发展,重点对燃料乙醇系统的模拟优化和碳减排研究进展进行了总结,并对燃料乙醇发展趋势进行了展望,以期为燃料乙醇的可持续发展提供参考。

燃料乙醇  /  生物质  /  碳排放  /  生命周期分析

Biomass is a rich and renewable carbon source. The efficient production of fuel ethanol with sugar, starch, straw cellulose or other biomass feedstocks can reduce the demand for fossil energy, among which the second generation fuel ethanol with lignocellulose as feedstock has broad prospects for development. Compared with fossil energy, fuel ethanol has the advantages of environmental protection, economy and renewable energy, but its production technology, economic benefits and environmental impact still need to be further studied. In recent years, through the optimization of fuel ethanol refining system and the study of the whole life cycle analysis, the progress of fuel ethanol technology has been effectively promoted, and the related research on carbon emission reduction of fuel ethanol has been promoted. This paper mainly discussed the development of fuel ethanol production technology in recent years, focused on the research progress of simulation optimization and carbon emission reduction of fuel ethanol system, and looked forward to the development trend of fuel ethanol, in order to provide reference for the sustainable development of fuel ethanol.

fuel ethanol  /  biomass  /  carbon emissions  /  life cycle analysis
张欢欢, 王圆圆, 阎振丽, 杜朝军, 赵子高, 陈玉洁, 常春. 燃料乙醇炼制系统优化与碳减排研究进展. 可再生能源, 2024 , 42 (3) : 284 -292 .
Huanhuan Zhang, Yuanyuan Wang, Zhenli Yan, Chaojun Du, Zigao Zhao, Yujie Chen, Chun Chang. Research progress on optimization of fuel ethanol refining system and carbon emission reduction[J]. Renewable Energy Resources, 2024 , 42 (3) : 284 -292 .
化石能源的消耗以及由其引发的碳排放问题正迫使人们寻求新的可再生能源。作为绿色生物燃料,燃料乙醇一直备受关注。燃料乙醇是指体积浓度达到 99.5%以上的无水乙醇,可补充替代化石能源,减少温室气体和污染物的排放。据统计, 2020 年全球燃料乙醇总产量为 986.44 亿 L, 混配出的乙醇汽油超过同期全球车用汽油消耗总量的 60%。美国是全球第一大燃料乙醇生产国和乙醇汽油消费国, 其燃料乙醇年产量占世界总产量的 53%,其次是巴西和中国 [ 1 ] 。我国力争到 2025 年实现纤维素燃料乙醇规模化生产,实现 ${\mathrm{{CO}}}_{2}$ 减排 37%,并计划到 2030 年减排 43% [ 2 ] ,2060 年实现 “碳中和”。
在“双碳”目标下, 大力发展生物燃料乙醇是我国长期的能源战略。但是,燃料乙醇生产工艺具有流程复杂、技术集成度低、成本高等问题,而且生产和使用燃料乙醇过程中可能会在臭氧层破坏、酸化、富营养化等方面对环境产生一定影响。 因此,全面分析燃料乙醇生物炼制技术,优化燃料乙醇炼制系统, 开展燃料乙醇全生命周期分析, 有助于客观评价燃料乙醇技术的经济可行性和对环境的影响,促进燃料乙醇炼制技术的进步和创新。
典型的燃料乙醇生产工艺主要由预处理、酶解、发酵、精馏、废醪液处理及副产品利用等单元组成。目前,以粮食为原料的燃料乙醇已实现了大规模生产,但如何进一步降低生产成本,实现以纤维素为原料的燃料乙醇商业化仍面临诸多挑战, 如纤维素酶价格高、乙醇收率较低、原料预处理和乙醇精馏过程能耗大、废水处理会增加环境成本等。需要指出的是, 在燃料乙醇生产过程中, 在得到目标产品的同时, 还会产生木质素、酒糟等高附加价值副产物, 将这些副产物增值利用可以增加收益, 有效抵偿燃料乙醇的生产成本, 提高经济性。
根据生产原料的不同,将燃料乙醇分为四代 $\left({1\mathrm{G},2\mathrm{G},3\mathrm{G}\text{和}4\mathrm{G}}\right)$ ,四代不同燃料乙醇所用原料、转化工艺及特点如 表 1 所示。其中, 第二代 (2G)燃料乙醇是本文论述的对象。
近年来,除了传统预处理方法的组合外[如稀酸(Dilute Acid, DA)与水热预处理(Hydrothermal Pretreatment, HTP) 组合等], 研究报道了一些新颖的预处理方法, 如离子液体 (Ionic liquids, ILs) 预处理、 $\gamma$ -戊内酯 ( $\gamma$ -valerolactone, GVL) 预处理、低共熔溶剂或称深度共熔溶剂(Deep Eutectic Solvents, DESs)预处理、共溶剂增强木质纤维素分馏 (Co-solvent Enhanced Lignocellulosic Fractionation, CELF) 预处理、氨浸 (Extractive Ammonia, EA) 预处理、微生物联合体生态位预处理 [ 9 , 10 ] 。这些方法能更有效地实现纤维素、半纤维素和木质素的分离, 同时具有绿色经济、安全高效和环境友好的特点, 有助于后续纤维素酶的选择、酶解工艺优化和酶解机理研究等。此外,固体酸催化剂(如碳基固体酸)具有选择性高、环保等优点,也被应用于 LCB 预处理过程中。一些预处理技术汇总如 表 2 所示。
生物质类型、组成和预处理条件对生物炼制系统的设计和规模扩大有重要影响,如:甘蔗渣用 SE 预处理, 纤维中 C6 糖的回收率和液体中 C5 糖的回收率均较高; 经氨溶液预处理的玉米秸秆已被证明有较高的糖产量 [ 14 ] ;青霉菌能够有效降解 LCB,添加 0.3%的青霉菌可提高漆酶的活性, 同时提高秸秆中木质纤维素的降解率 [ 15 ] 。因此,应根据生物质原料的物理化学性质, 选择合适的预处理方法、组合现有的预处理方式或开发一种通用的预处理方法来高值化利用不同的生物质, 以促进生物燃料和增值产品的大规模生产。
水解糖化分为酸水解与酶水解; 发酵分为连续发酵、补料分批发酵和分批发酵。发酵过程与酶水解耦合。糖化发酵工艺分为 5 种:直接微生物转化(Direct Microbial Transformation, DMT)法[又称联合生物加工(Combined Biological Processing, CBP)法]、非等温同时糖化发酵 (Non-isothermal Simultaneous Saccharification Fermentation, NSSF) 法、分步水解发酵(Step by Step Hydrolysis Fermentation, SHF)法、同步糖化共发酵(Simultaneous Saccharification and Co-fermentation, SSCF) 法和同步糖化发酵(Simultaneous Saccharification and Fermentation, SSF)法 [ 16 ] 。其中, SHF 法发酵时间较长,所需设备多、投资大,能耗高,但乙醇产率高; 与 SHF 法相比, SSF 法成本低、周期短、效率高, 更具潜力, 但产物中的乙醇含量较低; SSCF 法利用基因工程,重组酵母,但菌种不易获得;CBP 法是乙醇和发酵酶共生,由于纤维素酶生产成本低, 可有效降低燃料乙醇的生产成本, 但 CBP 法的乙醇产量低,发酵时间长,开发菌种难度大 [ 17 ] 。此外, 还有采用固定化细胞技术进行发酵[ 18 ], 其设备利用率高, 可连续发酵, 且发酵周期短, 固定化细胞可反复使用,乙醇产率高、污染小,但固定化载体易结垢、易受杂菌污染。
酶解糖化与发酵过程中存在纤维素酶活性低、重复利用率低以及酶水解生产周期长致使成本增加等问题, 因此, 研制高效的酶制剂、设计新型反应器(如微流体反应器, 可提高生物乙醇的质量和产量 [ 19 ] )、将纤维素酶生产工艺与乙醇发酵工艺相结合是有效的解决措施, 可有效减少酶成本, 构建高效经济的糖平台, 进而推动纤维素燃料乙醇炼制系统的产业化进程 [ 20 ] 。Liu X 开发了一种无酶机械催化糖化工艺,将 ${\mathrm{P}}_{2}{\mathrm{O}}_{5}$ 与木质纤维素混合研磨,然后连续水解成可发酵糖,用 $\mathrm{{NaOH}}$ 中和水解产物, 得到磷酸钠 (作为一种营养, 可促进酵母生长和乙醇发酵)。因此,无酶机械催化工艺可能成为 LCB 酶解糖化工艺的一种有竞争力的替代方法, 并为生产燃料乙醇和充分利用整个生物质组分提供了可能 [ 21 ]
乙醇的蒸馏技术有很多,如简单双塔体系、三塔差压蒸馏体系、真空精馏体系、蒸汽再压缩体系、多效蒸馏体系、六塔试剂乙醇体系、精馏联合分子筛脱水、膜法渗透汽化技术等。在美国应用最广泛的 ICM(International Creative Management)工艺,即采用全负压的精馏方式, 将粗塔、精塔和汽提塔相结合, 供热可采用低品位蒸汽, 同时, 采用热耦合技术为热液化、精馏及蒸发供热 [ 22 , 23 ] 。此外,通过热耦合技术将余热综合利用,能够显著降低热能消耗,节省生产成本,提高综合效益。膜法渗透汽化技术也是一项节能技术。邓衍宏提出了继代晶种法合成 NaA 分子筛膜(具有重复性好、 通量高、选择性高和致密的优点) 技术, 该技术可对废弃的母液进行有效利用, 具有良好的环境及经济优势, 为膜法生物燃料乙醇的生产提供了技术支持 [ 24 ]
燃料乙醇炼制系统是一个具有多反应底物、 多反应类型(物理、化学、生化)、多物流和能流耦合的复杂反应系统。由于目前还没有成熟的商业化生产模式, 研究者多采用系统流程模拟的方法对其进行建模及优化。常用的流程模拟软件有 ProSim, PRO II, gPROMS, ChemCAD, SuperPro Designer 和 Aspen Plus 等。近年来, 许多研究者基于燃料乙醇炼制系统模拟方法, 尝试对燃料乙醇炼制系统进行优化, 并取得了重要的优化结果。
Silva R G D [ 25 ] 使用 Aspen Plus 软件模拟玉米秸秆生产燃料乙醇的生物炼制过程, 模拟了 DA, HTP, SE, AFEX 和 OS 等预处理方法对燃料乙醇炼制系统的影响, 模拟结果表明: DA 预处理方法可获得最高的乙醇转化率,但成本较高; AFEX 和 OS 预处理方法在低压蒸汽、中压蒸汽和冷却水等方面的消费成本最高, ${\mathrm{{CO}}}_{2}$ 排放量最高, 分别为78.8万 $\mathrm{t}/\mathrm{a}$ 和76.3万 $\mathrm{t}/\mathrm{a}$ ,而 $\mathrm{{SE}}$ 预处理方法的 ${\mathrm{{CO}}}_{2}$ 排放量为48.6万 $\mathrm{t}/\mathrm{a}$$\mathrm{{DA}}$ 预处理方法的经济利润为 3920 万 $\$/\mathrm{a},{\mathrm{{CO}}}_{2}$ 排放量为 8.4 万 $\mathrm{t}/\mathrm{a}$ ; AFEX 预处理方法的经济利润为1990万 $\$/\mathrm{a},{\mathrm{{CO}}}_{2}$ 排放量为 ${6.8}\mathrm{\;万}\mathrm{t}/\mathrm{a}$
Liu F [ 26 ] 研究了以 LCB 为原料,结合热和电生产乙醇和木糖的多联产系统,该多联产系统主要由预处理、木糖和乙醇生产、废水处理和热电联产 (Combined Heat and Power, CHP) 系统组成, 年处理能力约为 34 万 $\mathrm{t}$ 玉米芯,年产无水乙醇 4 万 $\mathrm{t}$ , 木糖晶体 5.16 万 $\mathrm{t}$ ,由于副产物木糖的价值较高, 该系统单位生物质原料的产值比其他系统高得多。刘芳 [ 27 ] 利用能量分析软件 Aspen Energy Analyzer 对 CHP 系统的用能情况进行了分析, 从 Aspen Plus 模型中提取冷、热流股,按照夹点理论的基本原则设计换热网络,结果表明,乙醇-木糖-热和电的生物炼制系统稳态模型的冷、热流股通过 10 个换热器进行换热, 可减少 36.8%的冷公用工程用量和 ${60.6}\%$ 的热公用工程用量。
周凯 [ 28 ] 利用 Aspen Dynamic 软件,采用NRTL (Non-random two liquid) 物性方法在稳态模拟的基础上对乙醇-水体系的精馏塔装置进行动态模拟, 通过经验凑试法和系统自动测试法进行验证并对比例-积分-微分(Proportion-Integral-Differential coefficient, PID)参数进行了优化, 以保持液位、流量、压力和温度等过程参数稳定。结果表明, 当过程参数波动很小时,采用 PID 控制器可使过程参数快速趋于稳定,而当过程参数波动较大时, 需要采用比值控制系统与串级控制系统来优化过程控制,进而优化精馏塔装置的控制结构。
蒋亚楠 [ 29 ] 研究了含有异丁醇、异戊醇和正丙醇的多组分乙醇分离体系, 以二甲基亚砜为萃取剂,提出了热集成等效四塔萃取精馏、常规四塔萃取精馏和热集成三塔萃取精馏。采用 Aspen Plus 软件对 3 个萃取精馏流程进行稳态模拟, Aspen Dynamics 软件对精馏塔进行动态模拟,对比分析可知: 热集成等效四塔萃取精馏流程有效降低了萃取乙醇的年度总费用, 提高了经济性; 采用高值选择器辅助回流比控制器改善了进料扰动时的滞后问题,减小了瞬时偏差;采用双温度控制结构可减小稳态偏差,提高产品纯度。
通过以上对燃料乙醇炼制系统优化的分析可知, 利用 Aspen Plus 软件对燃料乙醇的生物精炼厂进行模拟时, 大多数研究都是基于稳态模拟, 但在化工生产过程中,装置运行效率、产品产量与质量、生产操作的经济性与安全性均受到诸多因素的影响。例如, 对精馏系统进行热集成改造过程中, 稳态模拟结果显示, 改进后的过程可取得显著的节能效果, 但对过程的可控性、过程在扰动时的响应情况以及在何处设置换热器来保证过程的可操作性能等问题, 均不能通过稳态模拟解决, 因此,需要用 Aspen Plus Dynamics 软件对燃料乙醇炼制工艺进一步完善。
生命周期评价(Life Cycle Assessment, LCA) 是系统性的从源头防止和降低环境影响的评价工具。LCA 研究包括目的和范围的确定、生命周期清单分析、影响评价和解释,4 个阶段相互关联 [ 30 ] , 对产品整个工艺过程的资源利用、经济效益、能源效益、环境影响和社会影响进行全面分析。因此, 研究者们采用全生命周期分析方法对燃料乙醇进行可持续性分析, 有助于预防和减少环境污染、提高产品质量, 对研究产业发展方向及政策制定具有重要参考意义。LCA 常用软件有 eBalance, GREET, SimaPro, OpenLCA, Gabi 等。
目前, 依据 LCA 基本原理, 常见的碳足迹测量方法有 3 种。第一种是以过程分析为基础的 “自下而上”模型, 又称生命周期分析法 (LCA); 第二种是以投入产出分析为基础的“自上而下”模型, 该模型根据产品生命周期流程图, 收集并定量描述各工艺单元的温室气体 (Greenhouse Gas, GHG)排放数据, GHG 排放用 ${\mathrm{{CO}}}_{2}$ 当量表征, GHG 排放强度也被称为碳强度(Carbon Intensity, CI), $\mathrm{{CI}}$ 表示一种燃料提供 $1\mathrm{{MJ}}$ 能量所产生的 ${\mathrm{{CO}}}_{2}$ 当量( ${\mathrm{{CO}}}_{2}$,$\mathrm{{CO}}$,${\mathrm{{CH}}}_{4}$,$\mathrm{{HC}}$,${\mathrm{N}}_{2}\mathrm{O}$,${\mathrm{{CF}}}_{4}$${\mathrm{{NO}}}_{x}$${\mathrm{{CO}}}_{2}$ 当量值分别为1,31,21,12,269,6500和282) [ 31 ] ;第三种是基于联合国政府间气候变化专门委员会 (Intergovernmental Panel on Climate Change, IPCC)清单碳足迹核算法,各种 GHG 的排放量采用 IPCC 编制的国家 GHG 清单和对应排放因子进行计算,其数据易得、计算过程简捷,但间接 GHG 排放不易计算, 且选取区域性排放因子有一定困难 [ 31 ]
欧盟利用 LCA 法研究了不同原料生产乙醇的 ${\mathrm{{CO}}}_{2}$ 固存能力,并规定 ${\mathrm{{CO}}}_{2}$ 固存能力低于 ${60}\%$ 的燃料将不再被认定为 “生物燃料” [ 32 ] 。以玉米、小麦、 甘蔗、纤维素和秸秆为原料生产乙醇的 ${\mathrm{{CO}}}_{2}$ 固存能力分别为 ${31}\%,{34}\%,{71}\%,{90}\%$${87}{\%}$ [ 32 ] ,由此可知,相比于 $1\mathrm{G}$ 燃料乙醇,以秸秆和纤维素生物质为原料的 $2\mathrm{G}$ 燃料乙醇具有很大的碳减排潜力。
燃料乙醇的工艺路线众多, 多数研究显示出燃料乙醇具有明显的碳减排效用。Dunn J B [ 33 ] 研究了 LCA 在玉米秸秆、柳枝稷和芒草生产乙醇中的应用, 以及生物燃料可能导致土地利用变化 (Land Use Change, LUC)的 GHG 排放估计。结果表明,与传统汽油相比,芒草燃料乙醇减排GHG 的效果最好,其次是玉米秸秆燃料乙醇、柳枝稷燃料乙醇。随着LCA 方法和关键数据的完善, 预测 LUC、地上碳、地下碳以及影响土地的其他物理变化的经济模型也在不断改善, LCA 实践者应将这些改善纳入生物燃料生命周期 $\mathrm{{GHG}}$ 排放的估计中。
Lask J [ 34 ] 对芒草燃料乙醇的生命周期进行了评价,对液体热水 (Liquid Hot Water, LHW)、稀硫酸和稀氢氧化钠预处理技术进行了比较。结果表明: 芒草乙醇在交通运输领域具有减少 GHG 排放的潜力, 对生命周期气候变化的影响 (以提供 1 $\mathrm{{MJ}}$ 能量所产生的 ${\mathrm{{CO}}}_{2}$ 当量计)为 ${0.03}\sim {0.061}\mathrm{\;{kg}}/\mathrm{{MJ}}$ ; 就不同的预处理方式而言, 稀硫酸和 LHW 预处理的减排潜力要大得多。魏庭玉 [ 35 ] 计算了生物化学转化制取燃料乙醇、快速热解超临界乙醇提质制取生物油、气化费托合成制取生物航空燃料 3 条路线中各环节的环境影响潜值, 主要考虑 7 种环境影响:全球变暖潜值 (Global Warming Potential, GWP)、酸化潜值(Acidification Potential, AP)、富营养化潜值(Eutrophication Potential, EP)、非生物资源耗尽潜值(Depletion Potential of Abiotic Resources, ADP)、光化学臭氧生成潜值 (Photochemical Ozone Creation Potentials, POCP). 臭氧层耗尽潜值(Ozone Depletion Potential, ODP)、人类毒性潜值(Human Toxicity Potential, HTP)。研究结果显示: 玉米种植与秸杆收集过程导致了 GWP 和 HTP 的升高,主要原因在于我国农业生产过程中农药、化肥大量甚至过量使用及其上游生产过程的能耗与排放造成的; 预处理和水解发酵过程中使用的化学品较多, GWP 分别占 13.7%和 1.6%, ADP 分别占 24.5%和 18.1%; 产物分离与后处理阶段包含了废弃物处理与排放过程,尤其是燃烧烟气 (含有少量酸性气体,如 ${\mathrm{{SO}}}_{x}$ , $\left.{\mathrm{{NO}}}_{x}\right)$ 和无机盐废水排放,对环境影响较大, $\mathrm{{AP}}$ , ODP, EP 分别为 86.6%, 99.8% 和 96.7%。
生物质能-碳捕集与封存(Bioenergy with Carbon Capture and Sequestration, BECCS) 是一种有价值的碳减排技术, 可有效助力负碳的生物经济并提供碳中性能量。Yang M [ 36 ] 研究了使用高粱生产燃料乙醇过程中的沼气升级为可再生天然气 (Renewable Natural Gas, RNG) 和 ${\mathrm{{CO}}}_{2}$ 捕集与封存 $\left({{\mathrm{{CO}}}_{2}\text{ Capture and Storage,}\mathrm{{CCS}}}\right)$ 技术对生命周期温室气体和经济的影响。结果表明:与汽油(GHG 排放量为 ${93}\mathrm{g}/\mathrm{{MJ}}$ )相比,高粱燃料乙醇具有减少约 ${70}\%\mathrm{{GHG}}$ 排放的潜力,有利于减少生物精炼厂的碳足迹;采用 CCS 技术可显著降低 GHG 足迹,并能将碳减排成本降低至 ${52}\sim {78}\$/\mathrm{t}$ 。Lask J [ 37 ] 用芒草结合 CCS 技术生产燃料乙醇,使用芒草燃料乙醇替代汽油时, 可有助于减少交通领域的 GHG 排放,减少潜力为 104%~138%。因此, BECCS 是实现 “碳中和”的有效策略, 但其面临土地可用性和 ${\mathrm{{CO}}}_{2}$ 储存能力的限制、社会经济障碍、政策保障充分性、实施困难以及其他可持续性问题, 仍需深入探索, 以确保BECCS 是一种经济上可行的技术。
国内外很多研究者采用不同生物质原料生产燃料乙醇并采用不同的方法进行全生命周期分析, 进一步证实了燃料乙醇的低碳环保优势。Lyu H [ 38 ] 提出了利用纤维素 C5糖等全组分生产燃料乙醇的综合工艺, 研究了纤维素 C5 糖不同利用方式对燃料乙醇生产的影响, 结果表明, 以纤维素 C5 糖为原料的燃料乙醇生产工艺性能较好, 其净能量比和可再生性分别为 ${0.94},{1.09},\mathrm{{GWP}}$${2929}\mathrm{\;{kg}}\;{\mathrm{{CO}}}_{2}$ 当量。QinZ C [ 39 ] 采用 LCA 方法对燃料乙醇的 GHG 排放量进行定量分析。结果表明,燃料乙醇全生命周期的 GHG 排放 $\left({{36}\sim {39}\mathrm{\;g}/\mathrm{{MJ}}}\right)$ 符合美国环境保护局为 D3 乙醇制定的 GHG 减排阈值。Pang B [ 40 ] 提出并评价了乙醇、木糖和胶粘剂 (Ethanol-Xylose-Adhesive, EXA) 生物炼制工艺, 该工艺以农业废料玉米芯为原料, 可连续生产乙醇、木糖和粘合剂,总碳利用率为 79.6%,通过将蒸汽源由煤改为生物质, GHG 排放减少 60%。 Vera I [ 41 ] 研究了 8 种木质纤维素能源作物 (芒草、 柳枝稷、巨型芦苇、芦苇金丝雀草、刺菜蓟、杨树、 柳树和桉树)生产燃料乙醇的碳足迹。结果表明, 利用来源于边际性土地的能源作物生产纤维素燃料乙醇可以减少 ${\mathrm{{CO}}}_{2}$ 排放,且木本能源作物生产乙醇工艺的碳减排表现优于草本能源作物。利用边际土地种植木质纤维素能源作物以获得可持续生物质,可以最大限度地减少土地竞争,减少负面环境影响。因此, 合理利用并量化边际土地生产的 LCB 可以优化生物质能源系统的实际可用潜力。
将不同研究者对不同原料生产的燃料乙醇的碳减排分析结果汇总于 表 3 。由 表 3 可以看出, 无论采用何种纤维素原料,即使将 LUC 的 GHG 排放也算在内, 生物燃料乙醇也比汽油更能减少 GHG 排放,这主要是由于乙醇中的生物源碳取代了汽油中的化石碳。
①开发绿色高效的预处理技术、酶解发酵技术、高效生产菌株及工程改造技术、分离提纯技术以及自动化技术, 并将技术优化集成, 是提高生物炼制系统效率和燃料乙醇产能的关键。利用生物质废弃物进行燃料乙醇与其他附加值产品的联合生产是提高燃料乙醇竞争力的有效策略。
②利用 Aspen Plus 软件对燃料乙醇生产工艺进行稳态模拟和优化, 可以探索出经济高效的工艺路线。而实际生产中存在多种不确定因素, 如进料量或进料组成的改变均会对整个工艺造成影响, 所以后续可以利用 Aspen Plus Dynamic 软件对各个精馏塔的动态控制开展模拟研究, 使模拟过程更接近实际生产过程, 从而为纤维素燃料乙醇生产工业化提供理论指导。
③燃料乙醇代替传统的化石燃料具有较大的发展潜力。LCA 研究表明,与化石燃料相比,生物炼制系统可以节能减排,对促进 “碳中和” 具有重要意义。充分利用 BECCS 技术、土壤碳封存技术等环保有效的 ${\mathrm{{CO}}}_{2}$ 减排技术,可以带来更多的减排效益, 有利于建立健全绿色低碳循环发展的经济体系,助力实现“双碳”目标。
  • 国家自然科学基金项目(22178328)
  • 南阳市协同创新重大专项(郑州大学南阳研究院)
  • 车用生物燃料技术国家重点实验室开放课题(KFKT2019001)
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2024年第42卷第3期
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  • 接收时间:2022-07-03
  • 首发时间:2025-07-22
  • 出版时间:2024-03-20
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  • 收稿日期:2022-07-03
基金
国家自然科学基金项目(22178328)
南阳市协同创新重大专项(郑州大学南阳研究院)
车用生物燃料技术国家重点实验室开放课题(KFKT2019001)
作者信息
    1 郑州大学 化工学院 河南 郑州 450001
    2 车用生物燃料技术国家重点实验室 南阳 473000
    3 南阳理工学院 郑州大学南阳研究院 南阳 473004
    4 河南省杰出外籍科学家工作室 河南 郑州 450001

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常春(1973-),男,博士,教授,研究方向为生物质资源转化与利用。E-mail:
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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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