Models for Decarbonization in the Chemical Industry.

IF 7.6 2区 工程技术 Q1 CHEMISTRY, APPLIED Annual review of chemical and biomolecular engineering Pub Date : 2024-07-01 Epub Date: 2024-07-03 DOI:10.1146/annurev-chembioeng-100522-114115
Yuan Yao, Kai Lan, Thomas E Graedel, Narasimha D Rao
{"title":"Models for Decarbonization in the Chemical Industry.","authors":"Yuan Yao, Kai Lan, Thomas E Graedel, Narasimha D Rao","doi":"10.1146/annurev-chembioeng-100522-114115","DOIUrl":null,"url":null,"abstract":"<p><p>Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology-, economic-, and planetary boundary-based modeling support a more holistic systems-level assessment, more efforts are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics.</p>","PeriodicalId":8234,"journal":{"name":"Annual review of chemical and biomolecular engineering","volume":null,"pages":null},"PeriodicalIF":7.6000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual review of chemical and biomolecular engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1146/annurev-chembioeng-100522-114115","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/3 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology-, economic-, and planetary boundary-based modeling support a more holistic systems-level assessment, more efforts are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
化工行业的脱碳模式。
为实现化工行业的脱碳,人们提出了各种技术和战略。评估这些技术和战略对脱碳、环境和经济的影响,对于确定通往更可持续工业未来的道路至关重要。本研究回顾了系统分析模型的最新进展和集成,包括工艺分析、物料流分析、生命周期评估、技术经济分析和机器学习。这些模型根据分析方法和应用规模(即微观、中观和宏观规模)进行分类,适用于有前景的脱碳技术(如碳捕获、储存和利用、生物质原料和电气化)和循环经济战略。将前瞻性的数据驱动方法纳入现有模型,可以优化复杂的工业系统并评估未来的影响。虽然工业生态学、经济学和基于行星边界的建模技术的进步支持更全面的系统级评估,但还需要更多的效果来考虑对生态系统的影响。这些先进的综合模型的有效应用需要化学工程、工业生态学和经济学等学科的跨学科合作。化学与生物分子工程年度综述》第 15 卷的最终在线出版日期预计为 2024 年 6 月。有关修订后的预计日期,请参见 http://www.annualreviews.org/page/journal/pubdates。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Annual review of chemical and biomolecular engineering
Annual review of chemical and biomolecular engineering CHEMISTRY, APPLIED-ENGINEERING, CHEMICAL
CiteScore
16.00
自引率
0.00%
发文量
25
期刊介绍: The Annual Review of Chemical and Biomolecular Engineering aims to provide a perspective on the broad field of chemical (and related) engineering. The journal draws from disciplines as diverse as biology, physics, and engineering, with development of chemical products and processes as the unifying theme.
期刊最新文献
Reassessing the Standard Chemotaxis Framework for Understanding Biased Migration in Helicobacter pylori. Models for Decarbonization in the Chemical Industry. Introduction. Will Hydrogen Be a New Natural Gas? Hydrogen Integration in Natural Gas Grids. Fluid Ejections in Nature
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1