Dynamic simulation and analysis of the phosgene recovery process using absorption under different control scheme
Journal of Cleaner Production, ISSN: 0959-6526, Vol: 426, Page: 139142
2023
- 3Citations
- 1Mentions
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Metrics Details
- Citations3
- Citation Indexes3
- Mentions1
- News Mentions1
- 1
Most Recent News
Findings from Qingdao University of Science and Technology Broaden Understanding of Environment and Sustainability Research (Dynamic Simulation and Analysis of the Phosgene Recovery Process Using Absorption Under Different Control Scheme)
2023 DEC 20 (NewsRx) -- By a News Reporter-Staff News Editor at Ecology Daily News -- Fresh data on Environment - Environment and Sustainability Research
Article Description
Phosgene was widely used in various industrial processes. The recovery of phosgene from tail gas is important for promoting environmental protection and process optimization. In this study, the solvent absorption method was employed to recover phosgene from tail gas. First, a baseline steady-state simulation of the phosgene recovery system was established and the results showed that 96 % of phosgene could be recovered. Second, a control scheme was developed; a dynamic simulation was conducted to analyze the dynamic performance of the system under different conditions, including system fluctuations and changes in operation. Additionally, technical and economic evaluations as well as an environmental analysis of the system were carried out. The results indicate that the control scheme has significant advantages in terms of resource conservation and a reduction in carbon and wastewater emissions. The findings provide a basis for the design and optimal operation of industrial phosgene recovery systems.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0959652623033000; http://dx.doi.org/10.1016/j.jclepro.2023.139142; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85173584699&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0959652623033000; https://dx.doi.org/10.1016/j.jclepro.2023.139142
Elsevier BV
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