Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Oxy-fuel circulating fluidized bed combustion is known as one of the most potent fuel combustion technologies that capture ultra-low greenhouse gases and pollutant emissions. While many investigations have been conducted for carbon capturing, the associated in-situ desulfurization process using calcium-based sorbents should also be underlined. This paper critically reviews the effects of changes in the operating environment on in-situ desulfurization processes compared to conventional air combustion. A comprehensive understanding of the process, encompassing hydrodynamic, physical and chemical aspects can be a guideline for designing the oxy-fuel combustion process with effective sulfur removal, potentially eliminating the need of a flue gas desulfurization unit. Results from thermogravimetric analyzers and morphological changes of calcium-based materials were presented to offer an insight into the sulfation mechanisms involved in the oxy-fuel circulating fluidized beds. Recently findings suggested that in-situ direct desulfurization is influenced not only by the desulfurization kinetics but also by the fluidization characteristics of calcium-based materials. Therefore, a complex reaction analysis that incorporated oxy-combustion reactions, computational fluid dynamics modeling, in-situ desulfurization reaction models and particle behavior can provide a thorough understanding of desulfurization processes across the reactor. Meanwhile, machine learning as a robust tool to predict desulfurization efficiency and improve operational flexibility should be applied with consideration of environmental improvement and economic feasibility.
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Source |
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http://dx.doi.org/10.1016/j.envres.2024.119982 | DOI Listing |
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