Flame ionization detection as a simple real-time tar monitoring device for biomass downdraft gasification
A new, simple online tar- and performance measurement method for biomass gasifiers, based on flame ionization detection (FID), is presented. An empirical correlation between the total hydrocarbon content (THC) and the gravimetric tars in the product gas is established. The evaluation is done on a co...
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Veröffentlicht in: | Fuel (Guildford) 2021-04, Vol.289, p.119950, Article 119950 |
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description | A new, simple online tar- and performance measurement method for biomass gasifiers, based on flame ionization detection (FID), is presented. An empirical correlation between the total hydrocarbon content (THC) and the gravimetric tars in the product gas is established. The evaluation is done on a commercially available 85 kW throated downdraft gasifier fed with wood pellets. The product gas composition is determined with a gas analyzer for CO, CO2, CH4 and H2, as well as the tar protocol. This data is compared to the total hydrocarbon content measured with a flame ionization detector. To investigate different tar levels, different operating points of the gasifier are analyzed. The gathered data of THC versus gravimetric tars are best fitted by an exponential function. The repeatability of the method is proven with data from previous measurements with wood pellets and wood chips, although the employed correlation has to be adapted for different fuels and gasifiers. The presented FID based method has three main advantages compared to other state-of-the-art tar detection techniques: 1) in contrast to the widely used tar protocol the method delivers real-time results, hence the investigation of fast process changes is possible; 2) while other online detection devices are expensive, highly complex and often maintenance intensive, the presented method is simple, cheap and robust; and 3) the FID is flexible and convenient not only for tar detection, but for numerous other applications, which increases its attractiveness. |
doi_str_mv | 10.1016/j.fuel.2020.119950 |
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An empirical correlation between the total hydrocarbon content (THC) and the gravimetric tars in the product gas is established. The evaluation is done on a commercially available 85 kW throated downdraft gasifier fed with wood pellets. The product gas composition is determined with a gas analyzer for CO, CO2, CH4 and H2, as well as the tar protocol. This data is compared to the total hydrocarbon content measured with a flame ionization detector. To investigate different tar levels, different operating points of the gasifier are analyzed. The gathered data of THC versus gravimetric tars are best fitted by an exponential function. The repeatability of the method is proven with data from previous measurements with wood pellets and wood chips, although the employed correlation has to be adapted for different fuels and gasifiers. The presented FID based method has three main advantages compared to other state-of-the-art tar detection techniques: 1) in contrast to the widely used tar protocol the method delivers real-time results, hence the investigation of fast process changes is possible; 2) while other online detection devices are expensive, highly complex and often maintenance intensive, the presented method is simple, cheap and robust; and 3) the FID is flexible and convenient not only for tar detection, but for numerous other applications, which increases its attractiveness.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/j.fuel.2020.119950</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Biomass ; Biomass gasification ; Carbon dioxide ; Downdraft ; Downdraft gasifier ; Empirical analysis ; Exponential functions ; Flame ionization detection ; Flame ionization detectors ; Gas analyzers ; Gas composition ; Gasification ; Gravimetric analysis ; Hydrocarbons ; Ionization ; Measurement methods ; Online tar measurement ; Pellets ; Performance measurement ; Real time ; Tar ; Tars ; Wood ; Wood chips</subject><ispartof>Fuel (Guildford), 2021-04, Vol.289, p.119950, Article 119950</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier BV Apr 1, 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-e42e8adcbb7cbd12eae81224ba06df9bdd90314815d9ec7e86b2bb8141827efd3</citedby><cites>FETCH-LOGICAL-c328t-e42e8adcbb7cbd12eae81224ba06df9bdd90314815d9ec7e86b2bb8141827efd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.fuel.2020.119950$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids></links><search><creatorcontrib>Zachl, A.</creatorcontrib><creatorcontrib>Buchmayr, M.</creatorcontrib><creatorcontrib>Gruber, J.</creatorcontrib><creatorcontrib>Anca-Couce, A.</creatorcontrib><creatorcontrib>Scharler, R.</creatorcontrib><creatorcontrib>Hochenauer, C.</creatorcontrib><title>Flame ionization detection as a simple real-time tar monitoring device for biomass downdraft gasification</title><title>Fuel (Guildford)</title><description>A new, simple online tar- and performance measurement method for biomass gasifiers, based on flame ionization detection (FID), is presented. An empirical correlation between the total hydrocarbon content (THC) and the gravimetric tars in the product gas is established. The evaluation is done on a commercially available 85 kW throated downdraft gasifier fed with wood pellets. The product gas composition is determined with a gas analyzer for CO, CO2, CH4 and H2, as well as the tar protocol. This data is compared to the total hydrocarbon content measured with a flame ionization detector. To investigate different tar levels, different operating points of the gasifier are analyzed. The gathered data of THC versus gravimetric tars are best fitted by an exponential function. The repeatability of the method is proven with data from previous measurements with wood pellets and wood chips, although the employed correlation has to be adapted for different fuels and gasifiers. The presented FID based method has three main advantages compared to other state-of-the-art tar detection techniques: 1) in contrast to the widely used tar protocol the method delivers real-time results, hence the investigation of fast process changes is possible; 2) while other online detection devices are expensive, highly complex and often maintenance intensive, the presented method is simple, cheap and robust; and 3) the FID is flexible and convenient not only for tar detection, but for numerous other applications, which increases its attractiveness.</description><subject>Biomass</subject><subject>Biomass gasification</subject><subject>Carbon dioxide</subject><subject>Downdraft</subject><subject>Downdraft gasifier</subject><subject>Empirical analysis</subject><subject>Exponential functions</subject><subject>Flame ionization detection</subject><subject>Flame ionization detectors</subject><subject>Gas analyzers</subject><subject>Gas composition</subject><subject>Gasification</subject><subject>Gravimetric analysis</subject><subject>Hydrocarbons</subject><subject>Ionization</subject><subject>Measurement methods</subject><subject>Online tar measurement</subject><subject>Pellets</subject><subject>Performance measurement</subject><subject>Real time</subject><subject>Tar</subject><subject>Tars</subject><subject>Wood</subject><subject>Wood chips</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWKt_wFPA89Yk-5UFL1KsCgUveg75mJSU3U1N0or-etOuZ08zDM87MzwI3VKyoIQ299uF3UO_YITlAe26mpyhGeVtWbS0Ls_RjGSqYGVDL9FVjFtCSMvraobcqpcDYOdH9yNTLthAAn3qZMQSRzfsesABZF8kl9EkAx4ynnxw4ybjB6cBWx-wcn6QMWLjv0YTpE14I6OzTp8WX6MLK_sIN391jj5WT-_Ll2L99vy6fFwXumQ8FVAx4NJopVqtDGUggVPGKiVJY2ynjOlISStOa9OBboE3iinFaUU5a8Gaco7upr274D_3EJPY-n0Y80nBqq6qSEdJmSk2UTr4GANYsQtukOFbUCKOSsVWHJWKo1IxKc2hhykE-f-DgyCidjBqMC5kZ8J491_8F0UzgcU</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Zachl, A.</creator><creator>Buchmayr, M.</creator><creator>Gruber, J.</creator><creator>Anca-Couce, A.</creator><creator>Scharler, R.</creator><creator>Hochenauer, C.</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>20210401</creationdate><title>Flame ionization detection as a simple real-time tar monitoring device for biomass downdraft gasification</title><author>Zachl, A. ; Buchmayr, M. ; Gruber, J. ; Anca-Couce, A. ; Scharler, R. ; Hochenauer, C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-e42e8adcbb7cbd12eae81224ba06df9bdd90314815d9ec7e86b2bb8141827efd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Biomass</topic><topic>Biomass gasification</topic><topic>Carbon dioxide</topic><topic>Downdraft</topic><topic>Downdraft gasifier</topic><topic>Empirical analysis</topic><topic>Exponential functions</topic><topic>Flame ionization detection</topic><topic>Flame ionization detectors</topic><topic>Gas analyzers</topic><topic>Gas composition</topic><topic>Gasification</topic><topic>Gravimetric analysis</topic><topic>Hydrocarbons</topic><topic>Ionization</topic><topic>Measurement methods</topic><topic>Online tar measurement</topic><topic>Pellets</topic><topic>Performance measurement</topic><topic>Real time</topic><topic>Tar</topic><topic>Tars</topic><topic>Wood</topic><topic>Wood chips</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zachl, A.</creatorcontrib><creatorcontrib>Buchmayr, M.</creatorcontrib><creatorcontrib>Gruber, J.</creatorcontrib><creatorcontrib>Anca-Couce, A.</creatorcontrib><creatorcontrib>Scharler, R.</creatorcontrib><creatorcontrib>Hochenauer, C.</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Fuel (Guildford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zachl, A.</au><au>Buchmayr, M.</au><au>Gruber, J.</au><au>Anca-Couce, A.</au><au>Scharler, R.</au><au>Hochenauer, C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Flame ionization detection as a simple real-time tar monitoring device for biomass downdraft gasification</atitle><jtitle>Fuel (Guildford)</jtitle><date>2021-04-01</date><risdate>2021</risdate><volume>289</volume><spage>119950</spage><pages>119950-</pages><artnum>119950</artnum><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>A new, simple online tar- and performance measurement method for biomass gasifiers, based on flame ionization detection (FID), is presented. An empirical correlation between the total hydrocarbon content (THC) and the gravimetric tars in the product gas is established. The evaluation is done on a commercially available 85 kW throated downdraft gasifier fed with wood pellets. The product gas composition is determined with a gas analyzer for CO, CO2, CH4 and H2, as well as the tar protocol. This data is compared to the total hydrocarbon content measured with a flame ionization detector. To investigate different tar levels, different operating points of the gasifier are analyzed. The gathered data of THC versus gravimetric tars are best fitted by an exponential function. The repeatability of the method is proven with data from previous measurements with wood pellets and wood chips, although the employed correlation has to be adapted for different fuels and gasifiers. The presented FID based method has three main advantages compared to other state-of-the-art tar detection techniques: 1) in contrast to the widely used tar protocol the method delivers real-time results, hence the investigation of fast process changes is possible; 2) while other online detection devices are expensive, highly complex and often maintenance intensive, the presented method is simple, cheap and robust; and 3) the FID is flexible and convenient not only for tar detection, but for numerous other applications, which increases its attractiveness.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.fuel.2020.119950</doi></addata></record> |
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subjects | Biomass Biomass gasification Carbon dioxide Downdraft Downdraft gasifier Empirical analysis Exponential functions Flame ionization detection Flame ionization detectors Gas analyzers Gas composition Gasification Gravimetric analysis Hydrocarbons Ionization Measurement methods Online tar measurement Pellets Performance measurement Real time Tar Tars Wood Wood chips |
title | Flame ionization detection as a simple real-time tar monitoring device for biomass downdraft gasification |
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