Unit-based emission inventory and uncertainty assessment of coal-fired power plants
A unit-based emission inventory of coal-fired power plants in China was developed which contains unit capacity, coal consumption, emission control technology and geographical location. Estimated total emissions of SO2, NOx, particulate matter (PM) and PM2.5 in 2011 were 7251 kt, 8067 kt, 1433 kt and...
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Veröffentlicht in: | Atmospheric environment (1994) 2014-12, Vol.99, p.527-535 |
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description | A unit-based emission inventory of coal-fired power plants in China was developed which contains unit capacity, coal consumption, emission control technology and geographical location. Estimated total emissions of SO2, NOx, particulate matter (PM) and PM2.5 in 2011 were 7251 kt, 8067 kt, 1433 kt and 622 kt, respectively. Units larger than 300 MW consumed 75% coal, while emitting 46% SO2, 58% NOx, 55% PM and 63.2% PM2.5. Emission comparisons between key regions such as the Yangtze River Delta, the Pearl River Delta and Shandong Province showed a general downward trend from 2005 to 2011, mainly because of the growing application ratio of desulphurisation, LNBs, denitration and dust-removal facilities. The uncertainties at unit level of SO2, NOx, PM and PM2.5 were estimated to be −10.1% ∼ +5.4%, −2.1% ∼ +4.6%, −5.7% ∼ +6.9% and −4.3% ∼ +6.5%, respectively. Meanwhile sector-based Monte Carlo simulation was conducted for better understanding of the uncertainties. Unit-based simulation yielded narrowed estimates of uncertainties, possibly caused by the neglected diversity of emission characteristics in sector-based simulation. The large number of plants narrowed unit-based uncertainties as large uncertainties were found in provinces with a small number of power plants, such as Qinghai. However, sector-based uncertainty analysis well depends on detailed source classification, because small NOx uncertainties were found in Shandong due to the detailed classification of NOx emission factors. The main uncertainty sources are discussed in the sensitivity analysis, which identifies specific needs in data investigation and field measures to improve them. Though unit-based Monte Carlo greatly narrowed uncertainties, the possibility of underestimated uncertainties at unit level cannot be ignored as the correlation of emission factors between units in the same source category was neglected.
•Large amount of plants decreases uncertainties in unit-based inventory.•Uncertainties at sector level mainly depend on the detailed source classification.•Field measurements are compiled to include NOx emission factor database.•Unit-based emission inventory of coal-fired power plants was developed for 2011.•Emission comparison between 2005 and 2011 showed a downward trend in key regions. |
doi_str_mv | 10.1016/j.atmosenv.2014.10.023 |
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•Large amount of plants decreases uncertainties in unit-based inventory.•Uncertainties at sector level mainly depend on the detailed source classification.•Field measurements are compiled to include NOx emission factor database.•Unit-based emission inventory of coal-fired power plants was developed for 2011.•Emission comparison between 2005 and 2011 showed a downward trend in key regions.</description><identifier>ISSN: 1352-2310</identifier><identifier>EISSN: 1873-2844</identifier><identifier>DOI: 10.1016/j.atmosenv.2014.10.023</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Atmospheric pollution ; China ; Classification ; Coal ; Coal fired powerplants ; Coal-fired power plant ; Combustion and energy production ; Computer simulation ; Emission ; Emission analysis ; Exact sciences and technology ; Freshwater ; Monte Carlo methods ; NOx ; PM2.5 ; Pollution ; Pollution sources ; Pollution sources. Measurement results ; SO2 ; Uncertainty ; Uncertainty assessment ; Unit-based emission inventory</subject><ispartof>Atmospheric environment (1994), 2014-12, Vol.99, p.527-535</ispartof><rights>2014</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-d857ba0c08a96c3b16c1be63094fb44039448c6f3e311f0e37abbdd993b775533</citedby><cites>FETCH-LOGICAL-c408t-d857ba0c08a96c3b16c1be63094fb44039448c6f3e311f0e37abbdd993b775533</cites><orcidid>0000-0002-8171-4632</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1352231014008127$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28914894$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Linghong</creatorcontrib><creatorcontrib>Sun, Yangyang</creatorcontrib><creatorcontrib>Wu, Xuecheng</creatorcontrib><creatorcontrib>Zhang, Yongxin</creatorcontrib><creatorcontrib>Zheng, Chenghang</creatorcontrib><creatorcontrib>Gao, Xiang</creatorcontrib><creatorcontrib>Cen, Kefa</creatorcontrib><title>Unit-based emission inventory and uncertainty assessment of coal-fired power plants</title><title>Atmospheric environment (1994)</title><description>A unit-based emission inventory of coal-fired power plants in China was developed which contains unit capacity, coal consumption, emission control technology and geographical location. Estimated total emissions of SO2, NOx, particulate matter (PM) and PM2.5 in 2011 were 7251 kt, 8067 kt, 1433 kt and 622 kt, respectively. Units larger than 300 MW consumed 75% coal, while emitting 46% SO2, 58% NOx, 55% PM and 63.2% PM2.5. Emission comparisons between key regions such as the Yangtze River Delta, the Pearl River Delta and Shandong Province showed a general downward trend from 2005 to 2011, mainly because of the growing application ratio of desulphurisation, LNBs, denitration and dust-removal facilities. The uncertainties at unit level of SO2, NOx, PM and PM2.5 were estimated to be −10.1% ∼ +5.4%, −2.1% ∼ +4.6%, −5.7% ∼ +6.9% and −4.3% ∼ +6.5%, respectively. Meanwhile sector-based Monte Carlo simulation was conducted for better understanding of the uncertainties. Unit-based simulation yielded narrowed estimates of uncertainties, possibly caused by the neglected diversity of emission characteristics in sector-based simulation. The large number of plants narrowed unit-based uncertainties as large uncertainties were found in provinces with a small number of power plants, such as Qinghai. However, sector-based uncertainty analysis well depends on detailed source classification, because small NOx uncertainties were found in Shandong due to the detailed classification of NOx emission factors. The main uncertainty sources are discussed in the sensitivity analysis, which identifies specific needs in data investigation and field measures to improve them. Though unit-based Monte Carlo greatly narrowed uncertainties, the possibility of underestimated uncertainties at unit level cannot be ignored as the correlation of emission factors between units in the same source category was neglected.
•Large amount of plants decreases uncertainties in unit-based inventory.•Uncertainties at sector level mainly depend on the detailed source classification.•Field measurements are compiled to include NOx emission factor database.•Unit-based emission inventory of coal-fired power plants was developed for 2011.•Emission comparison between 2005 and 2011 showed a downward trend in key regions.</description><subject>Applied sciences</subject><subject>Atmospheric pollution</subject><subject>China</subject><subject>Classification</subject><subject>Coal</subject><subject>Coal fired powerplants</subject><subject>Coal-fired power plant</subject><subject>Combustion and energy production</subject><subject>Computer simulation</subject><subject>Emission</subject><subject>Emission analysis</subject><subject>Exact sciences and technology</subject><subject>Freshwater</subject><subject>Monte Carlo methods</subject><subject>NOx</subject><subject>PM2.5</subject><subject>Pollution</subject><subject>Pollution sources</subject><subject>Pollution sources. Measurement results</subject><subject>SO2</subject><subject>Uncertainty</subject><subject>Uncertainty assessment</subject><subject>Unit-based emission inventory</subject><issn>1352-2310</issn><issn>1873-2844</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqNkE1LxDAQhoso-PkXpBfBS9dJkybtTRG_QPCgnkOaTiFLN1kz2RX_vVlXveppMpP3nTd5iuKUwYwBkxfzmUmLQOjXsxqYyMMZ1HynOGCt4lXdCrGbz7ypq5oz2C8OieYAwFWnDornV-9S1RvCocSFI3LBl86v0acQP0rjh3LlLcZknE-5J0KiRb4tw1jaYKZqdDF7l-EdY7mcjE90XOyNZiI8-a5Hxevtzcv1ffX4dPdwffVYWQFtqoa2Ub0BC63ppOU9k5b1KDl0YuyFAN4J0Vo5cuSMjYBcmb4fhq7jvVJNw_lRcb7du4zhbYWUdP6AxSk_AsOKNJMSQELTiH9Ihcos1ZdUbqU2BqKIo15GtzDxQzPQG-B6rn-A6w3wzTwDz8az7wxD1kxjNN46-nXXbcdE220CLrc6zGzWDqMm6zBDHjJJm_QQ3F9Rn2ulmo0</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Chen, Linghong</creator><creator>Sun, Yangyang</creator><creator>Wu, Xuecheng</creator><creator>Zhang, Yongxin</creator><creator>Zheng, Chenghang</creator><creator>Gao, Xiang</creator><creator>Cen, Kefa</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>7TV</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-8171-4632</orcidid></search><sort><creationdate>20141201</creationdate><title>Unit-based emission inventory and uncertainty assessment of coal-fired power plants</title><author>Chen, Linghong ; Sun, Yangyang ; Wu, Xuecheng ; Zhang, Yongxin ; Zheng, Chenghang ; Gao, Xiang ; Cen, Kefa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-d857ba0c08a96c3b16c1be63094fb44039448c6f3e311f0e37abbdd993b775533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Applied sciences</topic><topic>Atmospheric pollution</topic><topic>China</topic><topic>Classification</topic><topic>Coal</topic><topic>Coal fired powerplants</topic><topic>Coal-fired power plant</topic><topic>Combustion and energy production</topic><topic>Computer simulation</topic><topic>Emission</topic><topic>Emission analysis</topic><topic>Exact sciences and technology</topic><topic>Freshwater</topic><topic>Monte Carlo methods</topic><topic>NOx</topic><topic>PM2.5</topic><topic>Pollution</topic><topic>Pollution sources</topic><topic>Pollution sources. Measurement results</topic><topic>SO2</topic><topic>Uncertainty</topic><topic>Uncertainty assessment</topic><topic>Unit-based emission inventory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Linghong</creatorcontrib><creatorcontrib>Sun, Yangyang</creatorcontrib><creatorcontrib>Wu, Xuecheng</creatorcontrib><creatorcontrib>Zhang, Yongxin</creatorcontrib><creatorcontrib>Zheng, Chenghang</creatorcontrib><creatorcontrib>Gao, Xiang</creatorcontrib><creatorcontrib>Cen, Kefa</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Pollution Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Atmospheric environment (1994)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Linghong</au><au>Sun, Yangyang</au><au>Wu, Xuecheng</au><au>Zhang, Yongxin</au><au>Zheng, Chenghang</au><au>Gao, Xiang</au><au>Cen, Kefa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Unit-based emission inventory and uncertainty assessment of coal-fired power plants</atitle><jtitle>Atmospheric environment (1994)</jtitle><date>2014-12-01</date><risdate>2014</risdate><volume>99</volume><spage>527</spage><epage>535</epage><pages>527-535</pages><issn>1352-2310</issn><eissn>1873-2844</eissn><abstract>A unit-based emission inventory of coal-fired power plants in China was developed which contains unit capacity, coal consumption, emission control technology and geographical location. Estimated total emissions of SO2, NOx, particulate matter (PM) and PM2.5 in 2011 were 7251 kt, 8067 kt, 1433 kt and 622 kt, respectively. Units larger than 300 MW consumed 75% coal, while emitting 46% SO2, 58% NOx, 55% PM and 63.2% PM2.5. Emission comparisons between key regions such as the Yangtze River Delta, the Pearl River Delta and Shandong Province showed a general downward trend from 2005 to 2011, mainly because of the growing application ratio of desulphurisation, LNBs, denitration and dust-removal facilities. The uncertainties at unit level of SO2, NOx, PM and PM2.5 were estimated to be −10.1% ∼ +5.4%, −2.1% ∼ +4.6%, −5.7% ∼ +6.9% and −4.3% ∼ +6.5%, respectively. Meanwhile sector-based Monte Carlo simulation was conducted for better understanding of the uncertainties. Unit-based simulation yielded narrowed estimates of uncertainties, possibly caused by the neglected diversity of emission characteristics in sector-based simulation. The large number of plants narrowed unit-based uncertainties as large uncertainties were found in provinces with a small number of power plants, such as Qinghai. However, sector-based uncertainty analysis well depends on detailed source classification, because small NOx uncertainties were found in Shandong due to the detailed classification of NOx emission factors. The main uncertainty sources are discussed in the sensitivity analysis, which identifies specific needs in data investigation and field measures to improve them. Though unit-based Monte Carlo greatly narrowed uncertainties, the possibility of underestimated uncertainties at unit level cannot be ignored as the correlation of emission factors between units in the same source category was neglected.
•Large amount of plants decreases uncertainties in unit-based inventory.•Uncertainties at sector level mainly depend on the detailed source classification.•Field measurements are compiled to include NOx emission factor database.•Unit-based emission inventory of coal-fired power plants was developed for 2011.•Emission comparison between 2005 and 2011 showed a downward trend in key regions.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.atmosenv.2014.10.023</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-8171-4632</orcidid></addata></record> |
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subjects | Applied sciences Atmospheric pollution China Classification Coal Coal fired powerplants Coal-fired power plant Combustion and energy production Computer simulation Emission Emission analysis Exact sciences and technology Freshwater Monte Carlo methods NOx PM2.5 Pollution Pollution sources Pollution sources. Measurement results SO2 Uncertainty Uncertainty assessment Unit-based emission inventory |
title | Unit-based emission inventory and uncertainty assessment of coal-fired power plants |
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