Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province
The study qualitatively and quantitatively evaluated the uncertainty of the emission inventory of SO2, NOx, particulate matter (PM) and non-methane volatile organic compounds (NMVOCs) based on the measurement method in the process of organized sources in eight typical petroleum refining enterprises...
Gespeichert in:
| Veröffentlicht in: | IOP conference series. Earth and environmental science 2019-07, Vol.295 (5), p.52052 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 5 |
| container_start_page | 52052 |
| container_title | IOP conference series. Earth and environmental science |
| container_volume | 295 |
| creator | Xie, Donghai Zhang, Xiaxia Han, Qi He, Qingyang Meng, Xinxin Li, Feng Zhou, Kang |
| description | The study qualitatively and quantitatively evaluated the uncertainty of the emission inventory of SO2, NOx, particulate matter (PM) and non-methane volatile organic compounds (NMVOCs) based on the measurement method in the process of organized sources in eight typical petroleum refining enterprises in Hainan Province in 2017. According to the TRACE-P inventory grading, the activity level data uncertainty was between I and II, and the emission factor rating was roughly C-level. The qualitative assessment of the emission inventory is "good". The Monte Carlo simulation model was used to quantitatively evaluate the uncertainty. The results show that the uncertainties in emission inventory of SO2, NOx, PM and NMVOCs are ±2.9%, ±6.3%, ±7.6% and ±13.7%, respectively, with the highest uncertainty in NMVOCs emissions. The study on emission inventory uncertainty will help decision makers to scientifically formulate air pollutant control strategies for the accessibility of pollutant emission reduction targets of petrochemical enterprises and guide the improvement of emission inventory and data collection. |
| doi_str_mv | 10.1088/1755-1315/295/5/052052 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2557846399</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2557846399</sourcerecordid><originalsourceid>FETCH-LOGICAL-c460t-8742a23d5bcf57d7e477b5511e6b202ad2b2ec9945f9e88ccd632e6d6bf08ff33</originalsourceid><addsrcrecordid>eNqFkNFKwzAUhoMoOKevIAVvvKlN0iZpL8eobjCYoLsOaZpoRpfWpBPq05tZmQiCEDiB850vOT8A1wjeIZjnCWKExChFJMEFSUgCCQ7nBEyOjdPjHbJzcOH9FkLKsrSYgGZjpXK9MLYfopkVzeCNj1obPbpWKu-jtXsR1nyoOip3xnsTWkv7rmzfuiEygVN9IF_VzkjRRKXtleuc8SpIdLQIXvHlejfhnUtwpkXj1dV3nYLNffk8X8Sr9cNyPlvFMqOwj3OWYYHTmlRSE1YzlTFWEYKQohWGWNS4wkoWRUZ0ofJcypqmWNGaVhrmWqfpFNyM3s61b3vle75t9y4s5zkmhOUZTYsiUHSkpGu9d0rz8PGdcANHkB-S5YfQ-CFAHpLlhI_JhsHbcdC03Y-5LJ9-YbyrdUDxH-g__k8JCYmG</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2557846399</pqid></control><display><type>article</type><title>Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province</title><source>IOP Publishing Free Content</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>IOPscience extra</source><creator>Xie, Donghai ; Zhang, Xiaxia ; Han, Qi ; He, Qingyang ; Meng, Xinxin ; Li, Feng ; Zhou, Kang</creator><creatorcontrib>Xie, Donghai ; Zhang, Xiaxia ; Han, Qi ; He, Qingyang ; Meng, Xinxin ; Li, Feng ; Zhou, Kang</creatorcontrib><description>The study qualitatively and quantitatively evaluated the uncertainty of the emission inventory of SO2, NOx, particulate matter (PM) and non-methane volatile organic compounds (NMVOCs) based on the measurement method in the process of organized sources in eight typical petroleum refining enterprises in Hainan Province in 2017. According to the TRACE-P inventory grading, the activity level data uncertainty was between I and II, and the emission factor rating was roughly C-level. The qualitative assessment of the emission inventory is "good". The Monte Carlo simulation model was used to quantitatively evaluate the uncertainty. The results show that the uncertainties in emission inventory of SO2, NOx, PM and NMVOCs are ±2.9%, ±6.3%, ±7.6% and ±13.7%, respectively, with the highest uncertainty in NMVOCs emissions. The study on emission inventory uncertainty will help decision makers to scientifically formulate air pollutant control strategies for the accessibility of pollutant emission reduction targets of petrochemical enterprises and guide the improvement of emission inventory and data collection.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/295/5/052052</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Air pollution ; Data collection ; Emission analysis ; Emission inventories ; Emissions control ; Evaluation ; Measurement methods ; Monte Carlo simulation ; Nitrogen oxides ; Organic compounds ; Particulate emissions ; Particulate matter ; Petrochemicals ; Petroleum refining ; Pollutants ; Pollution control ; Sulfur dioxide ; Uncertainty analysis ; VOCs ; Volatile organic compounds</subject><ispartof>IOP conference series. Earth and environmental science, 2019-07, Vol.295 (5), p.52052</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c460t-8742a23d5bcf57d7e477b5511e6b202ad2b2ec9945f9e88ccd632e6d6bf08ff33</citedby><cites>FETCH-LOGICAL-c460t-8742a23d5bcf57d7e477b5511e6b202ad2b2ec9945f9e88ccd632e6d6bf08ff33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1755-1315/295/5/052052/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27901,27902,38845,38867,53815,53842</link.rule.ids></links><search><creatorcontrib>Xie, Donghai</creatorcontrib><creatorcontrib>Zhang, Xiaxia</creatorcontrib><creatorcontrib>Han, Qi</creatorcontrib><creatorcontrib>He, Qingyang</creatorcontrib><creatorcontrib>Meng, Xinxin</creatorcontrib><creatorcontrib>Li, Feng</creatorcontrib><creatorcontrib>Zhou, Kang</creatorcontrib><title>Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province</title><title>IOP conference series. Earth and environmental science</title><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><description>The study qualitatively and quantitatively evaluated the uncertainty of the emission inventory of SO2, NOx, particulate matter (PM) and non-methane volatile organic compounds (NMVOCs) based on the measurement method in the process of organized sources in eight typical petroleum refining enterprises in Hainan Province in 2017. According to the TRACE-P inventory grading, the activity level data uncertainty was between I and II, and the emission factor rating was roughly C-level. The qualitative assessment of the emission inventory is "good". The Monte Carlo simulation model was used to quantitatively evaluate the uncertainty. The results show that the uncertainties in emission inventory of SO2, NOx, PM and NMVOCs are ±2.9%, ±6.3%, ±7.6% and ±13.7%, respectively, with the highest uncertainty in NMVOCs emissions. The study on emission inventory uncertainty will help decision makers to scientifically formulate air pollutant control strategies for the accessibility of pollutant emission reduction targets of petrochemical enterprises and guide the improvement of emission inventory and data collection.</description><subject>Air pollution</subject><subject>Data collection</subject><subject>Emission analysis</subject><subject>Emission inventories</subject><subject>Emissions control</subject><subject>Evaluation</subject><subject>Measurement methods</subject><subject>Monte Carlo simulation</subject><subject>Nitrogen oxides</subject><subject>Organic compounds</subject><subject>Particulate emissions</subject><subject>Particulate matter</subject><subject>Petrochemicals</subject><subject>Petroleum refining</subject><subject>Pollutants</subject><subject>Pollution control</subject><subject>Sulfur dioxide</subject><subject>Uncertainty analysis</subject><subject>VOCs</subject><subject>Volatile organic compounds</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkNFKwzAUhoMoOKevIAVvvKlN0iZpL8eobjCYoLsOaZpoRpfWpBPq05tZmQiCEDiB850vOT8A1wjeIZjnCWKExChFJMEFSUgCCQ7nBEyOjdPjHbJzcOH9FkLKsrSYgGZjpXK9MLYfopkVzeCNj1obPbpWKu-jtXsR1nyoOip3xnsTWkv7rmzfuiEygVN9IF_VzkjRRKXtleuc8SpIdLQIXvHlejfhnUtwpkXj1dV3nYLNffk8X8Sr9cNyPlvFMqOwj3OWYYHTmlRSE1YzlTFWEYKQohWGWNS4wkoWRUZ0ofJcypqmWNGaVhrmWqfpFNyM3s61b3vle75t9y4s5zkmhOUZTYsiUHSkpGu9d0rz8PGdcANHkB-S5YfQ-CFAHpLlhI_JhsHbcdC03Y-5LJ9-YbyrdUDxH-g__k8JCYmG</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Xie, Donghai</creator><creator>Zhang, Xiaxia</creator><creator>Han, Qi</creator><creator>He, Qingyang</creator><creator>Meng, Xinxin</creator><creator>Li, Feng</creator><creator>Zhou, Kang</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>20190701</creationdate><title>Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province</title><author>Xie, Donghai ; Zhang, Xiaxia ; Han, Qi ; He, Qingyang ; Meng, Xinxin ; Li, Feng ; Zhou, Kang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c460t-8742a23d5bcf57d7e477b5511e6b202ad2b2ec9945f9e88ccd632e6d6bf08ff33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Air pollution</topic><topic>Data collection</topic><topic>Emission analysis</topic><topic>Emission inventories</topic><topic>Emissions control</topic><topic>Evaluation</topic><topic>Measurement methods</topic><topic>Monte Carlo simulation</topic><topic>Nitrogen oxides</topic><topic>Organic compounds</topic><topic>Particulate emissions</topic><topic>Particulate matter</topic><topic>Petrochemicals</topic><topic>Petroleum refining</topic><topic>Pollutants</topic><topic>Pollution control</topic><topic>Sulfur dioxide</topic><topic>Uncertainty analysis</topic><topic>VOCs</topic><topic>Volatile organic compounds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xie, Donghai</creatorcontrib><creatorcontrib>Zhang, Xiaxia</creatorcontrib><creatorcontrib>Han, Qi</creatorcontrib><creatorcontrib>He, Qingyang</creatorcontrib><creatorcontrib>Meng, Xinxin</creatorcontrib><creatorcontrib>Li, Feng</creatorcontrib><creatorcontrib>Zhou, Kang</creatorcontrib><collection>IOP Publishing Free Content</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>IOP conference series. Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xie, Donghai</au><au>Zhang, Xiaxia</au><au>Han, Qi</au><au>He, Qingyang</au><au>Meng, Xinxin</au><au>Li, Feng</au><au>Zhou, Kang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>295</volume><issue>5</issue><spage>52052</spage><pages>52052-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>The study qualitatively and quantitatively evaluated the uncertainty of the emission inventory of SO2, NOx, particulate matter (PM) and non-methane volatile organic compounds (NMVOCs) based on the measurement method in the process of organized sources in eight typical petroleum refining enterprises in Hainan Province in 2017. According to the TRACE-P inventory grading, the activity level data uncertainty was between I and II, and the emission factor rating was roughly C-level. The qualitative assessment of the emission inventory is "good". The Monte Carlo simulation model was used to quantitatively evaluate the uncertainty. The results show that the uncertainties in emission inventory of SO2, NOx, PM and NMVOCs are ±2.9%, ±6.3%, ±7.6% and ±13.7%, respectively, with the highest uncertainty in NMVOCs emissions. The study on emission inventory uncertainty will help decision makers to scientifically formulate air pollutant control strategies for the accessibility of pollutant emission reduction targets of petrochemical enterprises and guide the improvement of emission inventory and data collection.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/295/5/052052</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1755-1307 |
| ispartof | IOP conference series. Earth and environmental science, 2019-07, Vol.295 (5), p.52052 |
| issn | 1755-1307 1755-1315 |
| language | eng |
| recordid | cdi_proquest_journals_2557846399 |
| source | IOP Publishing Free Content; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; IOPscience extra |
| subjects | Air pollution Data collection Emission analysis Emission inventories Emissions control Evaluation Measurement methods Monte Carlo simulation Nitrogen oxides Organic compounds Particulate emissions Particulate matter Petrochemicals Petroleum refining Pollutants Pollution control Sulfur dioxide Uncertainty analysis VOCs Volatile organic compounds |
| title | Uncertainty Analysis on Process Organized Emission Inventory in Petrochemical Enterprises of Hainan Province |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T01%3A44%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Uncertainty%20Analysis%20on%20Process%20Organized%20Emission%20Inventory%20in%20Petrochemical%20Enterprises%20of%20Hainan%20Province&rft.jtitle=IOP%20conference%20series.%20Earth%20and%20environmental%20science&rft.au=Xie,%20Donghai&rft.date=2019-07-01&rft.volume=295&rft.issue=5&rft.spage=52052&rft.pages=52052-&rft.issn=1755-1307&rft.eissn=1755-1315&rft_id=info:doi/10.1088/1755-1315/295/5/052052&rft_dat=%3Cproquest_cross%3E2557846399%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2557846399&rft_id=info:pmid/&rfr_iscdi=true |