A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions
This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision probl...
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Veröffentlicht in: | The Science of the total environment 2018-04, Vol.621, p.980-989 |
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creator | Turrini, Enrico Carnevale, Claudio Finzi, Giovanna Volta, Marialuisa |
description | This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy.
[Display omitted]
•A new Integrated assessment methodology based on a multi-objective approach to support air quality planning;•Methodology able to be applied at different scale, from national to urban sites;•Methodology assessing the effectiveness of end-of pipe, energy and fuel switch measures, including behavioral changes;•Methodology assessing GHG emission variation due to changes in fuel consumption arising from energy measures application. |
doi_str_mv | 10.1016/j.scitotenv.2017.10.129 |
format | Article |
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[Display omitted]
•A new Integrated assessment methodology based on a multi-objective approach to support air quality planning;•Methodology able to be applied at different scale, from national to urban sites;•Methodology assessing the effectiveness of end-of pipe, energy and fuel switch measures, including behavioral changes;•Methodology assessing GHG emission variation due to changes in fuel consumption arising from energy measures application.</description><identifier>ISSN: 0048-9697</identifier><identifier>EISSN: 1879-1026</identifier><identifier>DOI: 10.1016/j.scitotenv.2017.10.129</identifier><identifier>PMID: 29089126</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Air quality ; Control strategy ; Decision support systems ; Environmental modelling ; Integrated assessment modelling ; Optimization ; Particulate matter</subject><ispartof>The Science of the total environment, 2018-04, Vol.621, p.980-989</ispartof><rights>2017 Elsevier B.V.</rights><rights>Copyright © 2017 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-9f6fc148fb9b4e4b302f99569b2a8d0e6932b9f52009871d8197b9a49bfd93123</citedby><cites>FETCH-LOGICAL-c371t-9f6fc148fb9b4e4b302f99569b2a8d0e6932b9f52009871d8197b9a49bfd93123</cites><orcidid>0000-0002-0309-0166 ; 0000-0002-0449-7558 ; 0000-0001-8924-6469</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.scitotenv.2017.10.129$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29089126$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Turrini, Enrico</creatorcontrib><creatorcontrib>Carnevale, Claudio</creatorcontrib><creatorcontrib>Finzi, Giovanna</creatorcontrib><creatorcontrib>Volta, Marialuisa</creatorcontrib><title>A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions</title><title>The Science of the total environment</title><addtitle>Sci Total Environ</addtitle><description>This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy.
[Display omitted]
•A new Integrated assessment methodology based on a multi-objective approach to support air quality planning;•Methodology able to be applied at different scale, from national to urban sites;•Methodology assessing the effectiveness of end-of pipe, energy and fuel switch measures, including behavioral changes;•Methodology assessing GHG emission variation due to changes in fuel consumption arising from energy measures application.</description><subject>Air quality</subject><subject>Control strategy</subject><subject>Decision support systems</subject><subject>Environmental modelling</subject><subject>Integrated assessment modelling</subject><subject>Optimization</subject><subject>Particulate matter</subject><issn>0048-9697</issn><issn>1879-1026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkMtuHCEQRVEUyx4_fiHpZTY9AfpFLUdWPLZkKZtkjYAuLEbdMAbakvP1oT2Ot2FTSPfUrapLyFdGt4yy_vthm4zLIaN_2XLKhu0qcPhENkwMUDPK-89kQ2krauhhuCCXKR1oeYNg5-SCAxXAeL8h067ywdeT86hiFY7Zze6Pyi746hjDU1Tz7PxTNYcRp8qGWCkXq-dFTS6_VsdJeb_KzptpGdefCbVGj9bl9Ibv7_cVzi6l4piuyZlVU8Kb93pFft_9-HV7Xz_-3D_c7h5r0wws12B7a1grrAbdYqsbyi1A14PmSowUe2i4BttxSkEMbBQMBg2qBW1HaBhvrsi3k2854XnBlGXZwOBU1sWwJMmgE13bdQMr6HBCTQwpRbTyGN2s4qtkVK5Ry4P8iFquUb8JHErnl_chi55x_Oj7l20BdicAy6kvDuNqhN7g6CKaLMfg_jvkL6GDlco</recordid><startdate>20180415</startdate><enddate>20180415</enddate><creator>Turrini, Enrico</creator><creator>Carnevale, Claudio</creator><creator>Finzi, Giovanna</creator><creator>Volta, Marialuisa</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0309-0166</orcidid><orcidid>https://orcid.org/0000-0002-0449-7558</orcidid><orcidid>https://orcid.org/0000-0001-8924-6469</orcidid></search><sort><creationdate>20180415</creationdate><title>A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions</title><author>Turrini, Enrico ; Carnevale, Claudio ; Finzi, Giovanna ; Volta, Marialuisa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c371t-9f6fc148fb9b4e4b302f99569b2a8d0e6932b9f52009871d8197b9a49bfd93123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Air quality</topic><topic>Control strategy</topic><topic>Decision support systems</topic><topic>Environmental modelling</topic><topic>Integrated assessment modelling</topic><topic>Optimization</topic><topic>Particulate matter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Turrini, Enrico</creatorcontrib><creatorcontrib>Carnevale, Claudio</creatorcontrib><creatorcontrib>Finzi, Giovanna</creatorcontrib><creatorcontrib>Volta, Marialuisa</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>The Science of the total environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Turrini, Enrico</au><au>Carnevale, Claudio</au><au>Finzi, Giovanna</au><au>Volta, Marialuisa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions</atitle><jtitle>The Science of the total environment</jtitle><addtitle>Sci Total Environ</addtitle><date>2018-04-15</date><risdate>2018</risdate><volume>621</volume><spage>980</spage><epage>989</epage><pages>980-989</pages><issn>0048-9697</issn><eissn>1879-1026</eissn><abstract>This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy.
[Display omitted]
•A new Integrated assessment methodology based on a multi-objective approach to support air quality planning;•Methodology able to be applied at different scale, from national to urban sites;•Methodology assessing the effectiveness of end-of pipe, energy and fuel switch measures, including behavioral changes;•Methodology assessing GHG emission variation due to changes in fuel consumption arising from energy measures application.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>29089126</pmid><doi>10.1016/j.scitotenv.2017.10.129</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-0309-0166</orcidid><orcidid>https://orcid.org/0000-0002-0449-7558</orcidid><orcidid>https://orcid.org/0000-0001-8924-6469</orcidid></addata></record> |
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source | Elsevier ScienceDirect Journals |
subjects | Air quality Control strategy Decision support systems Environmental modelling Integrated assessment modelling Optimization Particulate matter |
title | A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions |
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