Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?
•Large uncertainties in calculating climate impact of aviation provide difficulties in reliably assessing mitigation options.•Using a Monte Carlo simulation is a meaningful method for uncertainty assessment.•Robust assessment of mitigation options despite large uncertainties in calculating the clima...
Gespeichert in:
Veröffentlicht in: | Transportation research. Part D, Transport and environment Transport and environment, 2016-07, Vol.46, p.40-55 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 55 |
---|---|
container_issue | |
container_start_page | 40 |
container_title | Transportation research. Part D, Transport and environment |
container_volume | 46 |
creator | Dahlmann, K. Grewe, V. Frömming, C. Burkhardt, U. |
description | •Large uncertainties in calculating climate impact of aviation provide difficulties in reliably assessing mitigation options.•Using a Monte Carlo simulation is a meaningful method for uncertainty assessment.•Robust assessment of mitigation options despite large uncertainties in calculating the climate impact of aviation.
Air traffic has an increasing influence on climate; therefore identifying mitigation options to reduce the climate impact of aviation becomes more and more important. Aviation influences climate through several climate agents, which show different dependencies on the magnitude and location of emission and the spatial and temporal impacts. Even counteracting effects can occur. Therefore, it is important to analyse all effects with high accuracy to identify mitigation potentials. However, the uncertainties in calculating the climate impact of aviation are partly large (up to a factor of about 2). In this study, we present a methodology, based on a Monte Carlo simulation of an updated non-linear climate-chemistry response model AirClim, to integrate above mentioned uncertainties in the climate assessment of mitigation options. Since mitigation options often represent small changes in emissions, we concentrate on a more generalised approach and use exemplarily different normalised global air traffic inventories to test the methodology. These inventories are identical in total emissions but differ in the spatial emission distribution. We show that using the Monte Carlo simulation and analysing relative differences between scenarios lead to a reliable assessment of mitigation potentials. In a use case we show that the presented methodology can be used to analyse even small differences between scenarios with mean flight altitude variations. |
doi_str_mv | 10.1016/j.trd.2016.03.006 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1825458592</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1361920916000353</els_id><sourcerecordid>1825458592</sourcerecordid><originalsourceid>FETCH-LOGICAL-c406t-d350b95091fc20598e4cc765dcc73b382f7ddbb3521adb4f0f3edf94e3ee41693</originalsourceid><addsrcrecordid>eNp9kD2P1DAQQCMEEsdxP-A6lzQJ4zjOxqJAaMUB0kk0UFuOPb6bVTYOHi_oyvvneLXUNDNTzJuP1zS3EjoJcnx_6EoOXV_LDlQHML5oruS0M22vBnhZazXK1vRgXjdvmA8AoLUer5rnvVvFHxQZF3Lz8iQcMzILv9DRFRRHKvTgCqVVpO2cWMSUhaMsSnYxkhfscXWZEouAvFGFFpcfUJxWj7k4WgshC1qFK8fE2yPmCm05eTyv-vi2eRXdwnjzL183P-8-_9h_be-_f_m2_3Tf-gHG0galYTYajIy-B20mHLzfjTrUqGY19XEXwjwr3UsX5iFCVBiiGVAhDnI06rp5d5lbV_86IRd7pHr6srgV04mtnHo96EmbvrbKS6vPiTljtFuuOvKTlWDPuu3BVt32rNuCslV3ZT5cGKw__CbMlj1hVRAooy82JPoP_RcN7Yv3</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1825458592</pqid></control><display><type>article</type><title>Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?</title><source>Elsevier ScienceDirect Journals Complete</source><creator>Dahlmann, K. ; Grewe, V. ; Frömming, C. ; Burkhardt, U.</creator><creatorcontrib>Dahlmann, K. ; Grewe, V. ; Frömming, C. ; Burkhardt, U.</creatorcontrib><description>•Large uncertainties in calculating climate impact of aviation provide difficulties in reliably assessing mitigation options.•Using a Monte Carlo simulation is a meaningful method for uncertainty assessment.•Robust assessment of mitigation options despite large uncertainties in calculating the climate impact of aviation.
Air traffic has an increasing influence on climate; therefore identifying mitigation options to reduce the climate impact of aviation becomes more and more important. Aviation influences climate through several climate agents, which show different dependencies on the magnitude and location of emission and the spatial and temporal impacts. Even counteracting effects can occur. Therefore, it is important to analyse all effects with high accuracy to identify mitigation potentials. However, the uncertainties in calculating the climate impact of aviation are partly large (up to a factor of about 2). In this study, we present a methodology, based on a Monte Carlo simulation of an updated non-linear climate-chemistry response model AirClim, to integrate above mentioned uncertainties in the climate assessment of mitigation options. Since mitigation options often represent small changes in emissions, we concentrate on a more generalised approach and use exemplarily different normalised global air traffic inventories to test the methodology. These inventories are identical in total emissions but differ in the spatial emission distribution. We show that using the Monte Carlo simulation and analysing relative differences between scenarios lead to a reliable assessment of mitigation potentials. In a use case we show that the presented methodology can be used to analyse even small differences between scenarios with mean flight altitude variations.</description><identifier>ISSN: 1361-9209</identifier><identifier>EISSN: 1879-2340</identifier><identifier>DOI: 10.1016/j.trd.2016.03.006</identifier><language>eng</language><publisher>Elsevier India Pvt Ltd</publisher><subject>Aeronautics ; Air traffic ; Assessments ; Aviation ; Climate ; Climate impact ; Computer simulation ; Methodology ; Monte Carlo simulation ; Uncertainties ; Uncertainty</subject><ispartof>Transportation research. Part D, Transport and environment, 2016-07, Vol.46, p.40-55</ispartof><rights>2016 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c406t-d350b95091fc20598e4cc765dcc73b382f7ddbb3521adb4f0f3edf94e3ee41693</citedby><cites>FETCH-LOGICAL-c406t-d350b95091fc20598e4cc765dcc73b382f7ddbb3521adb4f0f3edf94e3ee41693</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.trd.2016.03.006$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Dahlmann, K.</creatorcontrib><creatorcontrib>Grewe, V.</creatorcontrib><creatorcontrib>Frömming, C.</creatorcontrib><creatorcontrib>Burkhardt, U.</creatorcontrib><title>Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?</title><title>Transportation research. Part D, Transport and environment</title><description>•Large uncertainties in calculating climate impact of aviation provide difficulties in reliably assessing mitigation options.•Using a Monte Carlo simulation is a meaningful method for uncertainty assessment.•Robust assessment of mitigation options despite large uncertainties in calculating the climate impact of aviation.
Air traffic has an increasing influence on climate; therefore identifying mitigation options to reduce the climate impact of aviation becomes more and more important. Aviation influences climate through several climate agents, which show different dependencies on the magnitude and location of emission and the spatial and temporal impacts. Even counteracting effects can occur. Therefore, it is important to analyse all effects with high accuracy to identify mitigation potentials. However, the uncertainties in calculating the climate impact of aviation are partly large (up to a factor of about 2). In this study, we present a methodology, based on a Monte Carlo simulation of an updated non-linear climate-chemistry response model AirClim, to integrate above mentioned uncertainties in the climate assessment of mitigation options. Since mitigation options often represent small changes in emissions, we concentrate on a more generalised approach and use exemplarily different normalised global air traffic inventories to test the methodology. These inventories are identical in total emissions but differ in the spatial emission distribution. We show that using the Monte Carlo simulation and analysing relative differences between scenarios lead to a reliable assessment of mitigation potentials. In a use case we show that the presented methodology can be used to analyse even small differences between scenarios with mean flight altitude variations.</description><subject>Aeronautics</subject><subject>Air traffic</subject><subject>Assessments</subject><subject>Aviation</subject><subject>Climate</subject><subject>Climate impact</subject><subject>Computer simulation</subject><subject>Methodology</subject><subject>Monte Carlo simulation</subject><subject>Uncertainties</subject><subject>Uncertainty</subject><issn>1361-9209</issn><issn>1879-2340</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kD2P1DAQQCMEEsdxP-A6lzQJ4zjOxqJAaMUB0kk0UFuOPb6bVTYOHi_oyvvneLXUNDNTzJuP1zS3EjoJcnx_6EoOXV_LDlQHML5oruS0M22vBnhZazXK1vRgXjdvmA8AoLUer5rnvVvFHxQZF3Lz8iQcMzILv9DRFRRHKvTgCqVVpO2cWMSUhaMsSnYxkhfscXWZEouAvFGFFpcfUJxWj7k4WgshC1qFK8fE2yPmCm05eTyv-vi2eRXdwnjzL183P-8-_9h_be-_f_m2_3Tf-gHG0galYTYajIy-B20mHLzfjTrUqGY19XEXwjwr3UsX5iFCVBiiGVAhDnI06rp5d5lbV_86IRd7pHr6srgV04mtnHo96EmbvrbKS6vPiTljtFuuOvKTlWDPuu3BVt32rNuCslV3ZT5cGKw__CbMlj1hVRAooy82JPoP_RcN7Yv3</recordid><startdate>201607</startdate><enddate>201607</enddate><creator>Dahlmann, K.</creator><creator>Grewe, V.</creator><creator>Frömming, C.</creator><creator>Burkhardt, U.</creator><general>Elsevier India Pvt Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201607</creationdate><title>Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?</title><author>Dahlmann, K. ; Grewe, V. ; Frömming, C. ; Burkhardt, U.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c406t-d350b95091fc20598e4cc765dcc73b382f7ddbb3521adb4f0f3edf94e3ee41693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Aeronautics</topic><topic>Air traffic</topic><topic>Assessments</topic><topic>Aviation</topic><topic>Climate</topic><topic>Climate impact</topic><topic>Computer simulation</topic><topic>Methodology</topic><topic>Monte Carlo simulation</topic><topic>Uncertainties</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dahlmann, K.</creatorcontrib><creatorcontrib>Grewe, V.</creatorcontrib><creatorcontrib>Frömming, C.</creatorcontrib><creatorcontrib>Burkhardt, U.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Transportation research. Part D, Transport and environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dahlmann, K.</au><au>Grewe, V.</au><au>Frömming, C.</au><au>Burkhardt, U.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?</atitle><jtitle>Transportation research. Part D, Transport and environment</jtitle><date>2016-07</date><risdate>2016</risdate><volume>46</volume><spage>40</spage><epage>55</epage><pages>40-55</pages><issn>1361-9209</issn><eissn>1879-2340</eissn><abstract>•Large uncertainties in calculating climate impact of aviation provide difficulties in reliably assessing mitigation options.•Using a Monte Carlo simulation is a meaningful method for uncertainty assessment.•Robust assessment of mitigation options despite large uncertainties in calculating the climate impact of aviation.
Air traffic has an increasing influence on climate; therefore identifying mitigation options to reduce the climate impact of aviation becomes more and more important. Aviation influences climate through several climate agents, which show different dependencies on the magnitude and location of emission and the spatial and temporal impacts. Even counteracting effects can occur. Therefore, it is important to analyse all effects with high accuracy to identify mitigation potentials. However, the uncertainties in calculating the climate impact of aviation are partly large (up to a factor of about 2). In this study, we present a methodology, based on a Monte Carlo simulation of an updated non-linear climate-chemistry response model AirClim, to integrate above mentioned uncertainties in the climate assessment of mitigation options. Since mitigation options often represent small changes in emissions, we concentrate on a more generalised approach and use exemplarily different normalised global air traffic inventories to test the methodology. These inventories are identical in total emissions but differ in the spatial emission distribution. We show that using the Monte Carlo simulation and analysing relative differences between scenarios lead to a reliable assessment of mitigation potentials. In a use case we show that the presented methodology can be used to analyse even small differences between scenarios with mean flight altitude variations.</abstract><pub>Elsevier India Pvt Ltd</pub><doi>10.1016/j.trd.2016.03.006</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1361-9209 |
ispartof | Transportation research. Part D, Transport and environment, 2016-07, Vol.46, p.40-55 |
issn | 1361-9209 1879-2340 |
language | eng |
recordid | cdi_proquest_miscellaneous_1825458592 |
source | Elsevier ScienceDirect Journals Complete |
subjects | Aeronautics Air traffic Assessments Aviation Climate Climate impact Computer simulation Methodology Monte Carlo simulation Uncertainties Uncertainty |
title | Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes? |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T11%3A15%3A42IST&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=Can%20we%20reliably%20assess%20climate%20mitigation%20options%20for%20air%20traffic%20scenarios%20despite%20large%20uncertainties%20in%20atmospheric%20processes?&rft.jtitle=Transportation%20research.%20Part%20D,%20Transport%20and%20environment&rft.au=Dahlmann,%20K.&rft.date=2016-07&rft.volume=46&rft.spage=40&rft.epage=55&rft.pages=40-55&rft.issn=1361-9209&rft.eissn=1879-2340&rft_id=info:doi/10.1016/j.trd.2016.03.006&rft_dat=%3Cproquest_cross%3E1825458592%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=1825458592&rft_id=info:pmid/&rft_els_id=S1361920916000353&rfr_iscdi=true |