Effects of the Emissions of Vehicles Ahead on In‐Car Exposure to Traffic‐Related Air Pollutants: A Multiple Statistical Analysis Approach
Traffic‐related air pollutants inside vehicle cabins are often extremely high compared to background pollution concentrations. The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aime...
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creator | Campagnolo, Davide Cattaneo, Andrea Iodice, Simona Favero, Chiara Lioi, Simone Boniardi, Luca Borghi, Francesca Fanti, Giacomo Keller, Marta Rovelli, Sabrina Zellino, Carolina De Vito, Giovanni Spinazzè, Andrea Fustinoni, Silvia Bollati, Valentina Cavallo, Domenico M. |
description | Traffic‐related air pollutants inside vehicle cabins are often extremely high compared to background pollution concentrations. The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aimed at identifying and quantifying the effect of several exposure determinants on carbon monoxide (CO), equivalent black carbon (eBC), two particulate matter (PM) fractions (PM 0.3–1 and PM 1–2.5 ), and ultrafine particle (UFP) concentrations inside a passenger car cabin. The novelty of this work consists in examining the effects of the emissions of the first vehicle ahead (henceforth called “leading vehicle”) on pollutant concentrations inside the cabin of the following vehicle (i.e., the car that was equipped with the air monitoring devices), with particular emphasis on the role of the leading vehicle characteristics (e.g., emission reduction technologies). The real‐time instrumentation was placed inside the cabin of a petrol passenger car, which was driven by the same operator two times per day on the same route in real driving conditions. The in‐cabin ventilation settings were set as follows: windows closed, air conditioning and recirculation modes off, and the fanned ventilation system on. The measurements were conducted over a total of 10 weekdays during two different seasons (i.e., summer and autumn). A video camera fixed to the windscreen was used to retrieve information about traffic conditions and leading vehicle characteristics through careful video analysis. The associations among pollutant concentrations and their potential determinants were evaluated using generalized estimating equation univariate and multiple models. The results confirmed the significant impact of several well‐known determinants such as seasonality, microclimatic parameters, traffic jam situations, and route characteristics. Moreover, the outcomes shed light on the key role of leading vehicle emissions as determinant factors of the pollutant concentrations inside car cabins. Indeed, in the tested cabin ventilation conditions, it was demonstrated that in‐cabin pollutant concentrations were significantly higher with leading vehicles ahead (from +14.6% to +67.5%) compared to empty road conditions, even though the introduction of newer technologies with better emissions reduction helped mitigate their effect. Additionally, diesel‐fuelled leading vehicles compared to petrol‐fuelled lead |
doi_str_mv | 10.1155/2024/6377126 |
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The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aimed at identifying and quantifying the effect of several exposure determinants on carbon monoxide (CO), equivalent black carbon (eBC), two particulate matter (PM) fractions (PM 0.3–1 and PM 1–2.5 ), and ultrafine particle (UFP) concentrations inside a passenger car cabin. The novelty of this work consists in examining the effects of the emissions of the first vehicle ahead (henceforth called “leading vehicle”) on pollutant concentrations inside the cabin of the following vehicle (i.e., the car that was equipped with the air monitoring devices), with particular emphasis on the role of the leading vehicle characteristics (e.g., emission reduction technologies). The real‐time instrumentation was placed inside the cabin of a petrol passenger car, which was driven by the same operator two times per day on the same route in real driving conditions. The in‐cabin ventilation settings were set as follows: windows closed, air conditioning and recirculation modes off, and the fanned ventilation system on. The measurements were conducted over a total of 10 weekdays during two different seasons (i.e., summer and autumn). A video camera fixed to the windscreen was used to retrieve information about traffic conditions and leading vehicle characteristics through careful video analysis. The associations among pollutant concentrations and their potential determinants were evaluated using generalized estimating equation univariate and multiple models. The results confirmed the significant impact of several well‐known determinants such as seasonality, microclimatic parameters, traffic jam situations, and route characteristics. Moreover, the outcomes shed light on the key role of leading vehicle emissions as determinant factors of the pollutant concentrations inside car cabins. Indeed, in the tested cabin ventilation conditions, it was demonstrated that in‐cabin pollutant concentrations were significantly higher with leading vehicles ahead (from +14.6% to +67.5%) compared to empty road conditions, even though the introduction of newer technologies with better emissions reduction helped mitigate their effect. Additionally, diesel‐fuelled leading vehicles compared to petrol‐fuelled leading vehicles were impactful on in‐cabin CO (−7.2%) and eBC (+45.3%) concentrations. An important effect (+30.4%) on in‐vehicle PM 1–2.5 concentrations was found with heavy‐duty compared to light‐duty leading vehicles. Finally, this research pointed out that road‐scale factors are more important determinant factors of in‐cabin concentrations than local pollution and meteorological conditions.</description><identifier>ISSN: 0905-6947</identifier><identifier>EISSN: 1600-0668</identifier><identifier>DOI: 10.1155/2024/6377126</identifier><language>eng</language><publisher>Malden: Hindawi Limited</publisher><subject>Air pollution ; Carbon ; Emissions ; Indoor air quality ; Mortality ; Nitrogen dioxide ; Outdoor air quality ; Pollutants ; Statistical analysis ; Systematic review ; Vehicle emissions ; Vehicles ; VOCs ; Volatile organic compounds</subject><ispartof>Indoor air, 2024-01, Vol.2024 (1)</ispartof><rights>Copyright © 2024 Davide Campagnolo et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c188t-449bc171613490f80f8ad4ac5f4d5aceea6e3c72c4eed7b540db6aa98d69834f3</cites><orcidid>0000-0001-5594-8761 ; 0000-0002-3953-1197 ; 0000-0003-0371-3164 ; 0000-0003-3608-7964 ; 0000-0003-3452-2803 ; 0000-0002-3728-839X ; 0000-0002-2962-7259 ; 0000-0002-6403-5101 ; 0000-0002-0370-9598 ; 0000-0002-2836-6106 ; 0000-0001-6634-2394 ; 0000-0001-6059-1306 ; 0000-0003-1853-2999 ; 0000-0002-0287-7338</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3118512656/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3118512656?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,21393,21394,27929,27930,33535,33749,43664,43810,64390,64394,72474,74109,74307</link.rule.ids></links><search><contributor>Yang, Xiaohu</contributor><contributor>Xiaohu Yang</contributor><creatorcontrib>Campagnolo, Davide</creatorcontrib><creatorcontrib>Cattaneo, Andrea</creatorcontrib><creatorcontrib>Iodice, Simona</creatorcontrib><creatorcontrib>Favero, Chiara</creatorcontrib><creatorcontrib>Lioi, Simone</creatorcontrib><creatorcontrib>Boniardi, Luca</creatorcontrib><creatorcontrib>Borghi, Francesca</creatorcontrib><creatorcontrib>Fanti, Giacomo</creatorcontrib><creatorcontrib>Keller, Marta</creatorcontrib><creatorcontrib>Rovelli, Sabrina</creatorcontrib><creatorcontrib>Zellino, Carolina</creatorcontrib><creatorcontrib>De Vito, Giovanni</creatorcontrib><creatorcontrib>Spinazzè, Andrea</creatorcontrib><creatorcontrib>Fustinoni, Silvia</creatorcontrib><creatorcontrib>Bollati, Valentina</creatorcontrib><creatorcontrib>Cavallo, Domenico M.</creatorcontrib><title>Effects of the Emissions of Vehicles Ahead on In‐Car Exposure to Traffic‐Related Air Pollutants: A Multiple Statistical Analysis Approach</title><title>Indoor air</title><description>Traffic‐related air pollutants inside vehicle cabins are often extremely high compared to background pollution concentrations. The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aimed at identifying and quantifying the effect of several exposure determinants on carbon monoxide (CO), equivalent black carbon (eBC), two particulate matter (PM) fractions (PM 0.3–1 and PM 1–2.5 ), and ultrafine particle (UFP) concentrations inside a passenger car cabin. The novelty of this work consists in examining the effects of the emissions of the first vehicle ahead (henceforth called “leading vehicle”) on pollutant concentrations inside the cabin of the following vehicle (i.e., the car that was equipped with the air monitoring devices), with particular emphasis on the role of the leading vehicle characteristics (e.g., emission reduction technologies). The real‐time instrumentation was placed inside the cabin of a petrol passenger car, which was driven by the same operator two times per day on the same route in real driving conditions. The in‐cabin ventilation settings were set as follows: windows closed, air conditioning and recirculation modes off, and the fanned ventilation system on. The measurements were conducted over a total of 10 weekdays during two different seasons (i.e., summer and autumn). A video camera fixed to the windscreen was used to retrieve information about traffic conditions and leading vehicle characteristics through careful video analysis. The associations among pollutant concentrations and their potential determinants were evaluated using generalized estimating equation univariate and multiple models. The results confirmed the significant impact of several well‐known determinants such as seasonality, microclimatic parameters, traffic jam situations, and route characteristics. Moreover, the outcomes shed light on the key role of leading vehicle emissions as determinant factors of the pollutant concentrations inside car cabins. Indeed, in the tested cabin ventilation conditions, it was demonstrated that in‐cabin pollutant concentrations were significantly higher with leading vehicles ahead (from +14.6% to +67.5%) compared to empty road conditions, even though the introduction of newer technologies with better emissions reduction helped mitigate their effect. Additionally, diesel‐fuelled leading vehicles compared to petrol‐fuelled leading vehicles were impactful on in‐cabin CO (−7.2%) and eBC (+45.3%) concentrations. An important effect (+30.4%) on in‐vehicle PM 1–2.5 concentrations was found with heavy‐duty compared to light‐duty leading vehicles. Finally, this research pointed out that road‐scale factors are more important determinant factors of in‐cabin concentrations than local pollution and meteorological conditions.</description><subject>Air pollution</subject><subject>Carbon</subject><subject>Emissions</subject><subject>Indoor air quality</subject><subject>Mortality</subject><subject>Nitrogen dioxide</subject><subject>Outdoor air quality</subject><subject>Pollutants</subject><subject>Statistical analysis</subject><subject>Systematic review</subject><subject>Vehicle emissions</subject><subject>Vehicles</subject><subject>VOCs</subject><subject>Volatile organic compounds</subject><issn>0905-6947</issn><issn>1600-0668</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNotkN1KxDAQhYMouP7c-QABb62bbNK09a4s6w8oiq7eltl0wkZiU5MU3DtfQPAZfRLrDwwMzBzOOXyEHHF2ynmeT2dsJqdKFAWfqS0y4YqxjClVbpMJq1ieqUoWu2QvxmfGeCEqMSEfC2NQp0i9oWmNdPFiY7S--z084dpqh5HWa4SW-o5edV_vn3MIdPHW-zgEpMnTZQBjrB4_9-ggYUtrG-idd25I0KV4Rmt6M7hke4f0IUGyMVkNjtYduE20o3_fBw96fUB2DLiIh_97nzyeL5bzy-z69uJqXl9nmpdlyqSsVpoXXHEhK2bKcaCVoHMj2xw0IigUuphpidgWq1yydqUAqrJVVSmkEfvk-M93jH0dMKbm2Q9hbBMbwXmZj_xyNapO_lQ6-BgDmqYP9gXCpuGs-QHe_ABv_oGLb9bQdfg</recordid><startdate>20240101</startdate><enddate>20240101</enddate><creator>Campagnolo, Davide</creator><creator>Cattaneo, Andrea</creator><creator>Iodice, Simona</creator><creator>Favero, Chiara</creator><creator>Lioi, Simone</creator><creator>Boniardi, Luca</creator><creator>Borghi, Francesca</creator><creator>Fanti, Giacomo</creator><creator>Keller, Marta</creator><creator>Rovelli, Sabrina</creator><creator>Zellino, Carolina</creator><creator>De Vito, Giovanni</creator><creator>Spinazzè, Andrea</creator><creator>Fustinoni, Silvia</creator><creator>Bollati, Valentina</creator><creator>Cavallo, Domenico M.</creator><general>Hindawi Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>8C1</scope><scope>8FD</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-5594-8761</orcidid><orcidid>https://orcid.org/0000-0002-3953-1197</orcidid><orcidid>https://orcid.org/0000-0003-0371-3164</orcidid><orcidid>https://orcid.org/0000-0003-3608-7964</orcidid><orcidid>https://orcid.org/0000-0003-3452-2803</orcidid><orcidid>https://orcid.org/0000-0002-3728-839X</orcidid><orcidid>https://orcid.org/0000-0002-2962-7259</orcidid><orcidid>https://orcid.org/0000-0002-6403-5101</orcidid><orcidid>https://orcid.org/0000-0002-0370-9598</orcidid><orcidid>https://orcid.org/0000-0002-2836-6106</orcidid><orcidid>https://orcid.org/0000-0001-6634-2394</orcidid><orcidid>https://orcid.org/0000-0001-6059-1306</orcidid><orcidid>https://orcid.org/0000-0003-1853-2999</orcidid><orcidid>https://orcid.org/0000-0002-0287-7338</orcidid></search><sort><creationdate>20240101</creationdate><title>Effects of the Emissions of Vehicles Ahead on In‐Car Exposure to Traffic‐Related Air Pollutants: A Multiple Statistical Analysis Approach</title><author>Campagnolo, Davide ; Cattaneo, Andrea ; Iodice, Simona ; Favero, Chiara ; Lioi, Simone ; Boniardi, Luca ; Borghi, Francesca ; Fanti, Giacomo ; Keller, Marta ; Rovelli, Sabrina ; Zellino, Carolina ; De Vito, Giovanni ; Spinazzè, Andrea ; Fustinoni, Silvia ; Bollati, Valentina ; Cavallo, Domenico M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c188t-449bc171613490f80f8ad4ac5f4d5aceea6e3c72c4eed7b540db6aa98d69834f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Air pollution</topic><topic>Carbon</topic><topic>Emissions</topic><topic>Indoor air quality</topic><topic>Mortality</topic><topic>Nitrogen dioxide</topic><topic>Outdoor air quality</topic><topic>Pollutants</topic><topic>Statistical analysis</topic><topic>Systematic review</topic><topic>Vehicle emissions</topic><topic>Vehicles</topic><topic>VOCs</topic><topic>Volatile organic compounds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Campagnolo, Davide</creatorcontrib><creatorcontrib>Cattaneo, Andrea</creatorcontrib><creatorcontrib>Iodice, Simona</creatorcontrib><creatorcontrib>Favero, Chiara</creatorcontrib><creatorcontrib>Lioi, Simone</creatorcontrib><creatorcontrib>Boniardi, Luca</creatorcontrib><creatorcontrib>Borghi, Francesca</creatorcontrib><creatorcontrib>Fanti, Giacomo</creatorcontrib><creatorcontrib>Keller, Marta</creatorcontrib><creatorcontrib>Rovelli, Sabrina</creatorcontrib><creatorcontrib>Zellino, Carolina</creatorcontrib><creatorcontrib>De Vito, Giovanni</creatorcontrib><creatorcontrib>Spinazzè, Andrea</creatorcontrib><creatorcontrib>Fustinoni, Silvia</creatorcontrib><creatorcontrib>Bollati, Valentina</creatorcontrib><creatorcontrib>Cavallo, Domenico M.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest Central (Alumni Edition)</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>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</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>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>Environment Abstracts</collection><jtitle>Indoor air</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Campagnolo, Davide</au><au>Cattaneo, Andrea</au><au>Iodice, Simona</au><au>Favero, Chiara</au><au>Lioi, Simone</au><au>Boniardi, Luca</au><au>Borghi, Francesca</au><au>Fanti, Giacomo</au><au>Keller, Marta</au><au>Rovelli, Sabrina</au><au>Zellino, Carolina</au><au>De Vito, Giovanni</au><au>Spinazzè, Andrea</au><au>Fustinoni, Silvia</au><au>Bollati, Valentina</au><au>Cavallo, Domenico M.</au><au>Yang, Xiaohu</au><au>Xiaohu Yang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Effects of the Emissions of Vehicles Ahead on In‐Car Exposure to Traffic‐Related Air Pollutants: A Multiple Statistical Analysis Approach</atitle><jtitle>Indoor air</jtitle><date>2024-01-01</date><risdate>2024</risdate><volume>2024</volume><issue>1</issue><issn>0905-6947</issn><eissn>1600-0668</eissn><abstract>Traffic‐related air pollutants inside vehicle cabins are often extremely high compared to background pollution concentrations. The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aimed at identifying and quantifying the effect of several exposure determinants on carbon monoxide (CO), equivalent black carbon (eBC), two particulate matter (PM) fractions (PM 0.3–1 and PM 1–2.5 ), and ultrafine particle (UFP) concentrations inside a passenger car cabin. The novelty of this work consists in examining the effects of the emissions of the first vehicle ahead (henceforth called “leading vehicle”) on pollutant concentrations inside the cabin of the following vehicle (i.e., the car that was equipped with the air monitoring devices), with particular emphasis on the role of the leading vehicle characteristics (e.g., emission reduction technologies). The real‐time instrumentation was placed inside the cabin of a petrol passenger car, which was driven by the same operator two times per day on the same route in real driving conditions. The in‐cabin ventilation settings were set as follows: windows closed, air conditioning and recirculation modes off, and the fanned ventilation system on. The measurements were conducted over a total of 10 weekdays during two different seasons (i.e., summer and autumn). A video camera fixed to the windscreen was used to retrieve information about traffic conditions and leading vehicle characteristics through careful video analysis. The associations among pollutant concentrations and their potential determinants were evaluated using generalized estimating equation univariate and multiple models. The results confirmed the significant impact of several well‐known determinants such as seasonality, microclimatic parameters, traffic jam situations, and route characteristics. Moreover, the outcomes shed light on the key role of leading vehicle emissions as determinant factors of the pollutant concentrations inside car cabins. Indeed, in the tested cabin ventilation conditions, it was demonstrated that in‐cabin pollutant concentrations were significantly higher with leading vehicles ahead (from +14.6% to +67.5%) compared to empty road conditions, even though the introduction of newer technologies with better emissions reduction helped mitigate their effect. Additionally, diesel‐fuelled leading vehicles compared to petrol‐fuelled leading vehicles were impactful on in‐cabin CO (−7.2%) and eBC (+45.3%) concentrations. An important effect (+30.4%) on in‐vehicle PM 1–2.5 concentrations was found with heavy‐duty compared to light‐duty leading vehicles. 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subjects | Air pollution Carbon Emissions Indoor air quality Mortality Nitrogen dioxide Outdoor air quality Pollutants Statistical analysis Systematic review Vehicle emissions Vehicles VOCs Volatile organic compounds |
title | Effects of the Emissions of Vehicles Ahead on In‐Car Exposure to Traffic‐Related Air Pollutants: A Multiple Statistical Analysis Approach |
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