Carbon emissions from road transport are one of the main issues related to modern transport planning. To address them adequately, the acquisition of reliable data about traffic flow is an essential prerequisite. However, the large quantity and the heterogeneity of available information often cause problems; missing or incomplete data are one of the most critical aspects. This paper discusses how technology handles imperfect information in order to obtain more accurate quantification of CO2 emissions. First, an analysis of single estimators and combination models is provided, highlighting their main characteristics. Then, the TANINO model (Tool for the Analysis of Non-conservative Carbon Emissions In TraNspOrt) is presented, jointly developed at the University of Seville and at the IUAV University of Venice. It consists of two different modules: the first is a combination model that optimizes the results of three traffic flow single estimators, while the second is a macro-model of carbon evaluation, which takes into account road infrastructure, vehicle type and traffic conditions. TANINO is then tested to calculate CO2 emissions along the ring road of the Spanish city of Seville, showing its more efficient performance, compared to the single estimators normally adopted for such aims. Transport planning can benefit from the adequate knowledge of traffic flows and related CO2 emissions, since it allows a more reliable monitoring of the progresses granted by specific carbon policies
Assessing carbon emissions from road transport through traffic flow estimators / Nocera, Silvio; Ruiz-Alarcón-Quintero, Cayetano; Cavallaro, Federico. - In: TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES. - ISSN 0968-090X. - 95:(2018), pp. 125-148. [10.1016/j.trc.2018.07.020]
Assessing carbon emissions from road transport through traffic flow estimators
Nocera, Silvio;Cavallaro, Federico
2018
Abstract
Carbon emissions from road transport are one of the main issues related to modern transport planning. To address them adequately, the acquisition of reliable data about traffic flow is an essential prerequisite. However, the large quantity and the heterogeneity of available information often cause problems; missing or incomplete data are one of the most critical aspects. This paper discusses how technology handles imperfect information in order to obtain more accurate quantification of CO2 emissions. First, an analysis of single estimators and combination models is provided, highlighting their main characteristics. Then, the TANINO model (Tool for the Analysis of Non-conservative Carbon Emissions In TraNspOrt) is presented, jointly developed at the University of Seville and at the IUAV University of Venice. It consists of two different modules: the first is a combination model that optimizes the results of three traffic flow single estimators, while the second is a macro-model of carbon evaluation, which takes into account road infrastructure, vehicle type and traffic conditions. TANINO is then tested to calculate CO2 emissions along the ring road of the Spanish city of Seville, showing its more efficient performance, compared to the single estimators normally adopted for such aims. Transport planning can benefit from the adequate knowledge of traffic flows and related CO2 emissions, since it allows a more reliable monitoring of the progresses granted by specific carbon policiesFile | Dimensione | Formato | |
---|---|---|---|
1-s2.0-S0968090X18306430-main.pdf
accesso riservato
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
3.61 MB
Formato
Adobe PDF
|
3.61 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2786984