The need to verify vehicle emissions in real world operation led to the implementation of Real Driving Emissions (RDE) test procedures, effective since September 2017 for new Euro 6 cars following ...the Commission Regulation (EU) 2016/427, which defines the RDE test conditions and data analysis methods to allow representative results. Main factors addressed by the regulation include the share of driving operation, ambient temperature range, altitude and elevation difference. However, RDE is still debatable since not only boundary conditions but also the evaluation methods and trip selection are being discussed together with a carbon dioxide (CO2) regulation, which is planned to be implemented in the short term.
Thus, this work focuses on analyzing the effect of different data measurement and analysis methods (i.e. cold-operation, road grade, trip selection and driving style) on CO2 and nitrogen oxides (NOx) emissions based on 13 RDE tests performed in the Lisbon Metropolitan Area, Portugal. The tests were conducted by 2 drivers using 5 vehicles. Each driver performed 2 trips per vehicle, one in normal driving and other in aggressive driving. A Portable Emissions Measurement System (PEMS) was used to collect 1 Hz data, which was compared and analyzed using the European Commission (EC) proposed method for RDE tests.
Results show the effects of each parameter such as average difference between drivers (7% in CO2 and 55% in NOx emissions) and between aggressive and normal driving. For road grade, big oscillations happen during the slope profile, which impacts emissions during all trips. Considering cold-operation, CO2 and NOx emissions are, on average, ~25% and 55% higher, respectively, than in hot-operation. These results highlight the need for deeper studies on these factors to assure that RDE tests evolve to a more established certification procedure than laboratorial certifications.
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•Evaluate current European RDE data analysis methods•Assess boundary conditions and driving behavior influence on RDE tests•Quantify the impacts of these factors in terms of CO2 and NOx emissions•Driving behavior leads to variations of up to 7% in CO2 and 55% in NOx emissions•Cold-operation increase CO2 and NOx emissions by 25% and 55% compared to hot-operation
The analysis of vehicle cold start emissions has become an issue of utmost importance since the cold phase occurs mainly in urban context, where most of the population lives. In this sense, this ...research work analyzes and quantifies the impacts of cold start in urban context using naturalistic driving data. Furthermore, an assessment of the influence of ambient temperature on the percentage of time spent on cold start was also performed.
Regarding the impacts of ambient temperature on cold start duration, a higher percentage of time spent on cold start was found for lower ambient temperatures (80% of the time for 0°C and ~50% for 29°C). Results showed that, during cold start, energy consumption is >110% higher than during hot conditions while emissions are up to 910% higher. Moreover, a higher increase on both energy consumption and emissions was found for gasoline vehicles than for diesel vehicles. When assessing the impacts on a city perspective, results revealed that the impacts of cold start increase for more local streets.
The main finding of this study is to provide evidence that a higher increase on emissions occurs on more local streets, where most of the population lives. This kind of knowledge is of particular relevance to urban planners in order to perform an informed definition of public policies and regulations to be implemented in the future, to achieve a cleaner and healthier urban environment.
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•Extensive real world data collection to evaluate vehicle cold start running.•Assess the impacts of cold start running on the city perspective.•Lower average ambient temperatures increases the cold start running duration.•Increase of 110% on energy consumption and up to 910% on emissions for cold start.•The impact of cold start is higher on more densely populated areas.
Considering the role of behavioral and environmental factors on road accidents and traffic intensities, the characterization of vehicle use and driver behavior opens new opportunities for safety ...improvements and energy savings. Thus, the objective of this work was to identify driving behavior patterns for several driving environments (based on street level and weather conditions) from real-world driving data and to analyze how these driving environments influenced driving behavior. The case study for this work was Lisbon, Portugal, where driving data from 47 drivers were collected with on-board data loggers for at least 6 months. The results show that both street level and weather conditions impact driving behavior significantly. However, while for rainy conditions, the results provide evidence that drivers tend to drive more calmly (average speed is 22% lower for heavy rain than without rain, while positive and negative accelerations decrease by 8% and 11%, respectively), when considering the influence of street level more local streets (level 2, 3 and 4 streets) are the ones that present more aggressive driving patterns in terms of acceleration (30–40% increase from level 1 to level 4 streets). This work contribution regards the quantification of the impacts of driving environment on driving behavior, providing evidence that rain conditions significantly affect driving behavior, leading drivers to adjust their driving behavior to the driving environment. However, regarding street level, the differences found in driving behavior seem to be more a consequence of the infrastructure characteristics than an adjustment of driving behavior.
•Assess the impacts of road grade and driving aggressiveness on fuel consumption.•Extensive real world driving data from a sample of 47 drivers.•Road grade and aggressive driving impact fuel ...consumption rates significantly.•Driving aggressiveness correlates with fuel consumption differently across road grades.•The impact of driving aggressiveness tends to be higher on urban streets.
The transportation sector contributes significantly to energy consumption with inherent consequences in terms of emission of local pollutants, which is associated with air quality deterioration. Considering that driving behavior significantly influences fuel consumption, this work goal was to assess how driving aggressiveness is influenced by the type of road and by the road grade, and consequently their impacts on fuel consumption. For that purpose, 47 drivers were monitored in the Lisbon Metropolitan Area during 6 months, allowing building an extensive 1 Hz real world driving database (∼33,000 trips, totalizing 28.9 million seconds). This database provided distinctive and representative data, allowing assessing the impacts on fuel consumption rates. Results showed that both road context and aggressive driving behavior impact fuel consumption rates significantly. However, for non-aggressive driving behavior fuel consumption rates increased more with road grade increments (up to 3 times) than for aggressive driving behavior (up to 2.3 times). Furthermore, this study results demonstrated that aggressiveness influences fuel consumption differently across road grades. Aggressiveness impacts are higher for lower road grades, with increased fuel consumption rates by up to 255%. The key findings associated to this research work are that aggressiveness on roads with lower grades tends to correlate with higher percent increase on fuel consumption for all speed ranges. Moreover, aggressiveness seems to correlate with higher fuel consumption on urban streets. Consequently, a reduction in driving under these conditions can offer significant savings in fuel consumption.
•Development of methodology to assess economic feasibility of EV parking spaces.•NPV break-even is more “easily” reached for higher parking prices.•Reductions of up to 14% with increasing occupancy ...rates were observed.•52–86% Reductions in WTW energy and environmental impacts were obtained.
The transportation sector faces increasing challenges related to energy consumption and local and global emissions profiles. Thus, alternative vehicle technologies and energy pathways are being considered in order to overturn this trend and electric mobility is considered one adequate possibility towards a more sustainable transportation sector.
In this sense, this research work consisted on the development of a methodology to assess the economic feasibility of deploying EV charging stations (Park-EV) by quantifying the tradeoff between economic and energy/environmental impacts for EV parking spaces deployment. This methodology was applied to 4 different cities (Lisbon, Madrid, Minneapolis and Manhattan), by evaluating the influence of parking premium, infrastructure cost and occupancy rates on the investment Net Present Value (NPV). The main findings are that the maximization of the premium and the minimization of the equipment cost lead to higher NPV results. The NPV break-even for the cities considered is more “easily” reached for higher parking prices, namely in the case of Manhattan with the higher parking price profile. In terms of evaluating occupancy rates of the EV parking spaces, shifting from a low usage (LU) to a high usage (HU) scenario represented a reduction in the premium to obtain a NPV=0 of approximately 14% for a 2500€ equipment cost, and, in the case of a zero equipment cost (e.g. financed by the city), a NPV=0 was obtained with approximately a 2% reduction in the parking premium. Moreover, due to the use of electric mobility instead of the average conventional technologies, Well-to-Wheel (WTW) gains for Lisbon, Madrid, Minneapolis and Manhattan were estimated in 58%, 53%, 52% and 75% for energy consumption and 66%, 75%, 62% and 86% for CO2 emissions, respectively.
This research confirms that the success of deploying an EV charging stations infrastructure will be highly dependent on the price the user will have to pay, on the cost of the infrastructure deployed and on the adhesion of the EV users to this kind of infrastructure. These variables are not independent and, consequently, the coordination of public policies and private interest must be promoted in order to reach an optimal solution that does not result in prohibitive costs for the users.
•Extensive real world data collection to evaluate aggressive driving behavior.•Assess the impacts of aggressive driving at a city perspective.•Aggressive driving increases energy consumption by 200% ...and emissions by 330%.•Avoiding aggressive driving can save up to 52.5 k€ on a daily basis.•Higher impacts of aggressive driving occur in more local streets.
This work assesses the impacts of aggressive driving behavior on pollutants emissions and energy consumption at a city level. Furthermore, it performs an economic analysis considering the potential avoided emissions and fuel savings and discusses potential policy measures to address this topic. The results showed that aggressive driving significantly impacts energy consumption and emissions, with energy consumption increasing by more than ∼200% and emissions by 330% for aggressive driving compared to non-aggressive driving (in MJ/km and in g/km, respectively). This increment was found to be even higher for diesel vehicles than for gasoline vehicles. On the contrary, gasoline vehicles showed higher percentages of increase for most emissions (CO, NOx and NO). Results also revealed that aggressive driving impacts are higher for local streets when examining the city level. Moreover, the economic analysis showed that significant cost reductions may be achieved by avoiding aggressive driving, reaching up to 52.5 k€ on a daily basis. In conclusion, this study is of particular relevance to policy makers and urban planners, enabling to obtain a comprehensive overview of the impacts of aggressive driving behaviors at a city level and providing new insights to perform further developments and to assess the feasibility of the implementation of policy measures.
Air quality in urban centers constitutes a challenge ahead for most cities. For this reason, the objective of this research work was to evaluate the impacts of changing traffic-related parameters on ...particulate matter (PM) concentration for several hierarchical street levels using real-world data for the city of Lisbon, Portugal. For that purpose, 2014 data regarding meteorological conditions, traffic volumes, typical vehicle speed, and a vehicle representative of the fleet was used in an air quality dispersion model (CALINE4). The available data allowed building a baseline case for several streets that are representative of the traffic circulation conditions in Lisbon, which was compared with different scenarios: hypothetical introduction of a cordon toll (S1.1 to S1.4) and the implementation of a low emission zone (S2.1 and 2.2). The results indicate that reductions on PM
2.5
concentrations from 5 to 42 % may be obtained from the implementation of the scenarios. Overall, this study demonstrates that modeling tools based on real-world data can provide a good approach to study urban policies regarding traffic-related PM exposure. Additionally, implementation of such measures requires an integrated strategy that enables proper enforcement and monitoring, as well as an adequate management of traffic flows between the implementation boundaries.
Air quality in urban centers constitutes a challenge ahead for most cities. For this reason, the objective of this research work was to evaluate the impacts of changing traffic-related parameters on ...particulate matter (PM) concentration for several hierarchical street levels using real-world data for the city of Lisbon, Portugal. For that purpose, 2014 data regarding meteorological conditions, traffic volumes, typical vehicle speed, and a vehicle representative of the fleet was used in an air quality dispersion model (CALINE4). The available data allowed building a baseline case for several streets that are representative of the traffic circulation conditions in Lisbon, which was compared with different scenarios: hypothetical introduction of a cordon toll (S1.1 to S1.4) and the implementation of a low emission zone (S2.1 and 2.2). The results indicate that reductions on PM2.5 concentrations from 5 to 42 % may be obtained from the implementation of the scenarios. Overall, this study demonstrates that modeling tools based on real-world data can provide a good approach to study urban policies regarding traffic-related PM exposure. Additionally, implementation of such measures requires an integrated strategy that enables proper enforcement and monitoring, as well as an adequate management of traffic flows between the implementation boundaries.
Air quality in urban centers constitutes a challenge ahead for most cities. For this reason, the objective of this research work was to evaluate the impacts of changing traffic-related parameters on ...particulate matter (PM) concentration for several hierarchical street levels using real-world data for the city of Lisbon, Portugal. For that purpose, 2014 data regarding meteorological conditions, traffic volumes, typical vehicle speed, and a vehicle representative of the fleet was used in an air quality dispersion model (CALINE4). The available data allowed building a baseline case for several streets that are representative of the traffic circulation conditions in Lisbon, which was compared with different scenarios: hypothetical introduction of a cordon toll (S1.1 to S1.4) and the implementation of a low emission zone (S2.1 and 2.2). The results indicate that reductions on PM sub(2.5) concentrations from 5 to 42 % may be obtained from the implementation of the scenarios. Overall, this study demonstrates that modeling tools based on real-world data can provide a good approach to study urban policies regarding traffic-related PM exposure. Additionally, implementation of such measures requires an integrated strategy that enables proper enforcement and monitoring, as well as an adequate management of traffic flows between the implementation boundaries.
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