Publications
102 results found
Anastasiadis E, Angeloudis P, Ainalis D, et al., 2021, On the selection of charging facility locations for EV-based ride-hailing services: a computational case study, Sustainability, Vol: 13, ISSN: 2071-1050
The uptake of Electric Vehicles (EVs) is rapidly changing the landscape of urban mobility services. Transportation Network Companies (TNCs) have been following this trend by increasing the number of EVs in their fleets. Recently, major TNCs have explored the prospect of establishing privately owned charging facilities that will enable faster and more economic charging. Given the scale and complexity of TNC operations, such decisions need to consider both the requirements of TNCs and local planning regulations. Therefore, an optimisation approach is presented to model the placement of CSs with the objective of minimising the empty time travelled to the nearest CS for recharging as well as the installation cost. An agent based simulation model has been set in the area of Chicago to derive the recharging spots of the TNC vehicles, and in turn derive the charging demand. A mathematical formulation for the resulting optimisation problem is provided alongside a genetic algorithm that can produce solutions for large problem instances. Our results refer to a representative set of the total data for Chicago and indicate that nearly 180 CSs need to be installed to handle the demand of a TNC fleet of 3000 vehicles.
Ma L, Graham DJ, Stettler MEJ, 2021, Air quality impacts of new public transport provision: A causal analysis of the Jubilee Line Extension in London, Atmospheric Environment, Vol: 245, Pages: 118025-118025, ISSN: 1352-2310
Public transport is commonly associated with benefits such as reducing road traffic congestion and improving air quality. This paper focuses on evaluating the causal impact of a new public transport provision in London, the Jubilee Line Extension (JLE) in 1999, on air quality. Using meteorological normalisation and a regression discontinuity design with time as the forcing variable, we show that the JLE led to only small changes in air pollution at some specific locations; detectable changes in NOx, NO2, and O3 concentrations were found at 63%, 43% and 29% of air pollution monitoring sites, respectively. For those sites where a change in pollution was detected, the responses ranged from −2% to +1% for NO2 and -1% to 0% for O3. We calculate that the long-run effects are greater, ranging from −11% to +3% for NO2 and from −2% to +2% for O3 at sites that showed a response to the JLE. Aggregating across all sites in London for a city-wide effect, both short and long-run effects were less than 1% or insignificant. We find statistically significant increases in NO2 and O3 concentrations at some background sites, but the magnitude of effect is within +1% in the short-run and +3% in the long-run. Our analysis shows that the effect of the JLE on air pollution in some areas was greater than others, however across London the effect was small and this indicates that public transport provision on its own is not an effective strategy to improve air quality.
Ye Q, Stebbins SM, Feng Y, et al., 2020, Intelligent management of on-street parking provision for the autonomous vehicles era, 23rd IEEE International Conference on Intelligent Transportation Systems (ITSC), Publisher: IEEE, Pages: 1-7, ISSN: 2153-0009
The increasing degree of connectivity between vehicles and infrastructure, and the impending deployment of autonomous vehicles (AV) in urban streets, presents unique opportunities and challenges regarding the on-street parking provision for AVs. This study develops a novel simulation-optimisation approach for intelligent curbside management, based on a metaheuristic technique. The hybrid method balances curb lanes for driving or parking, aiming to minimise the average traffic delay. The model is tested using an idealised grid layout with a range of flow rates and parking policies. Results demonstrate delay decreased by 9%-27% from the benchmark case. Additionally, the traffic delay distribution shows the trade-offs between expanding road capacity and minimising traffic demand through curb management, indicating the interplay between curb parking and traffic management in the AV era.
Whyte J, Mijic A, Myers RJ, et al., 2020, A research agenda on systems approaches to infrastructure, Journal of Civil Engineering and Environmental Systems, Vol: 37, Pages: 214-233, ISSN: 1029-0249
At a time of system shocks, significant underlying challenges are revealed in current approaches to delivering infrastructure, including that infrastructure users in many societies feel distant from nature. We set out a research agenda on systems approaches to infrastructure, drawing on ten years of interdisciplinary work on operating infrastructure, infrastructure interventions and lifecycles. Research insights and directions on complexity, systems integration, data-driven systems engineering, infrastructure life-cycles, and the transition towards zero pollution are summarised. This work identifies a need to better understand the natural and societal impacts of infrastructure interventions under uncertainty. We argue for a change in current approaches to infrastructure: starting from the natural environment and its resources, encompassing societal use of infrastructure and the supporting infrastructure assets and services. To support such proposed new systems approaches to infrastructure, researchers need to develop novel modelling methods, forms of model integration, and multi-criteria indicators.
Schroeder AK, Haugen MJ, Stettler MEJ, et al., 2020, Using Computer Vision with Instantaneous Vehicle Emissions Modelling, Pages: 89-94
Air pollution and in particular PM2.5 emissions are a major problem worldwide. Road transport is a significant contributor to PM2.5 emissions in urban areas and as such it is important to understand and be able to accurately model the effects of vehicles on PM2.5 emissions. In this paper a computer vision algorithm is introduced which is able to extract vehicle trajectories from video footage. The algorithm has a 100% accuracy for overall total vehicle counting. Comparing the speeds predicted by the computer vision script to manually following a single vehicle feature on the video file, the average relative speed accuracy is 2.7% at a 1 Hz time resolution. Using these vehicle trajectories in an instantaneous vehicle emissions model and also as input to COPERT v5, tailpipe PM2.5 emissions were estimated and compared to on-road measurements. It was shown that a local sensor is not sufficient to determine vehicle tailpipe emissions due to the influence of meteorological conditions and other emission sources. Combining computer vision with an instantaneous vehicle emissions model is a useful method to evaluate changes in emissions caused by transport policies.
Wu C, Wang Z, Hu S, et al., 2020, An automated machine-learning approach for road pothole detection using smartphone sensor data, Sensors, Vol: 20, Pages: 1-23, ISSN: 1424-8220
Road surface monitoring and maintenance are essential for driving comfort, transport safety and preserving infrastructure integrity. Traditional road condition monitoring is regularly conducted by specially designed instrumented vehicles, which requires time and money and is only able to cover a limited proportion of the road network. In light of the ubiquitous use of smartphones, this paper proposes an automatic pothole detection system utilizing the built-in vibration sensors and global positioning system receivers in smartphones. We collected road condition data in a city using dedicated vehicles and smartphones with a purpose-built mobile application designed for this study. A series of processing methods were applied to the collected data, and features from different frequency domains were extracted, along with various machine-learning classifiers. The results indicated that features from the time and frequency domains outperformed other features for identifying potholes. Among the classifiers tested, the Random Forest method exhibited the best classification performance for potholes, with a precision of 88.5% and recall of 75%. Finally, we validated the proposed method using datasets generated from different road types and examined its universality and robustness.
Le Cornec CMA, Molden N, van Reeuwijk M, et al., 2020, Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx: Insights from machine learning techniques, Science of The Total Environment, Vol: 737, Pages: 1-13, ISSN: 0048-9697
Accurate instantaneous vehicle emissions models are vital for evaluating the impacts of road transport on air pollution at high temporal and spatial resolution. In this study, we apply machine learning techniques to a dataset of 70 diesel vehicles tested in real-world driving conditions to: (i) cluster vehicles with similar emissions performance, and (ii) model instantaneous emissions. The application of dynamic time warping and clustering analysis by NOx emissions resulted in 17 clusters capturing 88% of trips in the dataset. We show that clustering effectively groups vehicles with similar emissions profiles, however no significant correlation between emissions and vehicle characteristics (i.e. engine size, vehicle weight) were found. For each cluster, we evaluate three instantaneous emissions models: a look-up table (LT) approach, a non-linear regression (NLR) model and a neural network multi-layer perceptron (MLP) model. The NLR model provides accurate instantaneous NOx predictions, on par with the MLP: relative errors in prediction of emission factors are below 20% for both models, average fractional biases are −0.01 (s.d. 0.02) and −0.0003 (s.d. 0.04), and average normalised mean squared errors are 0.25 (s.d. 0.14) and 0.29 (s.d. 0.16), for the NLR and MLP models respectively. However, neural networks are better able to deal with vehicles not belonging to a specific cluster. The new models that we present rely on simple inputs of vehicle speed and acceleration, which could be extracted from existing sources including traffic cameras and vehicle tracking devices, and can therefore be deployed immediately to enable fast and accurate prediction of vehicle NOx emissions. The speed and the ease of use of these new models make them an ideal operational tool for policy makers aiming to build emission inventories or evaluate emissions mitigation strategies.
Teoh R, Schumann U, Stettler MEJ, 2020, Beyond contrail avoidance: efficacy of flight altitude changes to minimise contrail climate forcing, Aerospace, Vol: 7, Pages: 121-121, ISSN: 0305-0831
Contrail cirrus introduce a short-lived but significant climate forcing that could be mitigated by small changes in aircraft cruising altitudes. This paper extends a recent study to evaluate the efficacy of several vertical flight diversion strategies to mitigate contrail climate forcing, and estimates impacts to air traffic management (ATM). We use six one-week periods of flight track data in the airspace above Japan (between May 2012 and March 2013), and simulate contrails using the contrail cirrus prediction model (CoCiP). Previous studies have predominantly optimised a diversion of every contrail-forming flight to minimise its formation or radiative forcing. However, our results show that these strategies produce a suboptimal outcome because most contrails have a short lifetime, and some have a cooling effect. Instead, a strategy that reroutes 15.3% of flights to avoid long-lived warming contrails, while allowing for cooling contrails, reduces the contrail energy forcing (EFcontrail) by 105% [91.8, 125%] with a total fuel penalty of 0.70% [0.66, 0.73%]. A minimum EFtotal strategy (contrails + CO2), diverting 20.1% of flights, reduces the EFcontrail by the same magnitude but also reduces the total fuel consumption by 0.40% [0.31, 0.47%]. For the diversion strategies explored, between 9% and 14% of diversions lead to a loss of separation standards between flights, demonstrating a modest scale of ATM impacts. These results show that small changes in flight altitudes are an opportunity for aviation to significantly and rapidly reduce its effect on the climate.
Karamanis R, Anastasiadis E, Angeloudis P, et al., 2020, Assignment and pricing of shared rides in ride-sourcing using combinatorial double auctions, IEEE Transactions on Intelligent Transportation Systems, Vol: 22, Pages: 5648-5659, ISSN: 1524-9050
Transportation Network Companies employ dynamic pricing methods at periods of peak travel to incentivise driver participation and balance supply and demand for rides. Surge pricing multipliers are commonly used and are applied following demand and estimates of customer and driver trip valuations. Combinatorial double auctions have been identified as a suitable alternative, as they can achieve maximum social welfare in the allocation by relying on customers and drivers stating their valuations. A shortcoming of current models, however, is that they fail to account for the effects of trip detours that take place in shared trips and their impact on the accuracy of pricing estimates. To resolve this, we formulate a new shared-ride assignment and pricing algorithm using combinatorial double auctions. We demonstrate that this model is reduced to a maximum weighted independent set model, which is known to be APX-hard. A fast local search heuristic is also presented, which is capable of producing results that lie within 10% of the exact approach for practical implementations. Our proposed algorithm could be used as a fast and reliable assignment and pricing mechanism of ride-sharing requests to vehicles during peak travel times.
Teoh R, Schumann U, Majumdar A, et al., 2020, Mitigating the climate forcing of aircraft contrails by small-scale diversions and technology adoption, Environmental Science and Technology (Washington), Vol: 54, Pages: 2941-2950, ISSN: 0013-936X
The climate forcing of contrails and induced-cirrus cloudiness is thought to be comparable to the cumulative impacts of aviation CO2 emissions. This paper estimates the impact of aviation contrails on climate forcing for flight track data in Japanese airspace and propagates uncertainties arising from meteorology and aircraft black carbon (BC) particle number emissions. Uncertainties in the contrail age, coverage, optical properties, radiative forcing, and energy forcing (EF) from individual flights can be 2 orders of magnitude larger than the fleet-average values. Only 2.2% [2.0, 2.5%] of flights contribute to 80% of the contrail EF in this region. A small-scale strategy of selectively diverting 1.7% of the fleet could reduce the contrail EF by up to 59.3% [52.4, 65.6%], with only a 0.014% [0.010, 0.017%] increase in total fuel consumption and CO2 emissions. A low-risk strategy of diverting flights only if there is no fuel penalty, thereby avoiding additional long-lived CO2 emissions, would reduce contrail EF by 20.0% [17.4, 23.0%]. In the longer term, widespread use of new engine combustor technology, which reduces BC particle emissions, could achieve a 68.8% [45.2, 82.1%] reduction in the contrail EF. A combination of both interventions could reduce the contrail EF by 91.8% [88.6, 95.8%].
Yu J, Stettler MEJ, Angeloudis P, et al., 2020, Urban network-wide traffic speed estimation with massive ride-sourcing GPS traces, Transportation Research Part C: Emerging Technologies, Vol: 112, Pages: 136-152, ISSN: 0968-090X
The ability to obtain accurate estimates of city-wide urban traffic patterns is essential for the development of effective intelligent transportation systems and the efficient operation of smart mobility platforms. This paper focuses on the network-wide traffic speed estimation, using trajectory data generated by a city-wide fleet of ride-sourcing vehicles equipped with GPS-capable smartphones. A cell-based map-matching technique is proposed to link vehicle trajectories with road geometries, and to produce network-wide spatio-temporal speed matrices. Data limitations are addressed using the Schatten p-norm matrix completion algorithm, which can minimize speed estimation errors even with high rates of data unavailability. A case study using data from Chengdu, China, demonstrates that the algorithm performs well even in situations involving continuous data loss over a few hours, and consequently, addresses large-scale network-wide traffic state estimation problems with missing data, while at the same time outperforming other data recovery techniques that were used as benchmarks. Our approach can be used to generate congestion maps that can help monitor and visualize traffic dynamics across the network, and therefore form the basis for new traffic management, proactive congestion identification, and congestion mitigation strategies.
Langshaw L, Ainalis D, Acha Izquierdo S, et al., 2020, Environmental and economic analysis of liquefied natural gas (LNG) for heavy goods vehicles in the UK: A Well-to-Wheel and total cost of ownership evaluation, Energy Policy, Vol: 137, Pages: 1-15, ISSN: 0301-4215
This paper evaluates the environmental and economic performance of liquefied natural gas (LNG) as a transition fuel to replace diesel in heavy goods vehicles (HGVs). A Well-to-Wheel (WTW) assessment based on real-world HGV drive cycles is performed to determine the life-cycle greenhouse gas (GHG) emissions associated with LNG relative to diesel. The analysis is complemented with a probabilistic approach to determine the total cost of ownership (TCO) across a range of scenarios. The methodologies are validated via a case study of vehicles operating in the UK, using data provided by a large food retailer. The spark-ignited LNG vehicles under study were observed to be 18% less energy efficient than their diesel counterparts, leading to a 7% increase in WTW GHG emissions. However, a reduction of up to 13% is feasible if LNG vehicles reach parity efficiency with diesel. Refuelling at publicly available stations enabled a 7% TCO saving in the nominal case, while development of private infrastructure incurred net costs. The findings of this study highlight that GHG emission reductions from LNG HGVs will only be realised if there are vehicle efficiency improvements, while the financial case for operators is positive only if a publicly accessible refuelling network is available.
Speirs J, Balcombe P, Blomerus P, et al., 2020, Natural gas fuel and greenhouse gas emissions in trucks and ships, Progress in Energy, Vol: 2, Pages: 012002-012002
Yang L, Zhang L, Stettler MEJ, et al., 2020, Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate, Sustainable Cities and Society, Vol: 52, ISSN: 2210-6707
Traditional urban and transport infrastructure planning that emphasized motorized transport has fractured public space systems and worsened environmental quality, leading to a decrease in active travel. A novel multiscale simulation method for supporting an integrated transportation infrastructure and public space design is presented in this paper. This method couples a mesoscale agent-based traffic prediction model, traffic-related emission calculation, microclimate simulations, and human thermal comfort assessment. In addition, the effects of five urban design strategies on traffic pollution and pedestrian level microclimate are evaluated (i.e., a “two-fold” evaluation). A case study in Beijing, China, is presented utilizing the proposed urban modeling-design framework to support the assessment of a series of transport infrastructure and public space scenarios, including the Baseline scenario, a System-Internal Integration scenario, and two External Integration scenarios. The results indicate that the most effective way of achieving an environmentally- and pedestrian- friendly urban design is to concentrate on both the integration within the transport infrastructure and public space system and the mitigation of the system externalities (e.g., air pollution and heat exhaustion). It also demonstrates that the integrated blue-green approach is a promising way of improving local air quality, micro-climatic conditions, and human comfort.
Brito TLF, Islam T, Stettler M, et al., 2019, Transitions between technological generations of alternative fuel vehicles in Brazil, Energy Policy, Vol: 134, Pages: 110915-110915, ISSN: 0301-4215
The transportation sector is responsible for nearly a quarter of greenhouse gases emissions (GHG); thus, incisive policies are necessary to mitigate the sector’s effect on climate change. Promoting alternative fuel vehicles (AFV) is an essential strategy to reduce GHG emissions in the short term. Here, we study the effects of governmental incentives on the diffusion of ethanol and flex-fuel vehicle technologies in Brazil. We use a multi-generation diffusion model which assumes that new technologies introduce fresh market potential for adopters as well as upgraders from established technologies. Our analysis indicates that tax rates affected the adoption of both gasoline and ethanol technology, but for flex vehicles, the effect of taxation is not significant. The effect of fuel price shocks during the 1990s meant that the introduction of ethanol technology made no significant impact on market potential and a negative word-of-mouth effect contributed to the technology’s failure. In contrast, the introduction of flex technology led to almost a doubling of total market potential. As policy suggestions, we emphasise the importance of tax reduction in addition to promoting versatile technologies, which insulate consumers against price fluctuations.
Woodward H, Stettler M, Pavlidis D, et al., 2019, A large eddy simulation of the dispersion of traffic emissions by moving vehicles at an intersection, Atmospheric Environment, Vol: 215, Pages: 1-16, ISSN: 1352-2310
Traffic induced flow within urban areas can have a significant effect on pollution dispersion, particularly for traffic emissions. Traffic movement results in increased turbulence within the street and the dispersion of pollutants by vehicles as they move through the street. In order to accurately model urban air quality and perform meaningful exposure analysis at the microscale, these effects cannot be ignored. In this paper we introduce a method to simulate traffic induced dispersion at high resolution. The computational fluid dynamics software, Fluidity, is used to model the moving vehicles through a domain consisting of an idealised intersection. A multi-fluid method is used where vehicles are represented as a second fluid which displaces the air as it moves through the domain. The vehicle model is coupled with an instantaneous emissions model which calculates the emission rate of each vehicle at each time step. A comparison is made with a second Fluidity model which simulates the traffic emissions as a line source and does not include moving vehicles. The method is used to demonstrate how moving vehicles can have a significant effect on street level concentration fields and how large vehicles such as buses can also cause acute high concentration events at the roadside which can contribute significantly to overall exposure.
Grylls T, Le Cornec CMA, Salizzoni P, et al., 2019, Evaluation of an operational air quality model using large-eddy simulation, Atmospheric Environment: X, Vol: 3, ISSN: 2590-1621
The large-eddy simulation (LES) model uDALES is used to evaluate the predictive skill of the operational air quality model SIRANE. The use of LES in this study presents a novel approach to air quality model evaluation, avoiding sources of uncertainty and providing numerical control that permits systematic analysis of targeted parametrisations and assumptions.A case study is conducted over South Kensington, London with the morphology, emissions, meteorological conditions and boundary conditions carefully matched in both models. The dispersion of both inert (NOx) and reactive (NO, NO2 and O3) pollutants under neutral, steady-state conditions is simulated for a south-westerly and westerly wind direction. A quantitative comparison between the two models is performed using statistical indices (the fractional bias, FB, the normalised mean squared error, NMSE, and the fraction in a factor of 2, FAC2).SIRANE is shown to successfully capture the dominant trends with respect to canyon-averaged concentrations of inert NOx (FB = -0.08, NMSE = 0.08 and FAC2 = 1.0). The prediction of along-canyon velocities is shown to exhibit sources of systematic error dependant on the angle of incidence of the mean wind (FB = -0.18). The assumption of photostationarity within SIRANE (deviations from equilibrium of up to 170% exist close to busy roads) is also identified as a significant source of systematic bias resulting in over- and underpredictions of NO2 (FB = -0.18) and O3 (FB = 0.14) respectively. The validity of the assumed uniform in-canyon concentration is assessed by analysing the pedestrian, leeward and windward concentrations resolved in uDALES. The use of canyon-averaged concentrations to predict pedestrian level exposure is shown to result in significant underestimations. Linear regression is used to effectively capture the relationship between pedestrian- and canyon-averaged concentrations in uDALES. Correction factors are derived (m ≈ 1.62 and R 2 = 0.92 for inert NOx) th
Achurra-Gonzalez PE, Angeloudis P, Goldbeck N, et al., 2019, Evaluation of port disruption impacts in the global liner shipping network, Journal of Shipping and Trade, Vol: 4, Pages: 1-21, ISSN: 2364-4575
The global container shipping network is vital to international trade. Current techniques for its vulnerability assessment are constrained due to the lack of historical disruption data and computational limitations due to typical network sizes. We address these modelling challenges by developing a new framework, composed by a game-theoretic attacker-defender model and a cost-based container assignment model that can identify systemic vulnerabilities in the network. Given its focus on logic and structure, the proposed framework has minimal input data requirements and does not rely on the presence of extensive historical disruption data. Numerical implementations are carried in a global-scale liner network where disruptions occur in Europe’s main container ports. Model outputs are used to establish performance baselines for the network and illus-trate the differences in regional vulnerability levels and port criticality rankings with different disruption magnitudes and flow diversion strategies. Sensitivity analysis of these outputs identifies network compo-nents that are more susceptible to lower levels of disruption which are more common in practice and to assess the effectiveness of component-level interventions seeking to increase the resilience of the system.
Teoh R, Stettler MEJ, Majumdar A, et al., 2019, A methodology to relate black carbon particle number and mass emissions, Journal of Aerosol Science, Vol: 132, Pages: 44-59, ISSN: 0021-8502
Black carbon (BC) particle number (PN) emissions from various sources contribute to the deterioration of air quality, adverse health effects, and anthropogenic climate change. This paper critically reviews different fractal aggregate theories to develop a new methodology that relates BC PN and mass concentrations (or emissions factors). The new methodology, named as the fractal aggregate (FA) model is validated with measurements from three different BC emission sources: an internal combustion engine, a soot generator, and two aircraft gas turbine engines at ground and cruise conditions. Validation results of the FA model show that R 2 values range from 0.44 to 0.95, while the Normalised Mean Bias is between −27.7% and +26.6%. The model estimates for aircraft gas turbines represent a significant improvement compared to previous methodologies used to estimate aviation BC PN emissions, which relied on simplified assumptions. Uncertainty and sensitivity analyses show that the FA model estimates have an asymmetrical uncertainty bound (−54%,+103%) at a 95% confidence interval for aircraft gas turbine engines and are most sensitive to uncertainties in the geometric standard deviation of the BC particle size distribution. Given the improved performance in estimating BC PN emissions from various sources, we recommend the implementation of the FA model in future health and climate assessments, where the impacts of PN are significant.
Speirs J, Balcombe P, Blomerus P, et al., 2019, Can natural gas reduce emissions from transport?: Heavy goods vehicles and shipping
Chen T, Liu YH, Li L, et al., 2019, Scenario analysis of CO2 emission peak in road transport of Chinese provinces: A case study of Guangdong, 5th International Conference on Transportation Information and Safety (ICTIS), Publisher: IEEE, Pages: 888-896
Karamanis R, Angeloudis P, Sivakumar A, et al., 2018, Dynamic pricing in one-sided autonomous ride-sourcing markets, 21st IEEE International Conference on Intelligent Transportation Systems (ITSC), Publisher: IEEE, Pages: 3645-3650, ISSN: 2153-0009
Dynamic pricing has been used by Transportation Network Companies (TNCs) to achieve a balance between the volume of ride requests with numbers of available drivers on two-sided TNC markets. Given the desire to reduce operating costs and the emergence of Autonomous Vehicles (AVs), the introduction of TNC-owned AV fleets could convert such services into one-sided markets, where operators have full control of service supply. In this paper we investigate the impact of utility-based dynamic pricing for Autonomous TNCs (ATNCs) in one-sided markets. We test the method using an Agent-Based Model (ABM) of Greater London in conditions of monopoly and competition, focusing on a statically priced ATNC service that offers a mix of private and shared ride services. Public transport is considered as an alternative mode of transportation in both scenarios. Results indicate that in monopoly, dynamic pricing provides higher revenues than static pricing at non-peak hours when average waiting times are low. On the contrary, in competition, dynamic pricing is superior at peak hours where increased waiting times are observed, thus increasing the value of low waiting time rides. Overall, in both market structures, it is found that shared trips are more popular in dynamic pricing compared to static pricing.
Popoola OAM, Carruthers D, Lad C, et al., 2018, Use of networks of low cost air quality sensors to quantify air quality in urban settings, Atmospheric Environment, Vol: 194, Pages: 58-70, ISSN: 1352-2310
Low cost sensors are becoming increasingly available for studying urban air quality. Here we show how such sensors, deployed as a network, provide unprecedented insights into the patterns of pollutant emissions, in this case at London Heathrow Airport (LHR). Measurements from the sensor network were used to unequivocally distinguish airport emissions from long range transport, and then to infer emission indices from the various airport activities. These were used to constrain an air quality model (ADMS-Airport), creating a powerful predictive tool for modelling pollutant concentrations. For nitrogen dioxide (NO2), the results show that the non-airport component is the dominant fraction (∼75%) of annual NO2 around the airport and that despite a predicted increase in airport related NO2 with an additional runway, improvements in road traffic fleet emissions are likely to more than offset this increase. This work focusses on London Heathrow Airport, but the sensor network approach we demonstrate has general applicability for a wide range of environmental monitoring studies and air pollution interventions.
Koudis GS, Hu SJ, Majumdar A, et al., 2018, The impact of single engine taxiing on aircraft fuel consumption and pollutant emissions, Aeronautical Journal, Vol: 122, Pages: 1967-1984, ISSN: 0001-9240
Optimisation of aircraft ground operations to reduce airport emissions can reduce resultant local air quality impacts. Single engine taxiing (SET), where only half of the installed number of engines are used for the majority of the taxi duration, offers the opportunity to reduce fuel consumption, and emissions of NOX, CO and HC. Using 3510 flight data records, this paper develops a model for SET operations and presents a case study of London Heathrow, where we show that SET is regularly implemented during taxi-in. The model predicts fuel consumption and pollutant emissions with greater accuracy than previous studies that used simplistic assumptions. Without SET during taxi-in, fuel consumption and pollutant emissions would increase by up to 50%. Reducing the time before SET is initiated to the 25th percentile of recorded values would reduce fuel consumption and pollutant emissions by 7–14%, respectively, relative to current operations. Future research should investigate the practicalities of reducing the time before SET initialisation so that additional benefits of reduced fuel loadings, which would decrease fuel consumption across the whole flight, can be achieved.
Ainalis D, Achurra-Gonzalez P, Gaudin A, et al., 2018, Ultra-Capacitor based kinetic energy recovery system for heavy goods vehicles, 15th International Symposium on Heavy Vehicle Transport Technology, Publisher: International Forum for Heavy Vehicle Transport & Technology
The Climate Change Act 2008 commits the UK to reduce the Greenhouse Gas emissions by 80% by 2050 relative to 1990 levels. While Heavy Goods Vehicles and buses contribute about 4% of the total Greenhouse Gas emissions in the UK, these emissions only decrease by 10% between 1990 and 2015. Urban areas are particularly susceptible to emissions and can have a significant impact upon the health of residents. For Heavy Goods Vehicles, braking losses are one of the most significant losses. A Kinetic Energy Recovery System can help reduce these emissions, and increase fuel efficiency by up to 30 %. This paper describes an InnovateUK funded project aimed at evaluating the technical and economic feasibility of a retrofitted Kinetic Energy Recovery System on Heavy Goods Vehicles through an operational trial, controlled emissions and fuel tests, and numerical modelling. A series of preliminary results using a numerical vehicle model is compared with operational data, along with simulations comparing the fuel efficiency of a Heavy Goods Vehicle with and without the KERS.
Karamanis R, Angeloudis P, Sivakumar A, et al., 2018, Market dynamics between public transport and competitive ride-sourcing providers, 7th Symposium of the European Association for Research in Transportation, Publisher: hEART
O'Driscoll R, Stettler MEJ, Molden N, et al., 2017, Real world CO2 and NOx emissions from 149 Euro 5 and 6 diesel, gasoline and hybrid passenger cars, Science of the Total Environment, Vol: 621, Pages: 282-290, ISSN: 0048-9697
In this study CO2 and NOx emissions from 149 Euro 5 and 6 diesel, gasoline and hybrid passenger cars were compared using a Portable Emissions Measurement System (PEMS). The models sampled accounted for 56% of all passenger cars sold in Europe in 2016. We found gasoline vehicles had CO2 emissions 13-66% higher than diesel. During urban driving, the average CO2 emission factor was 210.5 (sd. 47) gkm-1 for gasoline and 170.2 (sd. 34) gkm-1 for diesel. Half the gasoline vehicles tested were Gasoline Direct Injection (GDI). Euro 6 GDI engines <1.4ℓ delivered ~17% CO2 reduction compared to Port Fuel Injection (PFI). Gasoline vehicles delivered an 86-96% reduction in NOx emissions compared to diesel cars. The average urban NOx emission from Euro 6 diesel vehicles 0.44 (sd. 0.44) gkm-1 was 11 times higher than for gasoline 0.04 (sd. 0.04) gkm-1. We also analysed two gasoline-electric hybrids which out-performed both gasoline and diesel for NOx and CO2. We conclude action is required to mitigate the public health risk created by excessive NOx emissions from modern diesel vehicles. Replacing diesel with gasoline would incur a substantial CO2 penalty, however greater uptake of hybrid vehicles would likely reduce both CO2 and NOx emissions. Discrimination of vehicles on the basis of Euro standard is arbitrary and incentives should promote vehicles with the lowest real-world emissions of both NOx and CO2.
Koudis GS, Hu SJ, North RJ, et al., 2017, The impact of aircraft takeoff thrust setting on NO<inf>X</inf> emissions, Journal of Air Transport Management, Vol: 65, Pages: 191-197, ISSN: 0969-6997
Reduced thrust takeoff has the potential to reduce aircraft-related NO X emissions at airports, however this remains to be investigated using flight data. This paper analyses the effect of takeoff roll thrust setting variability on the magnitude and spatial distribution of NO X emissions using high-resolution data records for 497 Airbus A319 activities at London Heathrow. Thrust setting varies between 67 and 97% of maximum, and aircraft operating in the bottom 10th percentile emit on average 514 g less NO X per takeoff roll (32% reduction) than the top 10th percentile, however this is dependent on takeoff roll duration. Spatial analysis suggests that peak NO X emissions, corresponding to the start of the takeoff roll, can be reduced by up to 25% by adopting reduced thrust takeoff activities. Furthermore, the length of the emission source also decreases. Consequently, the use of reduced thrust takeoff may enable improved local air quality at airports.
Koudis GS, Hu J, Majumdar A, et al., 2017, Airport emissions reductions from reduced thrust takeoff operations, Transportation Research Part D: Transport and Environment, Vol: 52, Pages: 15-28, ISSN: 1361-9209
Given forecast aviation growth, many airports are predicted to reach capacity and require expansion. However, pressure to meet air quality regulations emphasises the importance of efficient ground-level aircraft activities to facilitate growth. Operational strategies such as reducing engine thrust setting at takeoff can reduce fuel consumption and pollutant emissions; however, quantification of the benefits and consistency of its use have been limited by data restrictions. Using 3,336 high-resolution flight data records, this paper analyses the impact of reduced thrust takeoff at London Heathrow. Results indicate that using reduced thrust takeoff reduces fuel consumption, nitrogen oxides (NOX) and black carbon (BC) emissions by 1.0-23.2%, 10.7-47.7%, and 49.0-71.7% respectively, depending on aircraft-engine combinations relative to 100% thrust takeoff. Variability in thrust settings for the same aircraft-engine combination and dependence on takeoff weight (TOW) is quantified. Consequently, aircraft-engine specific optimum takeoff thrust settings that minimise fuel consumption and pollutant emissions for different aircraft TOWs are presented. Further reductions of 1.9%, 5.8% and 6.5% for fuel consumption, NOX and BC emissions could be achieved, equating to reductions of approximately 0.4%, 3.5% and 3.3% in total ground level fuel consumption, NOX and BC emissions. These results quantify the contribution that reduced thrust operations offer towards achieving industry environmental targets and air quality compliance, and imply that the current implementation of reduced thrust takeoff at Heathrow is near optimal, considering operational and safety constraints.
Olfert JS, Dickau M, Momenimovahed A, et al., 2017, Effective density and volatility of particles sampled from a helicopter gas turbine engine, Aerosol Science and Technology, Vol: 51, Pages: 704-714, ISSN: 0278-6826
The effective density and size-resolved volatility of particles emitted from a Rolls-Royce Gnome helicopter turboshaft engine are measured at two engine speed settings (13,000 and 22,000 RPM). The effective density of denuded and undenuded particles were measured. The denuded effective densities are similar to the effective densities of particles from a gas turbine with a double annular combustor as well as a wide variety of internal combustion engines. The denuded effective density measurements were also used to estimate the size and number of primary particles in the soot aggregates. The primary particle size estimates show that the primary particle size was smaller at lower engine speed (in agreement with transmission electron microscopy analysis). As a demonstration, the size-resolved volatility of particles emitted from the engine are measured with a system consisting of a differential mobility analyzer, centrifugal particle mass analyzer, condensation particle counter, and catalytic stripper. This system determines the number distributions of particles that contain or do not contain non-volatile material, and the mass distributions of non-volatile material, volatile material condensed onto the surface of non-volatile particles, and volatile material forming independent particles (e.g. nucleated volatile material). It was found that the particulate at 13,000 RPM contained a measurable fraction of purely volatile material with diameters below ∼25 nm and had a higher mass fraction of volatile material condensed on the surface of the soot (6–12%) compared to the 22,000 RPM condition (1–5%). This study demonstrates the potential to quantify the distribution of volatile particulate matter and gives additional information to characterize sampling effects with regulatory measurement procedures.
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