Isocyanic acid and ammonia in vehicle emissions

Vehicles are considered to be an important source of ammonia (NH₃) and isocyanic acid (HNCO). HNCO and NH₃ have been shown to be toxic compounds. Moreover, NH₃ is also a precursor in the formation of atmospheric secondary aerosols. For that reason, real-time vehicular emissions from a series of Euro 5 and Euro 6 light-duty vehicles, including spark ignition (gasoline and flex-fuel), compression ignition (diesel) and a plug-in electric hybrid, were investigated at 23 and −7 °C over the new World harmonized Light-duty vehicle Test Cycle (WLTC) in the Vehicle Emission Laboratory at the European Commission Joint Research Centre Ispra, Italy. The median HNCO emissions obtained for the studied fleet over the WLTC were 1.4 mg km⁻¹ at 23 °C and 6 mg km⁻¹ at −7 °C. The fleet median NH₃ emission factors were 10 mg km⁻¹ and 21 mg km⁻¹ at 23 and −7 °C, respectively. The obtained results show that even though three-way catalyst (TWC), selective catalytic reduction (SCR), and NOx storage catalyst (NSC) are effective systems to reduce NOx vehicular emissions, they also lead to considerable emissions of the byproducts NH₃ and/or HNCO. It is also shown that diesel light-duty vehicles equipped with SCR can present NH₃ emission factors as high as gasoline light-duty vehicles at both, 23 and −7 °C over the WLTC. Therefore, with the introduction in the market of this DeNOx technology, vehicular NH₃ emissions will increase further.     

Assessment of energy-saving techniques in direct-current-electrified mass transit systems

Railway rapid transit systems are key stones for the sustainability of mass transit in developed countries. The overwhelming majority of these railway systems are direct-current (DC) electrified and several energy-saving techniques have been proposed in the literature for these systems. The use of regenerative-braking in trains is generally recognised as the main tool to improve the efficiency of DC-electrified mass transit railway systems but the energy recovered in braking cannot always be handled efficiently, above all in low traffic-density situations. Several emerging technologies as energy storage systems or reversible traction substations have the potential for making it possible to efficiently use train-braking. However, a systematic evaluation of their effect is missing in the literature.In this paper, a deep, rigorous and comprehensive study on the factors which affect energy issues in a DC-electrified mass transit railway system is carried out. This study clarifies what the actual potential is for energy saving in each situation. Then, a methodology to asses several energy-saving techniques to improve energy efficiency in DC-electrified mass transit systems is presented, constituting the main contribution of this paper. This methodology has been conceived to help operators in assessing the effect of railway-infrastructure emerging technologies in transit systems, so making it possible to shape planning, capacity, etc. It is stepped out in three basic movements. First of all, a traffic-density scan analysis is conducted in order to clarify the effect of the headway on system behaviour. Secondly, several traffic-density scenarios are simulated for a set of infrastructure-expanded cases. Finally, annual energy saving is evaluated by applying a realistic operation timetable. This methodology has been applied to a case study in Madrid Metro (Spain) to illustrate the steps of its application and the effect of several energy-saving techniques on this specific system. Results confirm that regenerative braking generally leads to an important increase of system energy efficiency – especially at high traffic-density scenarios. It has also been proved that infrastructure improvements can also contribute to energy savings and their contributions are more significant at low traffic densities. Annual energy results have been obtained, which may lead to investment decisions by carrying out an appropriate economic assessment based on cost analysis.The main results of the study presented here are likely to apply to other electric traction systems, at least qualitatively.     

A constraint programming model with time uncertainty for cooperative flight departures

The lack of a proper integration of strategic Air Traffic Management decision support tools with tactical Air Traffic Control interventions usually generates a negative impact on the Reference Business Trajectory adherence, and in consequence affects the potential of the Trajectory-Based Operations framework. In this paper, a new mechanism relaying on Reference Business Trajectories as a source of data to reduce the amount of Air Traffic Controller interventions at the tactical level while preserving Air Traffic Flow Management planned operations is presented. Artificial Intelligence can enable Constraint Programming as it is a powerful paradigm for solving complex, combinatorial search problems. The proposed methodology takes advantage of Constraint Programming and fosters adherence of Airspace User’s trajectory preferences by identifying tight interdependencies between trajectories and introducing a new mechanism to improve the aircraft separation at concurrence events considering time uncertainty. The underlying philosophy is to capitalize present degrees of freedom between layered Air Traffic Management planning tools, when sequencing departures at the airports by considering the benefits of small time stamp changes in the assigned Calculated Take-Off Time departures and to enhance Trajectory-Based Operations concepts.