Robin North

Environmental Balance of Shipping Emissions Reduction Strategies

Maritime shipping is regarded as the most efficient mode of transport; however, its contribution to climate change through greenhouse gas emissions and the health issues related to shipping activity near residential centers cannot be neglected. In recent years, the efforts of regulators, ship operators, and port authorities have led to actions for ship emissions reduction to improve shippings environmental performance. This work builds on an activity-based methodology that allows the estimation of emissions and examines environmental effects of slow steaming, fuel regulations, near-port speed-reduction schemes, and cold ironing. Pollutant emissions of carbon dioxide, sulfur dioxide, nitrogen oxides, and black carbon are modeled. A linear programming model minimizes fuel consumption through speed differentiation on a shipping lines routes based on fuel costs and binding regulations in each segment of the journey. Although the examined emissions-reduction actions may have a positive regional environmental effect by cutting emissions, it is possible that additional emissions are generated elsewhere because of increased sailing speeds beyond regulated areas. Trade-offs between pollutants are observed for reduction actions that may have a positive effect on some emission species but at the same time result in additional particulate matter and black carbon emissions. The presented framework allows key actors to conduct comprehensive studies and design improved emissions reduction actions with fewer negative impacts in other areas.

A mobile environmental sensing system to manage transportation and urban air quality

This work presents an integrated mobile environmental sensing and analysis system developed to support the management of transport and urban air quality. A novel spectroscopic UV sensor is employed to provide second-by- second measurements of multiple pollutants at ppb levels. Sensor nodes are deployed on vehicles, infrastructure and people and feed data into a dynamically configurable e-science computing platform that scales to support both near real-time incident management and longer term strategic planning decisions. This paper describes the system architecture and sensor node design alongside results from system development testing. It goes on to highlight avenues for future development and the potential for further applications involving the wider sensors community.

Smart systems commissioning for energy efficient buildings

The gap between as-designed and as-operating energy consumption of new buildings has been widely recognized. Commissioning for optimal energy performance should be a key process to remedy this but in practice, due to shortages of time and budget, commissioning is often limited to ensuring ‘practical completion’ and minimum year-round energy consumption may not be achieved. Commissioning implementation suffers, historically, from poor availability of real time data. Portable wireless sensor networks offer substantial opportunities to support energy-efficient seasonal commissioning by giving temporary access to additional, continuously and simultaneously monitored data points. This paper describes a strategy to implement ‘smart commissioning’ through portable wireless sensor networks for air conditioning systems. Key requirements for delivering seasonal commissioning strategies of multi-modal systems are discussed. Practical application : The importance of post-occupancy commissioning in delivering good energy and environmental performance of new buildings is now widely recognised through practices such as soft landings. However, troubleshooting can be difficult when the building is occupied and budget to do this limited. The building management system may identify that there is a problem but is very unlikely to be collecting the necessary forensic data to solve it. Portable wireless sensor networks specifically designed for analysing building services can overcome this problem in a convenient and economical way and can help development of new industry tools to close the performance gaps and demonstrate in-use building performance.

The vehicle emissions and performance monitoring system: analysis of tailpipe emissions and vehicle performance

This paper describes tailpipe emission results generated by the Vehicle Performance and Emissions Monitoring system (VPEMS). VPEMS integrates on‐board emissions and vehicle/driver performance measurements with positioning and communications technologies, to transmit a coherent spatio‐temporally referenced dataset to a central base station in near real time. These results focus on relationships between tailpipe emissions of CO, CO2, NOx and speed and acceleration. Emissions produced by different driving modes are also presented. Results are generally as one would expect, showing variation between vehicle speed, vehicle acceleration and emissions. Data is based upon a test run in central London on urban streets with speeds not exceeding about 65 km/h. The results presented demonstrate the capabilities of the system. Various issues remain with regard to validation of the data and expansion of the system capability to obtain additional vehicle performance data.

Effect of Transport Models on Connectivity of Interbus Communication Networks

Vehicular Ad-Hoc Networks (VANETs) attract considerable research and commercial interest with promising applications in a number of areas including cooperative vehicle-highways systems, sensor networks, and safety systems. However, as a result of high speed and variable driver behavior, automotive ad-hoc networks behave in fundamentally different ways to the most prevalent models in Mobile Ad-Hoc Network (MANET) research. Previous work in MANETs has mostly assumed that the mobile nodes move randomly with an unconstrained mobility model, and it is clear that a random mobility model is not adequate to represent the major characteristics of real-world vehicle motions and may therefore lead to unreliable results. Recent studies of VANETs have attempted to introduce macro- and micromobility constraints to model vehicle motions, but they have mostly focused on modeling the mobility of generic private vehicles. Given the potential for the coordinated deployment of network nodes on centrally managed fleet vehicles, it has become important to model the characteristics of a VANET featuring vehicles of different types, with systematically different behavior patterns. In this article, the authors study the connectivity of mobile ad-hoc networks that consist of buses moving in urban area and examine the implications for transport-related services. Buses have a unique set of behavior characteristics (e.g., fixed routes, schedules, bus stops, specific priorities), which gives rise to distinct effect on node connectivity in the communication network. Through extensive simulations on the basis of real bus routes in central London, the authors (a) demonstrated the effect of the locations of stops and the prevailing traffic patterns on node connectivity (including the distributions of contact duration and intercontact time between buses) and (b) explored its implication on the design of a dissemination system to capture and disseminate data. Their results give a key message that the mobility of buses has to be modeled explicitly, and such kind of knowledge of connectivity among buses will be significant for the studies of routing algorithms and other networking functions in interbus communication networks.

Quantitative Measures for GPS Based Road User Charging

The objective of this paper is to derive quantitative measures for road user charging (RUC). Instead of using complicated sensors to measure pollutant emissions and driver behavior, this paper uses location, velocity, acceleration and time (LVAT) determined by most widely used GPS receivers together with supporting information to derive indirect quantitative indicators for emissions and driver behavior. Test results show that most of the factors relevant to RUC are highly correlated to LVAT. This should enable the implementation and operation of a simple and cost effective variable RUC scheme based on LVAT data derived from GPS measurements.

Field investigation of vehicle acceleration at the stop line with a dynamic vision sensor

This article presents a study of vehicle acceleration measurements at the stop line of a traffic light in an urban environment. Accurate representation of vehicle acceleration behavior is an important parameter to traffic simulation tools especially when the emissions related to the simulated traffic need to be calculated. A smart eye traffic data sensor (TDS) system was used to record the vehicle trajectories. This device is based on dynamic vision sensor technology that features 1 millisecond temporal resolution, wide dynamic range of 120 dB of illumination, zero-redundancy and asynchronous data output. The trajectories of the detected vehicles from the vision sensor temporal contrast event data have been manually annotated in a space-time representation using a graphical tool. From these extracted trajectories the acceleration of the vehicles has been calculated. We present results of acceleration distributions obtained from over 300 passenger-car acceleration cycles observed in the field. The measurements focus on the first phase of acceleration from the stop line up to a maximum speed of 40 km/h. The results are compared to the results from a traffic micro simulation tool obtained for a similar stop line scenario. The results will be used in the traffic micro-simulation that serves as a basis for a decision support tool for adaptive traffic management developed in the CARBOTRAF FP7 EU project.

Evaluating mobility models in participatory sensing

Pervasive wireless sensor networks offer many mission oriented opportunities. In this paper we evaluate the potential benefits of combining fixed and mobile sensor nodes as part of a mission-oriented, participatory sensor network deployed on an urban environment that has the objective of detecting the extent of the emission of a substance of interest (e.g. pollutant). We evaluate the system both by assuming simple mobility models for sensors and more realistic models that seek to reduce operating costs.