Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Competitive food exploitation of smelt Osmerus eperlanus by great crested grebes Podiceps cristatus and perch Perca fluviatilis at Lake IJsselmeer, The Netherlands

The impact of predation by an avian predator (great crested grebe Podiceps cristatus) and a predatory fish (perch Perca fluviatilis) on a common resource, the small planktivorous fish smelt (Osmerus eperlanus) was studied in Lake IJsselmeer, The Netherlands, in July-October 1985-1988. At this time of the year the grebes are in simultaneous wing-moult and therefore temporarily flightless. Four factors limit the predation pressure by grebes: (1) an underwater visibility threshold of c. 40 cm Secchi depth is the lower limit at which large numbers attend the moulting site, (2) a lower density threshold of exploitable smelt biomass of c. 30 kg/ha determines the actual fishing areas, (3) a fish size threshold of 6.5 cm total length further limits prey availability, and (4) the vertical movements of the prey impose a strong (diel) time constraint on the birds, allowing only crepuscular foraging. Perch, the other main predator in this system, is less restricted in its foraging. Perch were found to be in direct competition with the grebes, preying heavily on the juvenile smelt. Over the 4 years of study 90% of all predation from 15 July to 15 October (72 233 kg/ha) was due to perch. The high level of predation by birds and fish was only possible due to a continuous immigration of smelt into the area (1.45 kg/ha per day). In three of the four years, however, the combined predation by fish and birds surpassed the immigration rate of the prey, which led to a strong reduction in smelt stocks in the study area. A conceptual model is developed to describe the different sets of constraints on the grebes' foraging. First, the state of eutrophication in relation to the weather condition determines the degree of algal blooms, and thus underwater visibility, in late summer. This is the major factor governing the numbers of grebes on the moulting area. Second, the size of the population of predatory fish determines the overall food availability (biomass and size distribution of smelt). These factors are partly interconnected and related to human action (pollution, fisheries). It is suggested that, despite deteriorating visibility conditions, the largest moulting site for grebes in Europe at Lake IJsselmeer exists because the stocks of predatory fish are kept low by overfishing

Physiomorphic transformation in extreme endurance migrants:Revisiting the case of Bar-tailed Godwits preparing for trans-Pacific flights

In a 1998 paper entitled “Guts don’t fly: small digestive organs in obese bar-tailed godwits,” Piersma and Gill (1998) showed that the digestive organs were tiny and the fat loads huge in individuals suspected of embarking on a non-stop flight from Alaska to New Zealand. It was suggested that prior to migratory departure, these godwits would shrink the digestive organs used during fuel deposition and boost the size and capacity of exercise organs to optimize flight performance. Here we document the verity of the proposed physiomorphic changes by comparing organ sizes and body composition of bar-tailed godwits Limosa lapponica baueri collected in modesty midway during their fueling period (mid-September; fueling, n = 7) with the previously published data for godwits that had just departed on their trans-Pacific flight (October 19; flying, n = 9). Mean total body masses for the two groups were nearly identical, but nearly half of the body mass of fueling godwits consisted of water, while fat constituted over half of total body mass of flying godwits. The two groups also differed in their fat-free mass components. The heart and flight muscles were heavier in fueling godwits, but these body components constituted a relatively greater fraction of the fat-free mass in flying godwits. In contrast, organs related to digestion and homeostasis were heavier in fueling godwits, and most of these organ groups were also relatively larger in fueling godwits compared to flying godwits. These results reflect the functional importance of organ and muscle groups related to energy acquisition in fueling godwits and the consequences of flight-related exertion in flying godwits. The extreme physiomorphic changes apparently occurred over a short time window (≤1 month). We conclude that the inferences made on the basis of the 1998 paper were correct. The cues and stimuli which moderate these changes remain to be studied

High speed autonomous off-road vehicle steering

High speed cornering of an off-road vehicle poses considerable challenges to the development of an autonomous vehicle due to the non-linear dynamics of the tyre road interface as well as those of the vehicle as a whole during high lateral accelerations. Most driver models are developed for low speed applications using linear control methods under the assumption of linear vehicle dy- namics. The dynamics of a vehicle however become highly non-linear as the lateral acceleration increases, thus rendering these linear models unusable during high speed manoeuvres. In this study, two robust driver models for use in an autonomous vehicle capable of path following at both low and high speeds are presented. Both models make use of the relationship between the yaw acceleration and steering rate to control the yaw angle of the vehicle. The first driver model is derived from the simulation of a full non-linear vehicle model in ADAMS. The Magic Tyre Formula is used to model the relationship between the vehicle's yaw acceleration and steer rate as a function of vehicle speed. The second driver model is a mathematical model which incorporates a form of sliding control. The model includes the lateral tyre dynamics as modelled by the Pacejka '89 tyre model. Both driver models are coupled with a gain scheduling proportional derivative controller to reduce the cross-track error. The two driver models were implemented on a Land Rover Defender and experimentally validated by performing a double lane change manoeuvre at speeds up to 80km/h. The vehicle remained stable even though the lateral accelerations experienced were 80% of the vehicle limits. The result is a robust controller capable of path following at various speeds and at high lateral accelerations. CopyrightDissertation (MEng)--University of Pretoria, 2011.Mechanical and Aeronautical EngineeringUnrestricte

CARBOTRAF: A decision Support system for reducing pollutant emissions by adaptive traffic management

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

Adverse wind conditions during northward Sahara crossings increase the in-flight mortality of Black-tailed Godwits

Long-distance migratory flights are predicted to be associated with higher mortality rates when individuals encounter adverse weather conditions. However, directly connecting environmental conditions experienced in-flight with the survival of migrants has proven difficult. We studied how the in-flight mortality of 53 satellite-tagged Black-tailed Godwits (Limosa limosa limosa) during 132 crossings of the Sahara Desert, a major geographical barrier along their migration route between The Netherlands and sub-Saharan Africa, is correlated with the experienced wind conditions and departure date during both southward and northward migration. We show that godwits experienced higher wind assistance during southward crossings, which seems to reflect local prevailing trade winds. Critically, we found that fatal northward crossings (15 deaths during 61 crossings) were associated with adverse wind conditions. Wind conditions during migration can thus directly influence vital rates. Changing wind conditions associated with global change may thus profoundly influence the costs of long-distance migration in the future

Air quality impact of a decision support system for reducing pollutant emissions: CARBOTRAF

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses these off-line model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

The Pacific as the world’s greatest theater of bird migration:Extreme flights spark questions about physiological capabilities, behavior, and the evolution of migratory pathways

The Pacific Basin, by virtue of its vastness and its complex aeroscape, provides unique opportunities to address questions about the behavioral and physiological capabilities and mechanisms through which birds can complete spectacular flights. No longer is the Pacific seen just as a formidable barrier between terrestrial habitats in the north and the south, but rather as a gateway for specialized species, such as shorebirds, to make a living on hemispherically distributed seasonal resources. This recent change in perspective is dramatic, and the research that underpins it has presented new opportunities to learn about phenomena that often challenge a sense of normal. Ancient Polynesians were aware of the seasonal passage of shorebirds and other landbirds over the Pacific Ocean, incorporating these observations into their navigational “tool kit” as they explored and colonized the Pacific. Some ten centuries later, systematic visual observations and tracking technology have revealed much about movement of these shorebirds, especially the enormity of their individual nonstop flights. This invites a broad suite of questions, often requiring comparative studies with bird migration across other ocean basins, or across continents. For example, how do birds manage many days of nonstop exercise apparently without sleep? What mechanisms explain birds acting as if they possess a Global Positioning System? How do such extreme migrations evolve? Through advances in both theory and tracking technology, biologists are poised to greatly expand the horizons of movement ecology as we know it. In this integrative review, we present a series of intriguing questions about trans-Pacific migrant shorebirds and summarize recent advances in knowledge about migratory behavior operating at temporal scales ranging from immediate decisions during a single flight, to adaptive learning throughout a lifetime, to evolutionary development of migratory pathways. Recent advances in this realm should stimulate future research across the globe and across a broad array of disciplines

Real-time lateral stability and steering characteristic control using non-linear model predictive control

This paper presents a non-linear integrated control strategy that primarily focuses maintaining vehicle lateral stability using active front steering and differential braking. The proposed control strategy utilises a non-linear model predictive controller to improve lateral stability. A stable linear reference model is used for reference generation. By including the understeer gradient in the reference model, different kinematic responses are obtained from the controlled vehicle. The prediction model utilises the road friction estimate to create dynamic stability constraints that include rollover and sliding of the vehicle. The design of the model predictive controller allows easy activation of different control actuators and dynamic modification to the control behaviour. The control methodology is validated using MATLAB/Simulink and a validated MSC ADAMS model. A sensitivity analysis is conducted to identify the susceptibility of the control strategy to various parameters and states.https://www.tandfonline.com/loi/nvsd20hj2023Mechanical and Aeronautical Engineerin