Psychological predictors of eco-driving: A longitudinal study

Eco-driving has well-known positive effects on fuel economy and greenhouse-gas emissions. Moreover, eco-driving reduces road-traffic noise, which is a serious threat to the health and well-being of many people. We investigated the psychological predictors of the adoption of eco-driving from the perspective of road-traffic noise abatement. The data came from 890 car drivers who participated in a longitudinal survey over four months. Specifically, we tested the effects of the intention to prevent road-traffic noise, variables derived from the theory of planned behavior (social norm, perceived behavioral control, and attitude), and variables derived from the health action process approach (implementation intention, maintenance self-efficacy, and action control) on the intention to practice eco-driving and on eco-driving behavior. The intention to prevent road-traffic noise was not linked to the intention to practice eco-driving. The strongest predictors of the intention to practice eco-driving were attitude and perceived behavioral control. The strongest predictor of eco-driving behavior was action control. The link between behavioral intention and behavior was weak, indicating that drivers have difficulties putting their intention to practice eco-driving into action. Therefore, intervention efforts should directly address and support the transition from intention to behavior. This could be accomplished by providing reminders, which help to maintain behavioral intention, and by providing behavior feedback, which helps car drivers to monitor their behavior.

Promoting a low-noise driving style: An eco-driving intervention study

Road-traffic noise impairs the well-being and health of many people. Motivating car drivers to voluntarily adopt a low-noise driving style (i.e., eco-driving) contributes to the reduction of road-traffic noise, complementary to requirements, bans, and laws. In a field study with employees of a municipality (N = 88), we investigated the effects of an intervention on car drivers’ motivation to prevent road-traffic noise, motivation to practice eco-driving, and driving behavior. The intervention consisted of a leaflet intended to enhance participants’ motivation, a practical eco-driving course, and weekly driving-performance feedbacks. We used a switching-replications design with two intervention groups. In both groups, eco-driving behavior was significantly strengthened by the intervention. The effects on the motivational variables were significant in only one of the groups (however, it should be noted that the average motivation was already relatively high before the intervention). For one of the groups, the study design allowed testing for the effects at an additional follow-up assessment (4 months after the intervention). The results showed that the intervention effect on driving behavior held across this period. The findings of the present research suggest that it is possible to improve car driver’s behavior with regard to a low-noise driving style.

Using floating car data to analyse the effects of ITS measures and eco-driving

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

Understanding how to reduce road transport emissions : modelling the impact of eco-driving

Entre los problemas medioambientales más trascendentales para la sociedad, se encuentra el del cambio climático así como el de la calidad del aire en nuestras áreas metropolitanas. El transporte por carretera es uno de los principales causantes, y como tal, las administraciones públicas se enfrentan a estos problemas desde varios ángulos: Cambios a modos de transporte más limpios, nuevas tecnologías y combustibles en los vehículos, gestión de la demanda y el uso de tecnologías de la información y la comunicación (ICT) aplicadas al transporte. En esta tesis doctoral se plantea como primer objetivo el profundizar en la comprensión de cómo ciertas medidas ICT afectan al tráfico, las emisiones y la propia dinámica de los vehículos. El estudio se basa en una campaña de recogida de datos con vehículos flotantes para evaluar los impactos de cuatro medidas concretas: Control de velocidad por tramo, límites variables de velocidad, limitador de velocidad (control de crucero) y conducción eficiente (eco‐driving). Como segundo objetivo, el estudio se centra en la conducción eficiente, ya que es una de las medidas que más ahorros de combustible presenta a nivel individual. Aunque estas reducciones están suficientemente documentadas en la literatura, muy pocos estudios se centran en estudiar el efecto que los conductores eficientes pueden tener en el flujo de tráfico, y cuál sería el impacto si se fuera aumentando el porcentaje de este tipo de conductores. A través de una herramienta de microsimulación de tráfico, se han construido cuatro modelos de vías urbanas que se corresponden con una autopista urbana, una arteria, un colector y una vía local. Gracias a los datos recogidos en la campaña de vehículos flotantes, se ha calibrado el modelo, tanto el escenario base como el ajuste de parámetros de conducción para simular la conducción eficiente. En total se han simulado 72 escenarios, variando el tipo de vía, la demanda de tráfico y el porcentaje de conductores eficientes. A continuación se han calculado las emisiones de CO2 and NOx mediante un modelo de emisiones a nivel microscópico. Los resultados muestran que en escenarios con alto porcentaje de conductores eficientes y altas demandas de tráfico las emisiones aumentan. Esto se debe a que las mayores distancias de seguridad y las aceleraciones y frenadas suaves hacen que aumente la congestión, produciendo así mayores emisiones a nivel global. Climate change and the reduced air quality in our metropolitan areas are two of the main environmental problems that the society is addressing currently. Being road transportation one of the main contributors, public administrations are facing these problems from different points of view: shift to cleaner modes, new fuels and vehicle technologies, demand management and the use of information and communication technologies (ICT) applied to transportation. The first objective of this thesis is to understand how certain ICT measures affect traffic, emissions and vehicle dynamics. The study is based on a data collection campaign with floating vehicles to evaluate the impact of four specific measures: section speed control, variable speed limits, cruise control and eco‐driving. The second objective of the study focuses on eco‐driving, as it is one of the measures that present the largest fuel savings at an individual level. Although these savings are well documented in the literature, few studies focus on how ecodrivers affect the surrounding vehicles and the traffic, and what would be the impact in case of different eco‐drivers percentage. Using a traffic micro‐simulation tool, four models in urban context have been built, corresponding to urban motorway, urban arterial, urban collector and a local street. Both the base‐case and the parameters setting to simulate eco‐driving have been calibrated with the data collected through floating vehicles. In total 72 scenarios were simulated, varying the type of road, traffic demand and the percentage of eco‐drivers. Then, the CO2 and NOx emissions have been estimated through the use of an emission model at microscopic level. The results show that in scenarios with high percentage of co‐drivers and high traffic demand the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Influence of driving style on fuel consumption and Emissions in diesel-powered passenger car

This paper presents the main results of a study on the influence of driving style on fuel consumption and pollutant emissions of diesel passenger car in urban traffic. Driving styles (eco, normal or aggressive) patterns were based on the “eco-driving” criteria. The methodology is based on on-board emission measurements in real urban traffic in the city of Madrid. Five diesel passenger cars, have been tested. Through a statistical analysis, a Dynamic Performance Index was defined for diesel passenger cars. Likewise, the CO, NOX and HC emissions were compared for each driving style for the tested vehicles. Eco-driving reduces by 14% fuel consumption and CO2 emissions, but aggressive driving increase consumption by 40%. Aggressive driving increases NOX emission by more than 40%. CO and HC, show different trends, but being increased in eco-driving style.

Reducing fuel consumption through modular vehicle architectures

By identifying energy waste streams in vehicles fuel consumption and introducing the concept of lean driving systems, a technological gap for reducing fuel consumption was identified. This paper proposes a solution to overcome this gap, through a modular vehicle architecture aligned with driving patterns. It does not address detailed technological solutions; instead it models the potential effects in fuel consumption through a modular concept of a vehicle and quantifies their dependence on vehicle design parameters (manifesting as the vehicle mass) and user behavior parameters (driving patterns manifesting as the use of a modular car in lighter and heavier mode, in urban and highway cycles). Modularity has been functionally applied in automotive industry as manufacture and assembly management strategies; here it is thought as a product development strategy for flexibility in use, driven by environmental concerns and enabled by social behaviors. The authors argue this concept is a step forward in combining technological solutions and social behavior, of which eco-driving is a vivid example, and potentially evolutionary to a lean, more sustainable, driving culture.

Complex patterns of global spread in invasive insects: eco-evolutionary and management consequences

The advent of simple and affordable tools for molecular identification of novel insect invaders and assessment of population diversity has changed the face of invasion biology in recent years. The widespread application of these tools has brought with it an emerging understanding that patterns in biogeography, introduction history and subsequent movement and spread of many invasive alien insects are far more complex than previously thought. We reviewed the literature and found that for a number of invasive insects, there is strong and growing evidence that multiple introductions, complex global movement, and population admixture in the invaded range are commonplace. Additionally, historical paradigms related to species and strain identities and origins of common invaders are in many cases being challenged. This has major consequences for our understanding of basic biology and ecology of invasive insects and impacts quarantine, management and biocontrol programs. In addition, we found that founder effects rarely limit fitness in invasive insects and may benefit populations (by purging harmful alleles or increasing additive genetic variance). Also, while phenotypic plasticity appears important post-establishment, genetic diversity in invasive insects is often higher than expected and increases over time via multiple introductions. Further, connectivity among disjunct regions of global invasive ranges is generally far higher than expected and is often asymmetric, with some populations contributing disproportionately to global spread. We argue that the role of connectivity in driving the ecology and evolution of introduced species with multiple invasive ranges has been historically underestimated and that such species are often best understood in a global context.

The signalling effect of eco-labels in modern coastal tourism

As the demand for environmentally sustainable tourism grows, eco-labels are becoming increasingly popular as a signal of environmental quality. However, the existence of a causal link between awarding a seaside eco-label and the increase in tourism flows is still under discussion in the literature. In this article, we gauge the signalling impact of a specific eco-label, the Blue Flag award, using detailed data on tourism flows to seaside Italian destinations during the period 2008-2012. We adopt a recent econometric modelling strategy - the synthetic control method - in shaping estimation results and testing the sensitivity and robustness of our results. We find that being awarded the Blue Flag increases the flow of domestic tourists for up to three seasons after assignment. However, we find no effect for the flow of international tourists. Investigating the mechanisms driving the results, we find that the award of a Blue Flag only positively affects the flow of domestic tourists when it is used as a driver of organisation, coordination and integrated management of the tourism supply.

Measuring the eco-efficiency of cement use

At present, the cement industry generates approximately 5% of the world`s anthropogenic CO(2) emissions. This share is expected to increase since demand for cement based products is forecast to multiply by a factor of 2.5 within the next 40 years and the traditional strategies to mitigate emissions, focused on the production of cement, will not be capable of compensating such growth. Therefore, additional mitigation strategies are needed, including an increase in the efficiency of cement use. This paper proposes indicators for measuring cement use efficiency, presents a benchmark based on literature data and discusses potential gains in efficiency. The binder intensity (bi) index measures the amount of binder (kg m(-3)) necessary to deliver 1 MPa of mechanical strength, and consequently express the efficiency of using binder materials. The CO(2) intensity index (ci) allows estimating the global warming potential of concrete formulations. Research benchmarks show that bi similar to 5 kg m(-3) MPa(-1) are feasible and have already been achieved for concretes >50 MPa. However, concretes with lower compressive strengths have binder intensities varying between 10 and 20 kg m(-3) MPa(-1). These values can be a result of the minimum cement content established in many standards and reveal a significant potential for performance gains. In addition, combinations of low bi and ci are shown to be feasible. (c) 2010 Elsevier Ltd. All rights reserved.

Eco-efficiency for the Dairy Processing Industry - Fact Sheet Sumary

This Toolkit was developed for the Australian dairy processing industry on behalf of Dairy Australia. At the conclusion of the project, industry participants gained exclusive access to a comprehensive Eco-Efficiency Manual, which outlined many of the opportunities available to the industry. Summary fact sheets were also prepared as publicly available resources and these are available for download below