Understanding Consumer Behaviour to Reduce Environmental Impacts through Sustainable Product Design

The use phase of the lifecycle of electrical products has a significant environmental impact, mainly determined by the consumer’s behaviour. Many consumers do not make the link between their daily consumption behaviour in the household and environmental problems such as climate change. In the 21st century, the residential sector, together with transport and industry, is one of the largest man-made contributors in the UK to climate change. It is argued that technological innovations, current eco-efficient products and consumer education have been ineffective in creating the long term radical behavioural change needed to reduce the impact of product use. Products, as the interface between consumers and consumption activities, have the potential to influence the way in which consumption occurs. In the sustainable design field however, designer responsibility traditionally considers raw material selection and product disposal. There is limited work that addresses the environmental impacts relating directly to use behaviour of the product. This paper illustrates that user behaviour studies can be the preliminary step for designers to improve energy efficiency of products. A single product type, household cold appliance, was chosen as a case to explore the capacity of designer-conducted user study to identify unsustainable aspects of product use. Adopting a user-centred approach, two pilot studies were used to gain an insight into domestic fridge and freezer use in the UK. Qualitative ethnographical research methods were employed to investigate the daily practices and “real” needs of user as well as the connection between the knowledge, attitudes, intention and actual action. The design suggestions drawn from the user behaviour analysis provide examples of how energy impact level of the interaction with the product can be reduced through design. Keywords: User-Centred Research; Sustainable Product Design; Changing Consumer Behaviour; Design Research; Household Energy Consumption; Household Cold Appliance.</p

Flow and non-flow correlations from four-particle multiplets in STAR

Elliptic flow results are presented for Au + Au collisions at $\sqrt{s_{NN}} = 130$ GeV in RHIC. This signal is investigated as a function of transverse momentum, rapidity and centrality. Results from four-particle correlation analysis, which can filter out contributions to the flow signal from correlations unrelated to the event reaction plane (``non-flow''), are presented and compared to the conventional method, in which non-flow effects are treated as part of the systematic uncertainty.Comment: 5 pages, 4 figures, uses the class "aipproc

Diffusion-Controlled Electron Transfer Processes and Power-Law Statistics of Fluorescence Intermittency of Nanoparticles

A mechanism involving diffusion-controlled electron transfer processes in Debye and non-Debye dielectric media is proposed to elucidate the power-law distribution for the lifetime of a blinking quantum dot. This model leads to two complementary regimes of power law with a sum of the exponents equal to 2, and to a specific value for the exponent in terms of a distribution of the diffusion correlation times. It also links the exponential bending tail with energetic and kinetic parameters

Determination of energetics and kinetics from single-particle intermittency and ensemble-averaged fluorescence intensity decay of quantum dots

Quantification of energetics and kinetics for the band-edge exciton states of quantum dots and the long-lived dark state is important for better understanding of the underlying mechanism for single-particle intermittency and ensemble fluorescence intensity decay. Based on a multistate diffusion-reaction model by extending our previous studies, we analyze experimental data from ensemble measurements and fluorescence intermittency of single quantum dots and determine important molecular-based quantities such as Stokes shift, free energy gap, activation energy, reorganization energy, and other kinetic parameters

A co-operating solver approach to building simulation

This paper describes the co-operating solver approach to building simulation as encapsulated within the ESP-r system. Possible adaptations are then considered to accommodate new functional requirements

Behavioral Learning of Aircraft Landing Sequencing Using a Society of Probabilistic Finite State Machines

Air Traffic Control (ATC) is a complex safety critical environment. A tower controller would be making many decisions in real-time to sequence aircraft. While some optimization tools exist to help the controller in some airports, even in these situations, the real sequence of the aircraft adopted by the controller is significantly different from the one proposed by the optimization algorithm. This is due to the very dynamic nature of the environment. The objective of this paper is to test the hypothesis that one can learn from the sequence adopted by the controller some strategies that can act as heuristics in decision support tools for aircraft sequencing. This aim is tested in this paper by attempting to learn sequences generated from a well-known sequencing method that is being used in the real world. The approach relies on a genetic algorithm (GA) to learn these sequences using a society Probabilistic Finite-state Machines (PFSMs). Each PFSM learns a different sub-space; thus, decomposing the learning problem into a group of agents that need to work together to learn the overall problem. Three sequence metrics (Levenshtein, Hamming and Position distances) are compared as the fitness functions in GA. As the results suggest, it is possible to learn the behavior of the algorithm/heuristic that generated the original sequence from very limited information