Eras of electric vehicles: electric mobility on the Verge. Focus Attention Scale

Daily or casual passenger vehicles in cities have negative burden on our finite world. Transport sector has been one of the main contributors to air pollution and energy depletion. Providing alternative means of transport is a promising strategy perceived by motor manufacturers and researchers. The paper presents the battery electric vehicles-BEVs bibliography that starts with the early eras of invention up till 2015 outlook. It gives a broad overview of BEV market and its technology in a chronological classification while sheds light on the stakeholders’ focus attentions in each stage, the so called, Focus-Attention-Scale-FAS. The attention given in each era is projected and parsed in a scale graph, which varies between micro, meso, and macro-scale. BEV-system is on the verge of experiencing massive growth; however, the system entails a variety of substantial challenges. Observations show the main issues of BEVsystem that require more attention followed by the authors’ recommendations towards an emerging market

Connecting brain and behavior in clinical neuroscience: A network approach

In recent years, there has been an increase in applications of network science in many different fields. In clinical neuroscience and psychopathology, the developments and applications of network science have occurred mostly simultaneously, but without much collaboration between the two fields. The promise of integrating these network applications lies in a united framework to tackle one of the fundamental questions of our time: how to understand the link between brain and behavior. In the current overview, we bridge this gap by introducing conventions in both fields, highlighting similarities, and creating a common language that enables the exploitation of synergies. We provide research examples in autism research, as it accurately represents research lines in both network neuroscience and psychological networks. We integrate brain and behavior not only semantically, but also practically, by showcasing three methodological avenues that allow to combine networks of brain and behavioral data. As such, the current paper offers a stepping stone to further develop multi-modal networks and to integrate brain and behavior

Investigating the Role of Occupants, Complex Contextual Factors, and Norms on Residential Energy Consumption.

Human behavior in the built environment has repeatedly been found to have significant meaningful impact on energy consumption. As a consequence researchers have spent considerable efforts investigating various approaches to induce improved occupant behavior, with much recent attention on the use of normative approaches. However, it still remains unclear as to how occupants behave in buildings, how complex factors influence behavioral interventions, and what the long term effects of intervening are. With this background in mind, there are three broad goals in this research: (1) to improve our understanding of the impact of occupant decision making in residential energy consumption, (2) to enhance our understanding of how individual characteristics and complex contextual factors influence change in individual behavior and its diffusion through communities when subjected to normative intervention, and (3) to identify more effective normative behavioral strategies for reducing energy consumption in the built environment. In order to achieve these diverse research objectives, I conducted four interrelated studies based on an iterative research framework that applies an interdisciplinary research approach integrating field experiments with computational modeling. Through these studies it was found that: (1) vast quantities of energy are spent in unoccupied residences and that the percentage of energy consumed while unoccupied in a residence is unrelated to total use; (2) when applying behavior interventions social network structure can meaningfully affect how behavior diffuses and intervention outcome; (3) normative messaging duration positively influenced the durability of behavior change; (4) not all individuals were equally influenced by normative messaging with high norm individuals reducing energy consumption and low norm individuals increasing consumption; (5) by exploiting behavioral responses to normative messaging significant reductions in energy consumption could conceptually be achieved. These findings improve our understanding of occupant behavior, how occupants are influenced by social forces in the built environment, and how complex contextual factors moderate the diffusion of behavior. Further, the findings provide insight into how to improve the environmental sustainability of buildings through behavioral approaches.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113508/1/kyleand_1.pd

Data Mining to Uncover Heterogeneous Water Use Behaviors From Smart Meter Data

Knowledge on the determinants and patterns of water demand for different consumers supports the design of customized demand management strategies. Smart meters coupled with big data analytics tools create a unique opportunity to support such strategies. Yet, at present, the information content of smart meter data is not fully mined and usually needs to be complemented with water fixture inventory and survey data to achieve detailed customer segmentation based on end use water usage. In this paper, we developed a data‐driven approach that extracts information on heterogeneous water end use routines, main end use components, and temporal characteristics, only via data mining existing smart meter readings at the scale of individual households. We tested our approach on data from 327 households in Australia, each monitored with smart meters logging water use readings every 5 s. As part of the approach, we first disaggregated the household‐level water use time series into different end uses via Autoflow. We then adapted a customer segmentation based on eigenbehavior analysis to discriminate among heterogeneous water end use routines and identify clusters of consumers presenting similar routines. Results revealed three main water end use profile clusters, each characterized by a primary end use: shower, clothes washing, and irrigation. Time‐of‐use and intensity‐of‐use differences exist within each class, as well as different characteristics of regularity and periodicity over time. Our customer segmentation analysis approach provides utilities with a concise snapshot of recurrent water use routines from smart meter data and can be used to support customized demand management strategies.TU Berlin, Open-Access-Mittel - 201

A review of agent-based modelling of climate-energy policy

Unidad de excelencia María de Maeztu CEX2019-000940-MAltres ajuts: Russian Science Foundation. Grant Number: 19-18-00262Agent-based models (ABMs) have recently seen much application to the field of climate mitigation policies. They offer a more realistic description of micro behaviour than traditional climate policy models by allowing for agent heterogeneity, bounded rationality and non-market interactions over social networks. This enables the analysis of a broader spectrum of policies. Here, we review 61 ABM studies addressing climate-energy policy aimed at emissions reduction, product and technology diffusion, and energy conservation. This covers a broad set of instruments of climate policy, ranging from carbon taxation and emissions trading through adoption subsidies to information provision tools such as smart meters and eco-labels. Our treatment pays specific attention to behavioural assumptions and the structure of social networks. We offer suggestions for future research with ABMs to answer neglected policy question

Impact Evaluations and Development: Nonie Guidance on Impact Evaluation

In international development, impact evaluation is principally concerned with final results of interventions (programs, projects, policy measures, reforms) on the welfare of communities, households, and individuals, including taxpayers and voters. Impact evaluation is one tool within the larger toolkit of monitoring and evaluation (including broad program evaluations, process evaluations, ex ante studies, etc.).The Network of Networks for Impact Evaluation (NONIE) was established in 2006 to foster more and better impact evaluations by its membership -- the evaluation networks of bilateral and multilateral organizations focusing on development issues, as well as networks of developing country evaluators. NONIE's member networks conduct a broad set of evaluations, examining issues such as project and strategy performance, institutional development, and aid effectiveness. By sharing methodological approaches and promoting learning by doing on impact evaluations, NONIE aims to promote the use of this more specific approach by its members within their larger portfolio of evaluations. This document, by Frans Leeuw and Jos Vaessen, has been developed to support this focus.For development practitioners, impact evaluations play a keyrole in the drive for better evidence on results and development effectiveness. They are particularly well suited to answer important questions about whether development interventions do or do not work, whether they make a difference, and how cost-effective they are. Consequently, they can help ensure that scarce resources are allocated where they can have the most developmental impact