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- All Subjects: Energy consumption
- Creators: Barnes, Elizabeth
- Creators: Chen, Hong
This paper focuses on the factors influencing Energy Management Behaviour (EMB) at the individual level. By reviewing academic literature, conducting surveys in Beijing, Shanghai and Guangzhou, the author builds an integrated behavioural energy management model of the Chinese energy consumers. This paper takes the vague term of EMB and redefines it as a function of two separate behavioural concepts: Energy Management Intention (EMI), and the traditional Energy Saving Intention (ESI).
Secondly, the author conducts statistical analyses on these two behavioural concepts. EMI is the main driver behind an individual’s EMB. EMI is affected by Behavioural Attitudes, Subjective Norms, and Perceived Behavioural Control (PBC). Among these three key factors, PBC exerts the strongest influence. This implies that the promotion of the energy management concept is mainly driven by good application user experience (UX). The traditional ESI also demonstrates positive influence on EMB, but its impact is weaker than the impacts arising under EMI’s three factors. In other words, the government and manufacturers may not be able to change an individual's energy management behaviour if they rely solely on their traditional promotion strategies. In addition, the study finds that the government may achieve better promotional results by launching subsidies to the manufacturers of these kinds of applications and smart appliances.
This LCA used data from a previous LCA done by Chester and Horvath (2012) on the proposed California High Speed Rail, and furthered the LCA to look into potential changes that can be made to the proposed CAHSR to be more resilient to climate change. This LCA focused on the energy, cost, and GHG emissions associated with raising the track, adding fly ash to the concrete mixture in place of a percentage of cement, and running the HSR on solar electricity rather than the current electricity mix. Data was collected from a variety of sources including other LCAs, research studies, feasibility studies, and project information from companies, agencies, and researchers in order to determine what the cost, energy requirements, and associated GHG emissions would be for each of these changes. This data was then used to calculate results of cost, energy, and GHG emissions for the three different changes. The results show that the greatest source of cost is the raised track (Design/Construction Phase), and the greatest source of GHG emissions is the concrete (also Design/Construction Phase).