scholarly journals Capturing the Environmental Impact of Individual Lifestyles: Evidence of the Criterion Validity of the General Ecological Behavior Scale

2017 ◽  
Vol 50 (3) ◽  
pp. 350-372 ◽  
Author(s):  
Oliver Arnold ◽  
Alexandra Kibbe ◽  
Terry Hartig ◽  
Florian G. Kaiser
Keyword(s):  
Environmental Impact ◽  
Electricity Consumption ◽  
Criterion Validity ◽  
Smart Meter ◽  
Behavioral Measures ◽  
Green Electricity ◽  
Power Company ◽  
Reported Study ◽  
Behavior Scale ◽  
Ecological Behavior

Do behavioral measures of ecological lifestyles reflect actual environmental impact? Three convenience samples of German adults ( N = 881) completed such a measure, the General Ecological Behavior (GEB) scale. Their household electricity consumption was self-reported (Study 1), assessed by a smart-meter (Study 2), or reported by the power company (Study 3). The latter two studies controlled for income, which can boost consumption just as it opens possibilities for behaving ecologically. Within and across studies, analyses revealed a negative association between self-reported ecological behavior and electricity consumption (−.18 ≤ rs ≤ −.22), even with adjustment for income. Furthermore, customers in a green electricity program reported more ecological engagement and consumed one third less electricity than did regular customers. These results indicate the criterion validity of the GEB scale for a highly practically relevant criterion and encourage the use of generic behavior measures in efforts to understand and foster more ecological lifestyles.

General Ecological Behavior Scale

2003 ◽  
Author(s):  
Florian G. Kaiser ◽  
Mark Wilson
Keyword(s):  
Behavior Scale ◽  
Ecological Behavior

scholarly journals Sistema Open-Source de Monitoramento do Consumo de Energia Elétrica

2020 ◽  
Author(s):  
Felipe Przysiada† ◽  
Diego Merks ◽  
Eduardo Silva ◽  
Alessandro Brawerman
Keyword(s):  
Energy Consumption ◽  
Environmental Impact ◽  
Electricity Consumption ◽  
User Profile ◽  
End User ◽  
Hydroelectric Plants ◽  
The Cost ◽  
Monitoring Devices ◽  
Generating System ◽  
Monthly Survey

The cost of electricity in Brazilian homes is increasingly high. This project consists of bringing a complete and easily accessible solution aiming to benefit the economy, in a much broader way, both for the end user and for the electricity generating system, which today has difficulty in meeting demand, as well as it provides a reduction in the environmental impact caused by the constant expansion of hydroelectric plants and other sources of energy. The use of this system, the Electricity Consumption Monitoring System, allows the user to have control of each equipment installed in the premises. The equipment in monitored by a device designed and built in this project. From these monitoring devices, which perform periodic measurements, it is possible to make a daily, weekly or monthly survey of the consumption of each equipment in the residence, sending alert messages, for excessive energy consumption, thus defining a user profile and even creating limitations for monthly spending. With this, the user will have the necessary resources to manage their energy consumption over the days, without having surprises at the end of the month.

scholarly journals Electricity Consumption Estimation of the Polymer Material Injection-Molding Manufacturing Process: Empirical Model and Application

Materials ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 1740 ◽  
Author(s):  
Ana Elduque ◽  
Daniel Elduque ◽  
Carmelo Pina ◽  
Isabel Clavería ◽  
Carlos Javierre
Keyword(s):  
Environmental Impact ◽  
Injection Molding ◽  
Empirical Model ◽  
Electricity Consumption ◽  
Injection Molding Process ◽  
Molding Process ◽  
Polymer Injection ◽  
Wide Range ◽  
Molded Parts ◽  
Polymer Injection Molding

Polymer injection-molding is one of the most used manufacturing processes for the production of plastic products. Its electricity consumption highly influences its cost as well as its environmental impact. Reducing these factors is one of the challenges that material science and production engineering face today. However, there is currently a lack of data regarding electricity consumption values for injection-molding, which leads to significant errors due to the inherent high variability of injection-molding and its configurations. In this paper, an empirical model is proposed to better estimate the electricity consumption and the environmental impact of the injection-molding process. This empirical model was created after measuring the electricity consumption of a wide range of parts. It provides a method to estimate both electricity consumption and environmental impact, taking into account characteristics of both the molded parts and the molding machine. A case study of an induction cooktop housing is presented, showing adequate accuracy of the empirical model and the importance of proper machine selection to reduce cost, electricity consumption, and environmental impact.

scholarly journals Electricity Consumption Clustering Using Smart Meter Data

Energies ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 859 ◽  
Author(s):  
Alexander Tureczek ◽  
Per Nielsen ◽  
Henrik Madsen
Keyword(s):  
Electricity Consumption ◽  
Smart Meter

scholarly journals A Comparative Life Cycle Assessment of Electronic Retail of Household Products

2020 ◽  
Vol 12 (11) ◽  
pp. 4604
Author(s):  
Jan Matuštík ◽  
Vladimír Kočí
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Environmental Impact ◽  
Real Life ◽  
Electricity Consumption ◽  
Assessment Method ◽  
Logistics Center ◽  
Variation Of Parameters ◽  
Household Products ◽  
Alternative Scenarios

Electronic shopping is getting more and more popular, and it is not only clothes and electronics that people buy online, but groceries and household products too. Based on real-life data from a major cosmetics and household products retailer in the Czech Republic, this study set to assess the life cycle environmental impact of parcel delivery. Two archetype parcels containing common household and hygiene products were designed and packed in two distinct ways, and the environmental impact was quantified using the Life Cycle Assessment method. It showed that it is environmentally beneficial to use plastic cushions to insulate the goods instead of paper. However, the most important process contributing to the environmental burden was found to be electricity consumption in the logistics center. Hence, the importance of energy efficiency and efficient space utilization was demonstrated on alternative scenarios. Since the cardboard box the goods are packed in turned out to be another important contributor, an alternative scenario was designed where a reusable plastic crate was used instead. Even though the scenario was based on several simplistic assumptions, it showed a clear potential to be environmentally beneficial. In the study, contribution of other processes was scrutinized, as well as sensitivity to variation of parameters, e.g. transportation distances. The main scientific contribution of this work is to show the importance of logistics and distribution of products to end customers in the rapidly developing field of electronic retail of household products.

scholarly journals A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors

Energies ◽  
2017 ◽  
Vol 10 (10) ◽  
pp. 1446 ◽  
Author(s):  
Fateh Melzi ◽  
Allou Same ◽  
Mohamed Zayani ◽  
Latifa Oukhellou
Keyword(s):  
Mixture Model ◽  
Electricity Consumption ◽  
Smart Meter

scholarly journals Smart metering system data analytics platform using multicore edge computing

2021 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Juan C. Olivares-Rojas ◽  
Enrique Reyes-Archundia ◽  
José A. Gutiérrez-Gnecchi ◽  
Ismael Molina-Moreno ◽  
Adriana C. Téllez-Anguiano ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Data Processing ◽  
Data Analytics ◽  
Electricity Consumption ◽  
Edge Computing ◽  
Smart Meter ◽  
Smart Metering ◽  
Smart Meters ◽  
System Data

The smart grid revolution has only been possible, thanks to the development and proliferation of smart meters. The increasingly growing computing capabilities for Internet of Things devices have made it possible for data to be processed directly from the devices where it is produced; this has been called edge computing. Edge computing is allowing the smart grid to become increasingly intelligent to solve problems that make electricity consumption more efficient and environmentally friendly. This work presents the implementation of a smart metering system that allows data analytics using a multiprocessing architecture directly on the smart meter. The results show that the development of smart meters with data analytics capabilities at the edge is a reality today, and the use of multiprocessing permits the improvement of data processing.

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