A system dynamics analysis of the growth in Virginia\u27s residential electricity consumption trends, 1980-2010.

Residential electricity consumption in the Commonwealth of Virginia has more than doubled in three decades, between 1980 and 2010. Per capita and per household consumption rates have grown faster than many other states including New York and California. The following dissertation applies systems dynamics methodology to explore the causes of growth in Virginia’s per capita and per household residential electricity consumption rates in relative contrast to New York and California over the past several decades. Major databases used in the study were accessed from the United States Energy Information Administration and the Census Bureau. Qualitative modelling applying system dynamics principles is used to understand the general dynamics that drive residential electricity consumption across U.S households. The extent to which these dynamics prevail in Virginia is then analyzed using the state’s historical data. Further comparative analysis with benchmark states of New York and California helps identify if those dynamics uniquely prevail in Virginia or are common across the benchmark states too. The study finds that a combination of economic and lifestyle factors among Virginia’s residents, compounded by a low-cost high-volume ‘business as usual’ strategy by the state’s power utility sector with negligible investments in demand side management efforts, have worked relentlessly to cause per capita and per household residential electricity consumption rates to rise in the Commonwealth during the three decades. The results of this study are intended to support in better management of residential electricity consumption rates in the Commonwealth of Virginia. Public educational programs, Government tax credits and rebates, and stronger utility demands side management are key recommendations in the interest of addressing the issue. A successful future reduction in consumption rates will help lessen pressures on the state’s economy as well as the environment

The drivers of Chinese CO2 emissions from 1980 to 2030

China's energy consumption doubled within the first 25 years of economic reforms initiated at the end of the 1970s, and doubled again in the past 5 years. It has resulted of a threefold CO2 emissions increase since early of 1980s. China's heavy reliance on coal will make it the largest emitter of CO2 in the world. By combining structural decomposition and input–output analysis we seek to assess the driving forces of China's CO2 emissions from 1980 to 2030. In our reference scenario, production-related CO2 emissions will increase another three times by 2030. Household consumption, capital investment and growth in exports will largely drive the increase in CO2 emissions. Efficiency gains will be partially offset the projected increases in consumption, but our scenarios show that this will not be sufficient if China's consumption patterns converge to current US levels. Relying on efficiency improvements alone will not stabilize China's future emissions. Our scenarios show that even extremely optimistic assumptions of widespread installation of carbon dioxide capture and storage will only slow the increase in CO2 emissions

Estimating direct and indirect rebound effects for UK households

Energy efficiency improvements by households lead to rebound effects that offset the potential energy and emissions savings. Direct rebound effects result from increased demand for cheaper energy services, while indirect rebound effects result from increased demand for other goods and services that also require energy to provide. Research to date has focused upon the former, but both are important for climate change. This study estimates the combined direct and indirect rebound effects from seven measures that improve the energy efficiency of UK dwellings. The methodology is based upon estimates of the income elasticity and greenhouse gas (GHG) intensity of 16 categories of household goods and services, and allows for the embodied emissions of the energy efficiency measures themselves. Rebound effects are measured in GHG terms and relate to the adoption of these measures by an average UK household. The study finds that the rebound effects from these measures are typically in the range 5-15% and arise mostly from indirect effects. This is largely because expenditure on gas and electricity is more GHG-intensive than expenditure on other goods and services. However, the anticipated shift towards a low carbon electricity system in the UK may lead to much larger rebound effects

Forecasting scenarios for UK household expenditure and associated GHG emissions : Outlook to 2030

Peer reviewedPreprin

Monitoring of the “Energiewende” – energy efficiency indicators for Germany

The increasing number of energy and climate targets both at national and international level induces a rising demand for regular monitoring. In this paper, we analyse the possibilities and limits of using energy efficiency indicators as a tool for monitoring these targets. We refer to the energy efficiency targets of the German “Energiewende” and calculate and discuss several energy efficiency indicators for Germany both at the level of the overall economy and the main energy consumption sectors. We make use of the energy efficiency indicator toolbox that we have developed within the ODYSSEE database in recent years and find that there is still a considerable gap to close to achieve the overall energy efficiency targets in Germany by 2020. We also show that progress in energy efficiency slowed down between 2008 and 2012, i.e. compared to the base year of most of the German energy efficiency targets and find that energy efficiency progress in the industrial sector during the last decade has been especially slow. We conclude that improvements in energy efficiency have to speed up considerably in order to achieve the targets for 2020. Although the use of energy efficiency indicators is limited by data constraints and some methodological problems, these indicators give a deep insight into the factors determining energy consumption and can therefore complement the official monitoring process of the German “Energiewende” which only relies on highly aggregated indicators for energy efficiency

Environmental actions to reduce household ecological footprints

This paper presents the ideas of UK householders on how to reduce their Ecological Footprint (EF) after applying a tool called 'EcoCal', which assesses the environmental impacts of households by measuring footprints arising from Transport, Energy, Shopping, House and Garden, Water and Waste. Analysis of the EcoCal results of nearly 700 adult Open University (OU) student households showed that transport and energy impacts are the biggest contributors to the household footprint. Reducing these impacts poses the greatest challenge to achieving a globally sustainable household EF of approximately 0.5 hectares per person. Analysis of the ideas that the OU students were prepared to consider to reduce their household EF revealed a variety of technical and behavioural changes. However, in the context of their own household, the OU students identified several constraints on the implementation of their environmental action plans. Despite such constraints, many of the students instigated changes that helped to make their households more sustainable

One More Awareness Gap? The Behaviour–Impact Gap Problem

Preceding research has made hardly any attempt to measure the ecological impacts of pro-environmental behaviour in an objective way. Those impacts were rather supposed or calculated. The research described herein scrutinized the ecological impact reductions achieved through pro-environmental behaviour and raised the question how much of a reduction in carbon footprint can be achieved through voluntary action without actually affecting the socio-economic determinants of life. A survey was carried out in order to measure the difference between the ecological footprint of “green” and “brown” consumers. No significant difference was found between the ecological footprints of the two groups—suggesting that individual pro-environmental attitudes and behaviour do not always reduce the environmental impacts of consumption. This finding resulted in the formulation of a new proposition called the BIG (behaviour–impact gap) problem, which is an interesting addition to research in the field of environmental awareness gaps

Residential electricity consumption and economic growth in Algeria

Within the framework of the COP21 (Conference of the Parties) agreement, Algeria submitted its Intended Nationally Determined Contribution pledging to reduce carbon emissions by at least 7% by 2030. However, it will be a difficult task to reach this target as total final energy consumption has increased 32% from 2010 to 2014, with the major energy increases being related to electricity use in the residential sector. In this context, the relationship between residential electricity consumption and income is analyzed for Algeria in the period 1970–2013, by estimating a residential electricity consumption per capita demand function which depends on GDP per capita, its squared and cubed terms, the electricity prices, and the goods and services imports. An extended Autoregressive Distributed Lag model (ARDL) was adopted to consider the different growth patterns registered in the evolution of GDP. The estimate results show that the relationships between electricity use and GDP (in per capita terms) present an inverted N-shape, with the second turning point having been reached. Therefore, promoting growth in Algeria could be convenient to reduce the electricity consumption, as a higher income level may allow the use of more efficient appliances. Additionally, renewable energies may be adequate to increase the electricity production in order to cover the increasing residential demand.Junta de Andalucía proyecto SEJ-132Ministerio de Economía y Competitividad de España, Cátedra de Economía de la Energía y del Medio Ambiente (Cátedra de Energía y Economía Ambiental) ECO2014-56399-

Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China

The fine-grained electricity consumption data created by advanced metering technologies offers an opportunity to understand residential demand from new angles. Although there exists a large body of research on demand response in short- and long-term forecasting, a comprehensive analysis to identify household consumption behaviour in different scenarios has not been conducted. The study’s novelty lies in its use of unsupervised machine learning tools to explore residential customers’ demand patterns and response without the assistance of traditional survey tools. We investigate behavioural response in three different contexts: 1) seasonal (using weekly consumption profiles); 2) holidays/festivals; and 3) extreme weather situations. The analysis is based on the smart metering data of 2,000 households in Chengdu, China over three years from 2014 to 2016. Workday/weekend profiles indicate that there are two distinct groups of households that appear to be white-collar or relatively affluent families. Demand patterns at the major festivals in China, especially the Spring Festival, reveal various types of lifestyle and households. In terms of extreme weather response, the most striking finding was that in summer, at night-time, over 72% of households doubled (or more) their electricity usage, while consumption changes in winter do not seem to be significant. Our research offers more detailed insight into Chinese residential consumption and provides a practical framework to understand households’ behaviour patterns in different settings

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