• Energy Research

AbstractAnthropogenic climate change is a global problem that affects every country and each individual. It is largely caused by human beings emitting greenhouse gases into the atmosphere. In general, a small percentage of the population is responsible for a large amount of emissions. This paper focuses on high emitters and their CO2 emissions from energy use in UK homes. It applies a cluster approach, aiming to identify whether the high emitters comprise clusters where households in each cluster share similar characteristics but are different from the others. The data are mainly based on the Living Cost and Food survey in the UK. The results show that after equivalising both household emissions and income, the high emitters can be clustered into six groups which share similar characteristics within each group, but are different from the others in terms of income, age, household composition, category and size of the dwelling, and tenure type. The clustering results indicate that various combinations of socioeconomic factors, such as low-income single female living in an at least six-room property, or high-income retired couple owning a large detached house, could all lead to high CO2 emissions from energy use at home. Policymakers should target each high-emitter cluster differently to reduce CO2 emissions from energy consumption at home more effectively.

AbstractAnthropogenic climate change is a global problem that affects every country and each individual. It is largely caused by human beings emitting greenhouse gases into the atmosphere. In general, a small percentage of the population is responsible for a large amount of emissions. This paper focuses on high emitters and their CO2 emissions from energy use in UK homes. It applies a cluster approach, aiming to identify whether the high emitters comprise clusters where households in each cluster share similar characteristics but are different from the others. The data are mainly based on the Living Cost and Food survey in the UK. The results show that after equivalising both household emissions and income, the high emitters can be clustered into six groups which share similar characteristics within each group, but are different from the others in terms of income, age, household composition, category and size of the dwelling, and tenure type. The clustering results indicate that various combinations of socioeconomic factors, such as low-income single female living in an at least six-room property, or high-income retired couple owning a large detached house, could all lead to high CO2 emissions from energy use at home. Policymakers should target each high-emitter cluster differently to reduce CO2 emissions from energy consumption at home more effectively.

Abstract Energy resilience is a complex issue, encapsulating a diversity of factors. Such complexity makes effective policymaking difficult, and requires a whole-systems approach. This paper argues that the bottom-up participatory causal loop mapping method can be helpful in facilitating a shared understanding of the issues, and can help facilitate the application of a whole-systems approach to the design of effective policy interventions. Focusing on Nepal as a case study, this paper outlines the participatory approach, highlighting the method’s value in visualising the variables and interconnections affecting the resilience of Nepal’s electricity supply. Through the mapping, participants identified four interconnected groups of factors as important for resilience: governance, technology, economic and social. Within these, political leadership was noted as particularly important. Environmental factors were largely absent, which is an interesting result given the emphasis on renewable sources and clean technologies in energy policy in Nepal. The outcomes of our bottom-up participatory approach show the significant benefit of using this approach for highlighting context-dependent understandings of complex issues and represents a novel methodological innovation for energy research, which could be applied in diverse geographies and contexts.

Abstract Energy resilience is a complex issue, encapsulating a diversity of factors. Such complexity makes effective policymaking difficult, and requires a whole-systems approach. This paper argues that the bottom-up participatory causal loop mapping method can be helpful in facilitating a shared understanding of the issues, and can help facilitate the application of a whole-systems approach to the design of effective policy interventions. Focusing on Nepal as a case study, this paper outlines the participatory approach, highlighting the method’s value in visualising the variables and interconnections affecting the resilience of Nepal’s electricity supply. Through the mapping, participants identified four interconnected groups of factors as important for resilience: governance, technology, economic and social. Within these, political leadership was noted as particularly important. Environmental factors were largely absent, which is an interesting result given the emphasis on renewable sources and clean technologies in energy policy in Nepal. The outcomes of our bottom-up participatory approach show the significant benefit of using this approach for highlighting context-dependent understandings of complex issues and represents a novel methodological innovation for energy research, which could be applied in diverse geographies and contexts.

The rapid growth of household electricity consumption is threatening the sustainable development of China’s economy and environment because of its impacts on the operation efficiency of the electric power system. To recognize the driving factors of the consumption growth and offer policy implications, based on the consumption-related data of 2015 and 2016, this research used the rank sum ratio (RSR) method to divide China’s 30 provinces into 5 groups and a logarithmic mean Divisia index (LMDI) algorithm to decompose the composition growth of each group into the quantitative contribution of each driving factor. The following conclusions were drawn from the empirical analysis. (1) The Yangtze basin is the most vigorous region of consumption growth and should be principally monitored. (2) Climate conditions have a remarkable impact on consumption growth and should be a key consideration when making differentiated household electricity policies. (3) The rebound effect has already appeared in a few of the most developed regions. Electricity price is an effective measure in dealing with this effect. (4) The improvement of the income level is the most important driving factor for consumption growth. (5) For provinces with high growth vitality, the change in the burden level of electricity expenditure prompts consumption growth. However, for provinces with low growth vitality, the situations are opposite. (6) The impacts of electricity price and population on consumption growth are negligible.

The rapid growth of household electricity consumption is threatening the sustainable development of China’s economy and environment because of its impacts on the operation efficiency of the electric power system. To recognize the driving factors of the consumption growth and offer policy implications, based on the consumption-related data of 2015 and 2016, this research used the rank sum ratio (RSR) method to divide China’s 30 provinces into 5 groups and a logarithmic mean Divisia index (LMDI) algorithm to decompose the composition growth of each group into the quantitative contribution of each driving factor. The following conclusions were drawn from the empirical analysis. (1) The Yangtze basin is the most vigorous region of consumption growth and should be principally monitored. (2) Climate conditions have a remarkable impact on consumption growth and should be a key consideration when making differentiated household electricity policies. (3) The rebound effect has already appeared in a few of the most developed regions. Electricity price is an effective measure in dealing with this effect. (4) The improvement of the income level is the most important driving factor for consumption growth. (5) For provinces with high growth vitality, the change in the burden level of electricity expenditure prompts consumption growth. However, for provinces with low growth vitality, the situations are opposite. (6) The impacts of electricity price and population on consumption growth are negligible.

To improve access to affordable, reliable and sustainable energy in rural areas of the global south, off-grid systems using renewable generation and energy storage are often proposed. However, solution design is often technology-driven, with insufficient consideration of social and cultural contexts. This leads to a risk of unintended consequences and inappropriate systems that do not meet local needs. To address this problem, this paper describes the application of a capabilities-led approach to understanding a community’s multi-dimensional energy poverty and assessing their needs as they see them, in order to better design suitable technological interventions. Data were collected in Tlamacazapa, Mexico, through site visits and focus groups with men and women. These revealed the ways in which constrained energy services undermined essential capabilities, including relating to health, safety, relationships and earning a living, and highlighted the specific ways in which improved energy services, such as lighting, cooking and mechanical power could improve capabilities in the specific context of Tlamacazapa. Based on these findings, we propose some potential technological interventions to address these needs. The case study offers an illustration of an assessment method that could be deployed in a variety of contexts to inform the design of appropriate technological interventions.

To improve access to affordable, reliable and sustainable energy in rural areas of the global south, off-grid systems using renewable generation and energy storage are often proposed. However, solution design is often technology-driven, with insufficient consideration of social and cultural contexts. This leads to a risk of unintended consequences and inappropriate systems that do not meet local needs. To address this problem, this paper describes the application of a capabilities-led approach to understanding a community’s multi-dimensional energy poverty and assessing their needs as they see them, in order to better design suitable technological interventions. Data were collected in Tlamacazapa, Mexico, through site visits and focus groups with men and women. These revealed the ways in which constrained energy services undermined essential capabilities, including relating to health, safety, relationships and earning a living, and highlighted the specific ways in which improved energy services, such as lighting, cooking and mechanical power could improve capabilities in the specific context of Tlamacazapa. Based on these findings, we propose some potential technological interventions to address these needs. The case study offers an illustration of an assessment method that could be deployed in a variety of contexts to inform the design of appropriate technological interventions.