• Energy Research

India's Intended Nationally Determined Contributions in 2015 toward the Two‐Degree Celsius climate change goal has endorsed 15% of renewable integration in the primary energy mix by 2020. The energy space is strategy to meet the target without affecting its immediate sustainable development goals. This study documents this strategic effort by tracking the historical trajectory of energy policy planning since its independence in 1947. An objective ontological approach was adopted in reviewing the evolution of energy policy into five distinct phases. Phase I (1947–1970), focused on supply adequacy with the overall thrust on infrastructure development as the pillar of Indian economy. In Phase II (the 1970s) the focus shifted in addressing the energy access crisis. Phase III (the 1980s) was based on increment, diversification, and streamlining on supplies for energy security purposes. Phase IV (the 1990s) is the period of modernization of the overall Indian electricity system. Phase V (the 2000s) is the present phase of market transformation and climate change mitigation energy policies. A co‐assessment of India's policy to the international climate negotiations showed that India remained responsive to international climate goals. It became reactive in the planning for sustainable energy policy after its ratification of Kyoto Protocol in 2001. Since then, India has been instrumental in administering strict emission reduction norms and efficiency measures. This review concludes that the country needs to upgrade its inefficient transmission and distribution networks, which was broadly neglected. The subsidy allocations in domestic energy resources should be well‐adjusted without compromising on its social costs.This article is categorized under: Energy and Climate > Economics and Policy Energy Infrastructure > Climate and Environment Energy Policy and Planning > Climate and Environment

Rural off-grid renewable energy solutions often fail due to uncertainties in household energy demand, insufficient community engagement, inappropriate financial models and policy inconsistency. Social shaping of technology (SST) of household appliances provides a critical lens of understanding the involved socio-technical drivers behind these constraints. This study employs an SST lens to investigate appliance uptake drivers in 14,580 households in Rwanda, such that these drivers can aid in policy design for green growth at the grassroots level. The methodology includes an epistemological review of non-income drivers of appliance uptake. Empirical analysis using a binary logistic regression, based on which disruptive innovation pathways were derived for fostering green growth. Results showed that appliance uptake was highly gendered and skewed across the Ubudehe (social welfare) categories. ICT-devices like mobile phones and radios had a higher likelihood of ownership than welfare appliances like refrigerator and laundry machines. Fans and cookers also demonstrated a greater probability of ownership. Disruptive innovation pathways were derived from leveraging the ICT-driven wave of appliance ownership, creation of service sectors through off-grid renewable solutions and promoting cleaner fuel-switching of cooking energy at the household level. Further policy implications were drawn to support the creation of consumption identities for green growth.

Around a billion people live in slums today globally, and rehabilitating them to formal housing is a significant challenge. Slum rehabilitation housing is a policy effort to solve this crisis and alleviate urban poverty. However, the question of whether slum rehabilitation programmes are accomplishing more good than harm or whether they are creating a whole host of new problems remains unexplored in the literature. This thesis investigates the effect of slum rehabilitation on household energy demand in Brazil, India and Nigeria through the lens of distributive energy justice. Furthermore, this thesis makes methodological innovation to aid in just policy design by improving the objectivity of including local and contextual knowledge on how poor households live and use energy. Doing so makes novel theoretical and methodological contributions: a theoretical contribution to temporality and spatial energy justice studies on how to offer cross-sectional depictions of energy demand within the slum rehabilitation housing, which was evaluated through structural equation modelling, and a methodological contribution in developing a deep-narrative analysis framework using natural language processing and machine learning-based Latent Dirichlet Allocation algorithm to capture the grounded narratives of distributive injustices objectively. This research highlighted the significance of contextualisation in planning for energy justice in slum communities and the role of digital tools like natural language processing in objectively integrating grounded narratives in just policy design. The contextualisation was done through zoom-in and zoom-out of the grounded narratives enabled through the multi-method approach. Zooming-out view of distributed injustices in the study areas of Mumbai (India), Rio de Janeiro (Brazil) and Abuja (Nigeria) revealed inefficiencies in the administration of electricity distribution companies, lumped billing periods and lack of people-centric built environment design considerations. Similarly, zooming-in the case studies revealed that the poor design of the slum rehabilitation-built environment influenced the increase in energy intensity in the Mumbai case, leading to energy poverty. Whereas created distinct poverty traps in the Brazilian and Nigerian cases through frequent power cuts, high cost of appliance repair, and poor housing design. Finally, policy implications were drawn as per the policy actors across municipal, state and national levels that suggested leveraging digital tools like the deep-narrative analysis and the heavy penetration of Information and Communication Technology devices in such low-income communities. Such tools can improve accountability in decision-making and improve the representation of the occupants through their narratives of injustices associated with living in such communities. Thus, this thesis uniquely forwarded a data-driven pathway for integrating local collective intelligence in just policy design.

This study explores the effect of slum rehabilitation on appliance ownership and its implications on residential electricity demand. The low-income scenario makes it unique because the entire proposition is based on the importance of non-income drivers of appliance ownership that includes effects of changing the built environment (BE), household practices (HP) and appliances characteristics (AC). This study demonstrates quantitatively that non-income factors around energy practices influence appliance ownership, and therefore electricity consumption. The methodology consists of questionnaire design across the dimension of BE, HP and AC based on social practice theory, surveying of 1224 households and empirical analysis using covariance-based structural equation modelling. Results show that higher appliance ownership in the slum rehabilitation housing is due to change in household practice, built environment and affordability criteria of the appliances. Change in HP shifts necessary activities like cooking, washing and cleaning from outdoor to indoor spaces that positively and significantly influences higher appliance ownership. Poor BE conditions about indoor air quality, thermal comfort and hygiene; and product cost, discounts and ease of use of the appliances also triggers higher appliance ownership. The findings of this study can aid in designing better regulatory and energy efficiency policies for low-income settlements.

Rural off-grid renewable energy solutions often fail due to uncertainties in household energy demand, insufficient community engagement, inappropriate financial models, policy inconsistency and lack of political will. Social shaping of technology (SST) of specific household electric appliances provides a critical lens of understanding the involved socio-technical drivers behind these constraints. This study employs an SST lens to investigate appliance uptake drivers in Rwanda using the EICV5 micro dataset, such that these drivers can aid in policy design of a socially inclusive renewable energy transition. The methodology includes a systemic and epistemological review of current literature on the drivers of appliance uptake in the Global South. These drivers were then analysed using binary logistic regression on 14,580 households. Results show that appliance uptake is highly gendered in Rwanda and the type of appliance determines its diffusion across the welfare categories, commonly referred as to Ubudehe categories. Regression results show that mobile phones, radios and TV-sets have a higher likelihood of ownership than welfare appliances (refrigerator and laundry machine) by low-income households. There is also a high likelihood of uptake of power stabilisers in urban areas, indicating poor power quality. Policy implications were drawn using the lens of disruptive innovation.

AbstractExtensive research highlights global and within-country inequality in personal carbon footprints. However, the extent to which people are aware of these inequalities remains unclear. Here we use an online survey distributed across four diverse countries: Denmark, India, Nigeria and the USA, to show widespread underestimation of carbon footprint inequality, irrespective of participants’ country and income segment. Of the 4,003 participants, within each country, 50% of participants were sampled from the top 10% income group. Our results show links between carbon footprint inequality perceptions and climate policy support, but with significant variations observed across the four countries and with participants’ income segments. Furthermore, there are links to the perceived fairness of actual carbon footprint inequality, highlighting the need to raise awareness about carbon footprint inequality and further unpack its implications for climate justice and policy.

© 2016 The Authors. Daylight is an important element of energy efficient buildings. Energy savings from artificial lighting during the daytime can have significant impact on the energy sustainability residential buildings. For a city like Mumbai, where the buildings have limited access to daylight due to the sprawling of densely packed high rise buildings, energy saving from daylighting can be an effective driver of sustainability. Under this purview, it is prudent to evaluate the effects of various building design elements like orientation and window-to-wall ratio (WWR) on energy saving potential through daylighting. In this study, two parameters of daylight incidences: Useful Daylight Illuminance (UDI) and annual light exposure, were studied to understand the daylight performance of a high rise residential building. UDI values were then reiterated by varying the orientation and WWR. The results showed that the building performed best at the South-East orientation with a WWR of 50% which allowed 63% more ambient illuminance in the functional space. This study also unveils the paradigm that ambient illuminance inside the functional space of the building may be independent of total incident annual light exposure in the rooms. That means more annual exposure does not necessarily means better lighting conditions within the indoor functional space. Hence, this study creates a way forward in designing energy efficient buildings using UDI as a daylight performance metric.