• Energy Research
• 2016-2025close
• National Science Foundation close
• 1. No poverty close

“Modern energy for all,” an internationally supported initiative to connect populations to electricity services, is expected to help reduce poverty-induced vulnerabilities. It has become a primary strategy for meeting sustainable development goals, especially in sub-Saharan Africa. However, when electricity is supplied by a capacity-constrained grid to a resource-constrained population, the service quality can vary both spatially and temporally. This research explores the quality of electricity services based on a case study of Unguja, Tanzania. Using 1) open-ended interviews, 2) detailed electricity-systems monitoring, and 3) household surveys, we show how voltage quality varies significantly, even within highly localized settings. Fluctuations result in dim lights at best and power outages and broken appliances at worst, denying many Unguja residents the expected benefits of access to modern energy. By combining an extensive understanding of the physical system together with interviews and surveys, this work presents a unique mapping of voltage quality in a system that is financially and physically constrained and highlights the consequences of poor-quality service for poor users.

Climate change risks like extreme temperatures and high variability in rainfall adversely affect livelihoods, particularly for farmers in Burkina Faso where the primary sector is agriculture. Decisions on whether to adapt to these risks depend on how farmers perceive each risk and the resources they have available. In this study, we examine how long-term changes in temperature and rainfall are perceived by farmers in Burkina Faso. We also compare the extent to which these perceptions align with actual recorded changes in temperature and rainfall for multiple periods between 1991 and 2014. We use a logistic regression model to analyze the role of resources, such as asset ownership and perceived standards of living, along with household size, age, and gender of the household head to explain differences in perception and ultimately the decision to adapt. Our results show that the vast majority of farmers in Burkina Faso perceive changes in temperature and rainfall; however, only about half of those individuals perceive changes in ways that align with recorded long-term trends in their local temperature or rainfall. The extent to which those perceptions align with recorded changes depends on the time frame selected. Older farmers and those with assets were less likely to perceive temperature and rainfall trends in ways that aligned with climate records; however, farmers' perceptions of temperature change aligning with records and their perceived standard of living were both associated with the decision to adapt. This misalignment of perceptions with records and resources has significant implications for efforts to inform and support climate risk mitigation and adaptation.

As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments. We review the history and state of the art of models used in climate research, including integrated assessment models (IAMs) and national studies, and those that model mitigation and climate-change impacts. We assess how and to what extent they represent distributional impacts within countries. We argue that there is much scope to improve the representation of income distribution and poverty. Given the diversity of models, this endeavour presents fundamental challenges for some models, but possibly requires only incremental changes in others.

The paper considers a bidirectional power flow model of the electric vehicles (EVs) in a charging station. The EVs can inject energies by discharging via a Vehicle-to-Grid (V2G) service which can enhance the profits of the charging station. However, frequent charging and discharging degrade battery life. A proper compensation needs to be paid to the users to participate in the V2G service. We propose a menu-based pricing scheme, where the charging station selects a price for each arriving user for the amount of battery utilization, the total energy, and the time (deadline) that the EV will stay. The user can accept one of the contracts or rejects all depending on their utilities. The charging station can serve users using a combination of the renewable energy and the conventional energy bought from the grid. We show that though there exists a profit maximizing price which maximizes the social welfare, it provides no surplus to the users if the charging station is aware of the utilities of the users. If the charging station is not aware of the exact utilities, the social welfare maximizing price may not maximize the expected profit. In fact, it can give a zero profit. We propose a pricing strategy which provides a guaranteed fixed profit to the charging station and it also maximizes the expected profit for a wide range of utility functions. Our analysis shows that when the harvested renewable energy is small the users have higher incentives for the V2G service. We, numerically, show that the charging station's profit and the user's surplus both increase as V2G service is efficiently utilized by the pricing mechanism. Submitted in IEEE Transactions on Automatic Control. arXiv admin note: substantial text overlap with arXiv:1609.09037

The 2030 Agenda for Sustainable Development outlines 17 individual Sustainable Development Goals (SDGs) that guide the needs of practice for many professional disciplines around the world, including engineering, research, policy, and development. The SDGs represent commitments to reduce poverty, hunger, ill health, gender inequality, environmental degradation, and lack of access to clean water and sanitation. If a typical reductionist approach is employed to address and optimize individual goals, it may lead to a failure in technological, policy, or managerial development interventions through unintended consequences in other goals. This study uses a systems approach to understand the fundamental dynamics between the SDGs in order to identify potential synergies and antagonisms. A conceptual system model was constructed to illustrate the causal relationships between SDGs, examine system structures using generic system archetypes, and identify leverage points to effectively influence intentional and minimize unintentional changes in the system. The structure of interactions among the SDGs reflects three archetypes of system behavior: Reinforcing Growth, Limits to Growth, and Growth and Underinvestment. The leverage points identified from the conceptual model are gender equality, sustainable management of water and sanitation, alternative resources, sustainable livelihood standards, and global partnerships. Such a conceptual system analysis of SDGs can enhance the likelihood that the development community will broaden its understanding of the potential synergistic benefits of their projects on resource management, environmental sustainability, and climate change. By linking the interactions and feedbacks of those projects with economic gains, women’s empowerment, and educational equality, stakeholders can recognize holistic improvements that can be made to the quality of life of many of the world’s poor.

Increased frequency and length of high heat episodes are leading to more cardiovascular issues and asthmatic responses among the population of San Juan, the capital of the island of Puerto Rico, USA. An urban heat island effect, which leads to foci of higher temperatures in some urban areas, can raise heat-related mortality. The objective of this research is to map the risk of high temperature in particular locations by creating heat maps of the city of San Juan. The heat vulnerability index (HVI) maps were developed using images collected by satellite-based remote sensing combined with census data. Land surface temperature was assessed using images from the Thermal Infrared Sensor flown on Landsat 8. Social determinants (e.g., age, unemployment, education and social isolation, and health insurance coverage) were analyzed by census tract. The data were examined in the context of land cover maps generated using products from the Puerto Rico Terrestrial Gap Analysis Project (USDA Forest Service). All variables were set in order to transform the indicators expressed in different units into indices between 0 and 1, and the HVI was calculated as sum of score. The tract with highest index was considered to be the most vulnerable and the lowest to be the least vulnerable. Five vulnerability classes were mapped (very high, high, moderate, low, and very low). The hottest and the most vulnerable tracts corresponded to highly built areas, including the Luis Munoz International Airport, seaports, parking lots, and high-density residential areas. Several variables contributed to increased vulnerability, including higher rates of the population living alone, disabilities, advanced age, and lack of health insurance coverage. Coolest areas corresponded to vegetated landscapes and urban water bodies. The urban HVI map will be useful to health officers, emergency preparedness personnel, the National Weather Service, and San Juan residents, as it helps to prepare for and to mitigate the potential effects of heat-related illnesses.

Globally, environmental and social change in water-scarce regions challenge the sustainability of social-ecological systems. WaterSES, a sponsored working group within the Program for Ecosystem Change and Society, explores and compares the social-ecological dynamics related to water scarcity across placed-based international research sites with contrasting local and regional water needs and governance, including research sites in Spain and Sweden in Europe, South Africa, China, and Alabama, Idaho, Oklahoma, and Texas in the USA. This paper aims to provide a commentary on insights into conducting future solutions-oriented research on water scarcity based on the understanding of the social-ecological dynamics of water scarce regions.