Policy trade-offs between climate mitigation and clean cook-stove access in South Asia

Household air pollution from traditional cook stoves presents a greater health hazard than any other environmental factor. Despite government efforts to support clean-burning cooking fuels, over 700 million people in South Asia could still rely on traditional stoves in 2030. This number could rise if climate change mitigation efforts increase energy costs. Here we quantify the costs of support policies to make clean cooking affordable to all South Asians under four increasingly stringent climate policy scenarios. Our most sringent mitigation scenario increases clean fuel costs 38% in 2030 relative to the baseline, keeping 21% more South Asians on traditional stoves or increasing the minimum support policy cost to achieve universal clean cooking by up to 44%. The extent of this increase depends on how poliymakers allocate subsidies between clean fuels and stoves. These additional costs are within the range of financial transfers to South Asia estimated in efforts-sharing scenarios of international climate agreements. Three billion people globally burn solid fuels such as firewood, charcoal, coal, dung, and crop resides in open fires and traditional stoves for cooking and heating. Household air pollution from the incomplete combustion of these fuels globally leads to 4.3 million premature deaths each year, with 1.7 million of those in South Asia. This exceeds the burden of disease from any other energy-related or environmental risk factor. Solid-fuel use also perpetuates income and gender inequality by forcing users, mostly poor women and children, to spend long hours collecting fuels and to suffer from its adverse health effects. To address this problem, the United Nations Secretary-General's Sustainable Energy for All (SE4All) initiative and the new Sustainable Development Goals aim to achieve universal access to modern energy services by 2030. Numerous intervention efforts have focused on distributing more efficient and cleaner burning biomass stoves, but several of these programmes have had little or no demonstrable impact on health outcomes. In India, the nation with the largest population of solid-fuel users globally, government interventions have sought to make petroleum-based fuels, such as kerosene and liquefied petroleum gas (LPG), more affordable through subsidy at an estimated cost of over US$6 billion per year. Although LPG use has grown rapidly, particularly in rural areas, over 72% of Indians continued to rely primarily on solid fuels in 2012. In the future, expanding clean cooking may become more challenging if climate policies increase the cost of fuels. Previous research has found that greenhouse gas (GHG) emissions reductions in Asia and Africa would increase the cost of kerosene and LPG. However, these studies do not explore compensatory policies that could counteract these effects, and assess only a limited set of climate mitigation scenarios. Only two studies explore normative scenarios that achieve access and climate goals simultanously, both of which do not explore the cost-effectiveness or distributional impacts on population subgroups of these policies. Meanwhile, studies that have evaluated the cost-effectiveness of energy access policies have not considered the impact of climate policy. Te latest assessment of the Intergovernmental Panel on Climate Change (IPCC) concludes that we have only low confidence in our understanding of the possible impacts of climate policy on access to modern energy services, and medium confidence in the policies needed to counteract them. In this study, we contribute new insights to the interaction of climate policy and clean cooking acces policies by quantifying the feasibility and costs of achieving universal access by 2030 for a range of climate policy stringencies, and under a wide range of fuel and stove price support policies. Our analysis suggests that the potential trade-offs between the two goals might be arger than suggested by previous studies. However, we find that efficient policy design could partially compensate for the additional access policy costs associated with climate mitigation. Furthermore, these costs fall below the level of potential financial transfers to South Asia that may result from international climate agreements

Stranded on a low-carbon planet: Implications of climate policy for the phase-out of coal-based power plants

Limiting global warming to 2 degrees C will likely entail the complete phase-out of coal-based electricity generation without carbon capture and storage (CCS). The timing and rate of this phase-out will depend on the stringency of near-term climate policy and will have important implications for the stranding of coal power plant capacity without CCS. The objectives of this paper are to better understand the relationship between near-term climate policy and stranded coal capacity (assuming a long-term goal of limiting warming to 2 degrees C) and to explore strategies for reducing stranded capacity. Our analysis suggests that strengthening near-term climate policy (i.e., lowering the global greenhouse gas emission target in 2030) generally reduces stranded coal capacity and its costs. An effective strategy for reducing stranded capacity is to minimize new construction of coal capacity without CCS, which can be accomplished by reducing electricity demand through energy intensity improvements and/or by keeping existing plants operating through lifetime extensions. Another strategy, providing emission exemptions for pre-existing coal plants (i.e., grandfathering), would eliminate stranded capacity, but also decreases the likelihood of achieving the 2 degrees C target. Finally, the ability of CCS retrofits to significantly reduce stranded capacity depends on how quickly the technology can be deployed

Summary of International Transport Energy Modeling Workshop

The NextSTEPS program at ITS-Davis convened a one-day workshop on international transportation energy modeling (iTEM), focused on comparing the frameworks and scenario projections from four major global transport models: -- Global Change Assessment Model (GCAM) by Pacific Northwest National Laboratory (PNNL) and ITS-Davis, -- MESSAGE-Transport (Model for Energy Supply Strategy Alternatives and their General Environmental Impact) by the International Institute for Applied Systems Analysis (IIASA), -- Mobility Model (MoMo) by the International Energy Agency, and -- Roadmap by the International Council on Clean Transportation (ICCT). Highlights: -- Projections of "baseline" global transportation energy use rise from 98 EJ in 2010 to 160-250 EJ by 2050. -- There are considerable differences in historical data for some modes, both globally and for individual countries (particularly non-OECD countries). Variability in estimates of transportation activity are in most cases much larger than energy differences. -- Global average vehicle ownership rates are projected to range from 270 to 450 per 1,000 people by 2050 with wide ranges across countries: 700-1,075 for the US by the middle of the century (US is around 700 today), 100-650 for China, and 80-380 for India across four models. -- All models rely mainly on GDP to estimate the future demand for freight and hold the base year modal shares (e.g. truck v. rail) roughly constant through 2050. In reality, future evolution will depend on characteristics of products (e.g. type of commodities) being shipped, technologies available for freight and their efficiencies, and policies and infrastructure. -- Current policy commitments toward EVs, PHEVs and H2FCVs (and thus baseline projections) maybe below the numbers suggested by iTEM models as required for meeting climate targets (e.g., 2 degrees C). -- Improvements in data quality and the representation of car ownership and use across the models were identified as priorities. Modeling transport energy use can either be done by estimating how far people travel and what mode of transportation they choose or by estimating how many vehicles there are and how far each one travels. These are complementary approaches, and in theory they should both lead to the same answer. The former approach, used in "service demand" models, seem more intuitive when one wants to model societal shifts in modes of transportation, either in emerging economies as they develop or in developed economies as they decarbonize; but collecting data on service demand is notoriously difficult. In contrast, vehicle stock models use readily-available vehicle sales data, but are harder to use in future-state, what-if scenarios (particularly in estimating modal shift behaviors) and thus require special attention by experts. The four iTEM models are different in terms of scope (GCAM and MESSAGE cover all sectors of the energy system vs. MoMo and Roadmap which cover transportation only) and model structure (GCAM and MESSAGE rely on internal drivers, particularly the costs of technology and travel, to project future changes whereas MoMo and Roadmap rely on experts' judgments and detailed analysis of technology and policies to drive long-term changes). Yet, owing to these differences, the models are highly complementary and in some cases can be used jointly to answer questions that no single model can tackle on its own. The following summary shares some of the comparisons and findings from the workshop

An Overview of the Palomar Transient Factory Pipeline and Archive at the Infrared Processing and Analysis Center

The Palomar Transient Factory is conducting a wide-field, variable-cadence optical survey of the northern sky to detect transient, variable, and moving objects. As a member of the PTF collaboration, the Infrared Processing and Analysis Center has developed an image archive, a high-quality photometry pipeline, and a searchable database of detected astronomical sources. The system is capable of processing and storing 300 Gbytes of data per night over the course of the 5-year survey. With an expected total of ~ 20 billion rows, the table containing sources extracted from PTF images will be among the largest astronomical databases ever created. The survey is efficiently discovering transient sources from asteroids to supernovae, and will inform the development of future sky surveys like that of the Large Synoptic Survey Telescope

Does Migration Make You Happy?:A Longitudinal Study of Internal Migration and Subjective Well-Being

The authors acknowledge financial support from the Economic and Social Research Council (ESRC) (RES-625-28-0001). This project is part of the ESRC Centre for Population Change (CPC). Financial support from the Marie Curie programme under the European Union's Seventh Framework Programme (FP/2007-2013) / Career Integration Grant n. PCIG10-GA-2011-303728 (CIG Grant NBHCHOICE, Neighbourhood choice, neighbourhood sorting, and neighbourhood effects).The majority of quantitative studies on the consequences of internal migration focus almost exclusively on the labour-market outcomes and the material well-being of migrants. We investigate whether individuals who migrate within the UK become happier after the move than they were before, and whether the effect is permanent or transient. Using life-satisfaction responses from twelve waves of the British Household Panel Survey and employing a fixed-effects model, we derive a temporal pattern of migrants’ subjective well-being around the time of the migration event. Our findings make an original contribution by revealing that, on average, migration is preceded by a period when individuals experience a significant decline in happiness for a variety of reasons, including changes in personal living arrangements. Migration itself causes a boost in happiness, and brings people back to their initial levels. The research contributes, therefore, to advancing an understanding of migration in relation to set-point theory. Perhaps surprisingly, long-distance migrants are at least as happy as short-distance migrants despite the higher social and psychological costs involved. The findings of this paper add to the pressure to retheorize migration within a conceptual framework that accounts for social well-being from a life-course perspective.PostprintPeer reviewe

Expedition Earth and Beyond: Engaging Classrooms in Student-Led Research Using NASA Data, Access to Scientists, and Integrated Educational Strategies

Classroom teachers are challenged with engaging and preparing today s students for the future. Activities are driven by state required skills, education standards, and high-stakes testing. Providing educators with standards-aligned, inquiry-based activities that will help them engage their students in student-led research in the classroom will help them teach required standards, essential skills, and help inspire their students to become motivated learners. The Astromaterials Research and Exploration Science (ARES) Education Program, classroom educators, and ARES scientists at the NASA Johnson Space Center created the Expedition Earth and Beyond education program to help teachers promote student-led research in their classrooms (grades 5-14) by using NASA data, providing access to scientists, and using integrated educational strategies

Renormalization Group Analysis of a Quivering String Model of Posture Control

Scaling concepts and renormalization group (RG) methods are applied to a simple linear model of human posture control consisting of a trembling or quivering string subject to damping and restoring forces. The string is driven by uncorrelated white Gaussian noise intended to model the corrections of the physiological control system. We find that adding a weak quadratic nonlinearity to the posture control model opens up a rich and complicated phase space (representing the dynamics) with various non-trivial fixed points and basins of attraction. The transition from diffusive to saturated regimes of the linear model is understood as a crossover phenomenon, and the robustness of the linear model with respect to weak non-linearities is confirmed. Correlations in posture fluctuations are obtained in both the time and space domain. There is an attractive fixed point identified with falling. The scaling of the correlations in the front-back displacement, which can be measured in the laboratory, is predicted for both the large-separation (along the string) and long-time regimes of posture control.Comment: 20 pages, 13 figures, RevTeX, accepted for publication in PR

Thermoplastic coating of carbon fibers

Now that quantities of prepreg were made on the thermoplastic coating line, they are being formed into both textile preform structures and directly into composite samples. The textile preforms include both woven and knitted structures which will be thermoformed into a finished part. In order to determine if the matrix resin is properly adhering to the fibers or if voids are being formed in the coating process, the tensile strength and modulus of these samples will be tested. The matrix uniformity of matrix distribution in these samples is also being determined using an image analyzer