Wait, cities can do what? Achieving city energy goals through franchise agreements
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Cook, Jeffrey J.↗
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Results for “goal”
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An Introduction to the E3SM Special Collection: Goals, Science Drivers, Development, and Analysis
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54 ENVIRONMENTAL SCIENCES↗
Inverse Reinforcement Learning based Bayesian Goal Inference Method for Early Nuclear Proliferation Detection
Traditional methods for detection of nuclear proliferation indicators are usually applied after nuclear proliferation has already occurred. There is a need to advance these methods to perform early detection of nuclear proliferation indicators. In this project, we formulated an early detection problem as a sequential, decision-making, goal inference problem based on research publications of authors, to determine whether it is possible to infer whether an author will publish on a research activity before it has occurred. To develop and test our approach, we selected a civil nuclear activity for our case study. We constructed a state-action-state transition graph from publications of authors associated with the activity and the co-authors of their publications, using titles, abstracts, and author publication sequences. We then used inverse reinforcement learning to model the goal-directed behavior of authors in trajectories that terminate at selected goal states. Using a Bayesian formulation, we computed the probability that authors would reach each selected state from partially observed trajectories of their state transitions in their research topic space. The state with the highest probability was selected as the most probable goal state. Based on our results, we found that 60% of the times we can infer the correct goal state early; sometimes the inference is either delayed, or multiple states could be inferred as goal states. Overall, our results show that it is possible to perform early detection of research activities of authors in a nuclear technology area. Further research is necessary to establish a more accurate understanding of how topic modeling, topic space grid discretization, and the extent of overlap among trajectories of different goal states, affect the goal inference results. The methods developed in this work may be used to enhance data-driven methods for early detection of nuclear proliferation indicators.
97 MATHEMATICS AND COMPUTING↗
How do Management Goals for Wild Chinook Salmon Align with Feasibility?
Evaluation of goals is crucial for effective management to conserve viable and diverse fish populations and to support harvest. Management of wild Chinook Salmon Oncorhynchus tshawytscha in the Snake River basin exemplifies the struggle to meet fisheries goals. Considering contemporary production of juvenile emigrants, it is imperative to determine the survival from emigration to adult ( S e‐a ) required to meet abundance goals. Increased anthropogenic impact on spawning and rearing habitats leads to higher S e‐a required to attain goals. Wilderness populations exhibit viability and could sustain fisheries with S e‐a lower than required elsewhere. Conversely, populations targeted for habitat restoration demand higher S e‐a to fulfill goals, indicating a need to enhance egg‐to‐smolt survival. However, S e‐a has fallen below the threshold needed for replacement in all populations, even at current low abundances. Despite these challenges, most populations still possess the potential to achieve abundance goals, emphasizing the importance of strategic interventions to bolster their resilience.
Copeland, Timothy↗
State-by-state energy-water-land-health impacts of the US net-zero emissions goal
As decisionmakers at various scales begin to design strategies to implement the US net-zero goal, a holistic understanding of its broader economic and sustainability implications at subnational scales is important to shape public support and facilitate implementation. Here, we use an integrated assessment model to explore four different pathways toward the US net-zero goal and investigate their energy-water-land-health implications at the state level. In this study, we show that achieving the net-zero goal implies significant capital turnover (170–200 billion USD/year capital investment and 16–29 billion USD/year stranded assets in the power sector), reduced water withdrawal (120–210 km 3 /year), avoided air pollution damages (220–300 billion USD/year), and expanded forests (300–500 thousand km 2 ). However, the economic and sustainability implications of achieving the net-zero goal at the state-level may not be correlated to a state's contribution to national emission reductions. Our study lays the foundations for a deeper understanding of the broader implications of the US net-zero goal to facilitate cost-effective and environmentally sustainable transitions toward that goal.
54 ENVIRONMENTAL SCIENCES↗
Strategies for Achieving the DOE Hydrogen Shot Goal: Thermal Conversion Approaches
In July 2021 the United States (U.S.) Department of Energy (DOE) launched the first of a series of Department-wide Energy Earthshot goals designed to accelerate breakthroughs of more abundant, affordable, and reliable clean energy solutions within the decade. The Hydrogen Shot goal seeks to reduce the cost of clean hydrogen to $\$$1 per 1 kilogram in 1 decade ("1 1 1"). Today, thermal conversion of fossil fuels represents the predominant, lowest cost method of hydrogen production. In 2020 approximately 75 percent of global, dedicated hydrogen production was produced via fossil fuels using thermal conversion approaches such as steam reforming and gasification. However, carbon management techniques such as CO 2 capture and sequestration (CCS) and pyrolysis are not widely represented in the current fossil-based hydrogen production fleet. Lowering the cost of clean hydrogen production from commercial and advanced thermal conversion-based technologies is critical for successfully achieving the Hydrogen Shot goal. This report presents the findings from an initial screening analysis of several scenarios that explore cost drivers related to clean hydrogen production. The screening encompasses commercially available and developing thermal conversion technology alternatives as well as factors exogenous to the plant such as feedstock/byproduct pricing, CO 2 pipeline and storage infrastructure costs, and scale to assess potential pathways towards meeting the Hydrogen Shot goal. Additionally, this report presents initial Research and Development (R&D) strategies to advance thermal conversion technology towards meeting the Hydrogen Shot goal.
08 HYDROGEN↗
Satellite remote sensing for environmental sustainable development goals: A review of applications for terrestrial and marine protected areas
With few years left to achieve the vital United Nations Sustainable Development Goals (SDGs), member nations must urgently leverage technological advancements in environmental monitoring to succeed. Remote sensing now provides decades of global observations at a variety of spatio-temporal scales and a litany of data products to guide comprehensive measures for climate action, and aquatic and terrestrial biota preservation. Protected areas, such as national parks and wildlife preserves, represent largely untapped resources for both applying robust conservation measures and testing ambitious new approaches to sustainable development that could jumpstart the much-needed adoption of strategies to efficiently pursue global sustainability. This review summarizes recent demonstrated utilities of remotely sensed data applied to protected areas for research related to SDG goals 13, 14, and 15: “Climate Action”, “Life below Water”, and “Life on Land”. We identify successful uses of such data for each SDG, identify areas for improvement, and provide recommendations from the literature on how to expand what others have done to achieve lofty goals with global impact. We demonstrate that remote sensing provides a valuable tool for achieving SDGs as it facilitates monitoring vegetation health, water quality and condition, and climate variables at large spatial and fine temporal scales, while also evaluating the effectiveness of management and conservation practices. Issues remain, however, in that there is currently no reference from which to relate goal progress to human livelihoods. Further, the current relationship between remotely sensed indices and ecological services that determine sustainable development omit steps that would establish this connection.
54 ENVIRONMENTAL SCIENCES↗
Achieving Economy-wide Net-Zero Emissions: Is it an impossible goal?
Meeting growing energy demands while eliminating emissions, maintaining affordability, and ensuring energy justice is one of the most significant grand challenges of our time. Governments and private industry around the world have established aggressive goals to achieve net-zero emissions by mid-century. In the U.S., this equates to a net-zero electricity sector by 2035 and across all energy use sectors—including electricity, industry, and transportation—by 2050. The key question then becomes: Can we get there from here? Meeting these aggressive goals demands immediate action, and they require us to think more holistically about our clean energy options. Currently, almost 85% of global energy demands are met by unabated fossil fuels. That means we have a lot of work to do, and we need to consider all of the non-emitting generation options available in each region—including fossil with carbon capture, renewables, and nuclear. And we need to reach our goal while establishing energy justice, which refers to the goal of achieving equity in social and economic participation in the energy system, while remediating past social, economic, and health burdens on communities that have been brought about by our energy system. This presentation will describe U.S. and global efforts focused on novel energy system solutions that strive to maximize use of all clean energy generation options to meet our energy demands, while ensuring sustainability, customer affordability, and a just energy system.
08 HYDROGEN↗
Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning
We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.
97 MATHEMATICS AND COMPUTING↗
Role of climate goals and clean-air policies on reducing future air pollution deaths in China: a modelling study
Over 3 million people still die every year from diseases caused by exposure to outdoor PM 2.5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO 2 emissions (e.g., to avoid 1.5°C of warming) may also dramatically improve air quality and public health. Yet there has been no comprehensive accounting of public health outcomes under different energy pathways and local clean air management decisions in China. In particular, further research is needed to understand the relationships among climate and clean air polices and future health burdens in China, where an aging population will further exacerbate the impacts of air pollution. Using a China-focused integrated assessment model (GCAM-China) and a dynamic emission projection model (DPEC), we project future Chinese air quality in scenarios spanning a range of global climate targets (i.e. 1.5°0C, 2°C, NDC, unambitious, baseline, and 4.5°C) as well as national clean air actions (i.e. 2015-pollution, current-pollution, and ambitious-pollution). We then evaluate the health impacts of PM2·5 air pollution of scenario matrix using the chemical transport model WRF-CMAQ and the latest epidemiological concentration–response (C-R) functions (i.e. GBD2019). We find that, without ambitious climate mitigation (e.g., under current NDC pledges), Chinese deaths related the PM2.5 air pollution do not substantially decrease—and often grow—by mid-century, regardless of clean air policies and air quality improvements. For example, in scenarios that track China’s current NDC pledge and deploy best-available pollution control technologies, PM 2.5 -related deaths in China decrease slightly by 2030 (to 1.2 million per year) but no further by mid-century (Ambitious-pollution-NDC-goals; 1.2 million deaths in 2050) despite substantial and continuous improvements in population-weighted air quality (27.2 to 16.0 µg/m 3 from 2030 to 2050). The contrary trends of improving air quality and increasing PM 2·5 -related deaths in many of our scenarios reveals the extent to which extra efforts are needed to compensate for the established fact of increasing age of China’s population in future. Substantial decreases in China’s PM 2.5 -related deaths and age-standardized death rates (e.g., decreasing by 0.3–0.5 million deaths and 10.2–14.2 per 100,000 population age-standardized death rates per year) thus require the sort of large-scale transition in energy sources entailed by scenarios that meet international climate goals to avoid 1.5°C and 2°C of warming (Ambitious-pollution-2°C- and 1.5°C-goals).
58 GEOSCIENCES↗
How Much Could Article 6 Enhance Nationally Determined Contribution Ambition Toward Paris Agreement Goals Through Economic Efficiency?
The Paris Agreement of 2015 uses Nationally Determined Contributions (NDCs) to achieve its goal to limit climate change to well below 2°C. Article 6 allows countries to cooperatively implement NDCs provided they do not double-count mitigation. We estimate that economic efficiency gains from cooperative implementation of existing NDC goals using Article 6 could reduce the cost of achieving NDC goals in 2030 to all parties by ~$\$300$ × 10 9 , which if reinvested in additional emissions mitigation could add 9 billion tons CO 2 /year mitigation, beyond the 8 billion tons CO 2 /year currently pledged in 2030. We estimate that more than half of the 2030 gains could come from nature-based measures, but long-term potential for nature-based measures is more limited. How much or even if this economic potential can be realized is uncertain and will depend on both the rules and their implementation.
54 ENVIRONMENTAL SCIENCES↗
Enhancing integrated analysis of national and global goal pursuit by endogenizing economic productivity
Analysis with integrated assessment models (IAMs) and multisector dynamics models (MSDs) of global and national challenges and opportunities, including pursuit of Sustainable Development Goals (SDGs), requires projections of economic growth. In turn, the pursuit of multiple interacting goals affects economic productivity and growth, generating complex feedback loops among actions and objectives. Yet, most analysis uses either exogenous projections of productivity and growth or specifications endogenously enriched with a very small set of drivers. Extending endogenous treatment of productivity to represent two-way interactions with a significant set of goal-related variables can considerably enhance analysis. Among such variables incorporated in this project are aspects of human development (e.g., education, health, poverty reduction), socio-political change (e.g., governance capacity and quality), and infrastructure (e.g. water and sanitation and modern energy access), all in conditional interaction with underlying technological advance and economic convergence among countries. Using extensive datasets across countries and time, this project broadly endogenizes total factor productivity (TFP) within a large-scale, multi-issue IAM, the International Futures (IFs) model system. We demonstrate the utility of the resultant open system via comparison of new TFP projections with those produced for Shared Socioeconomic Pathways (SSP) scenarios, via integrated analysis of economic growth potential, and via multi-scenario analysis of progress toward the SDGs. We find that the integrated system can reproduce existing SSP projections, help anticipate differential economic progress across countries, and facilitate extended, integrated analysis of trade-offs and synergies in pursuit of the SDGs.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Effects on the Sustainable Development Goals of Wood Pellet Production in the Southeastern United States
Wood-based pellets produced in the southeastern United States (SE US) and shipped overseas for the generation of heat and power support achievement of several of the United Nation’s Sustainable Development Goals and their targets. If improperly implemented, pellet supply chains, like most energy technologies, can have negative impacts on water and air quality, biodiversity, and other ecosystem services. Cooperation between regional and local industry partners and local communities as well as readily accessible information on environmental and societal effects of the industry are important for addressing sustainability goals. Strengths of this supply chain include replacement of fossil coal with bioenergy; support for renewable energy goals; conservation of forests through sustainable, green economy jobs; and more efficient use of waste materials.
09 BIOMASS FUELS↗
Scientists’ call to action: Microbes, planetary health, and the Sustainable Development Goals
Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.
59 BASIC BIOLOGICAL SCIENCES↗
Linearization errors in discrete goal-oriented error estimation
This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete, adjoint-based approach for error estimation is considered. The traditional method to derive an error estimate in this context requires linearizing both the nonlinear variational form and the nonlinear functional of interest which introduces linearization errors into the error estimate. In this paper, we investigate these linearization errors. In particular, we develop a novel discrete goal-oriented error estimate that accounts for traditionally neglected nonlinear terms at the expense of greater computational cost. We demonstrate how this error estimate can be used to drive mesh adaptivity. Here, we show that accounting for linearization errors in the error estimate can improve its effectivity for several nonlinear model problems and quantities of interest. We also demonstrate that an adaptive strategy based on the newly proposed estimate can lead to more accurate approximations of the nonlinear functional with fewer degrees of freedom when compared to uniform refinement and traditional adjoint-based approaches.
42 ENGINEERING↗
Goal-oriented a-posteriori estimation of model error as an aid to parameter estimation
In this work, a Bayesian model calibration framework is presented that utilizes goal-oriented a-posterior error estimates in quantities of interest (QoIs) for classes of high-fidelity models characterized by PDEs. It is shown that for a large class of computational models, it is possible to develop a computationally inexpensive procedure for calibrating parameters of high-fidelity models of physical events when the parameters of low-fidelity (surrogate) models are known with acceptable accuracy. The main ingredients in the proposed model calibration scheme are goal-oriented a-posteriori estimates of error in QoIs computed using a so-called lower fidelity model compared to those of an uncalibrated higher fidelity model. The estimates of error in QoIs are used to define likelihood functions in Bayesian inversion analysis. A standard Bayesian approach is employed to compute the posterior distribution of model parameters of high-fidelity models. As applications, parameters in a quasi-linear second-order elliptic boundary-value problem (BVP) are calibrated using a second-order linear elliptic BVP. In a second application, parameters of a tumor growth model involving nonlinear time-dependent PDEs are calibrated using a lower fidelity linear tumor growth model with known parameter values.
A-posterior estimates↗
Sustainability of the U.S. Manufacturing Sector: Use of the United Nations Sustainable Development Goals
The United Nations' 17 Sustainable Development Goals (SDGs) aim to improve health and education, reduce inequality, and encourage economic growth, while also preserving or improving the conditions of our oceans and forests. Pursuing these SDGs would mean $12 trillion in economic opportunities for companies, while also improving the lives of all people and bettering the planet. Some manufacturing companies are already focusing on sustainability, but not all. In 2019, almost 30% of National Association of Manufacturers members did not have a sustainable policy, goals, or program in place. Business drivers for sustainability and the SDGs are similar, with focuses on economic growth and consumer demands. Despite the shortcomings of the SDGs, they represent an opportunity for manufacturing companies to further improve energy, material efficiency, and productivity. This report evaluates the SDGs and the manufacturing sector. The manufacturing sector was analyzed using the technology assessments (TAs) introduced in the 2015 Quadrennial Technology Review (QTR) review, which focused on concepts, challenges, and solutions to meet the United States' energy needs. Annual or sustainability reporting of companies performing work in one of those TAs were analyzed for mentions of the SDGs. The call-out boxes throughout this report provide examples of companies making progress toward the SDGs. The possible overlap between the SDGs and the Advanced Manufacturing Office (AMO) was also evaluated. The TAs in the 2015 QTR Review were furthered with detailed targets in the draft Multi-Year Program Plan (MYPP) for Fiscal Years 2017-2021. Direct and likely relationships between the SDGs and the TAs were established. Positives, challenges, SDG-related literature, and future steps are also discussed in this report.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Effects of Production of Woody Pellets in the Southeastern United States on the Sustainable Development Goals
Wood-based pellets are produced in the southeastern United States (SE US) and shipped to Europe for the generation of heat and power. Effects of pellet production on selected Sustainability Development Goals (SDGs) are evaluated using industry information, available energy consumption data, and published research findings. Challenges associated with identifying relevant SDG goals and targets for this particular bioenergy supply chain and potential deleterious impacts are also discussed. We find that production of woody pellets in the SE US and shipments to displace coal for energy in Europe generate positive effects on affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), and life on land (SDG 15). Primary strengths of the pellet supply chain in the SE US are the provisioning of employment in depressed rural areas and the displacement of fossil fuels. Weaknesses are associated with potential impacts on air, water, and biodiversity that arise if the resource base and harvest activities are improperly managed. The SE US pellet supply chain provides an opportunity for transition to low-carbon industries and innovations while incentivizing better resource management.
09 BIOMASS FUELS↗