Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs

Toward an Understanding of Synergies and Trade-Offs Between Water, Energy, and Food SDG Targets

Achieving the targets set out in the UN Sustainable Development Goals (SDG) will require committed efforts by nations and organizations over the coming decade. To determine which actions work most harmoniously within funding, infrastructure development, and implementation of three closely aligned goals, we conducted an assessment to identify where the greatest synergies may occur and where conflicting resource needs create trade-offs that may threaten SDG success. The SDGs each have several targets that need to be realized for the goal to be reached. In the present study, we developed a methodology where each target of the SDG 2 (food), 6 (water), and 7 (energy) was analyzed for its input requirements, infrastructure needs, and the risks and benefits for the provision of ecosystem services. Then the targets were compared pairwise and a total score of interaction was calculated to determine different levels of synergies and trade-offs for every pair. In some cases targets were mutually supportive, in other cases there were no interactions among the targets, and for some areas the targets were in conflict with each other. For example, targets 2.5 (maintain genetic diversity), 6.5 (implement integrated water resources management) and 7.a (enhance international cooperation to facilitate access to clean energy) have no conflicts with other targets and have different levels of synergies with most of the other targets. On the contrary, various targets of SDG 2, and especially the target 2.b (correct and prevent trade restrictions), are in slight conflict with other targets by potentially overusing resources needed by other targets or threatening ecosystem services. Our approach confirms the general belief that SDG 6 (water) has the highest number of potential synergies (a total of 124). Thus, achieving the water targets will make it continuously easier to achieve other targets. While the results may need to be adapted for a specific locality or country, overall they provide an improved understanding of the interactions between the targets. The value of the study lies in the quantitative methodology as it can be used as a replicable analysis for any level of work on SDG implementation

3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

The Clean Air Interstate Rule (CAIR) is expected to reduce transport of air pollutants (e.g. fine sulfate particles) in nonattainment areas in the Eastern United States. CAIR highlights the need for an integrated air quality observational and modeling system to understand sulfate as it moves in multiple dimensions, both spatially and temporally. Here, we demonstrate how results from an air quality model can be combined with a 3d monitoring network to provide decision makers with a tool to help quantify the impact of CAIR reductions in SO2 emissions on regional transport contributions to sulfate concentrations at surface monitors in the Baltimore, MD area, and help improve decision making for strategic implementation plans (SIPs). We sample results from the Community Multiscale Air Quality (CMAQ) model using ensemble back trajectories computed with the NASA Langley Research Center trajectory model to provide Lagrangian time series and vertical profile information, that can be compared with NASA satellite (MODIS), EPA surface, and lidar measurements. Results are used to assess the regional transport contribution to surface SO4 measurements in the Baltimore MSA, and to characterize the dominant source regions for low, medium, and high SO4 episodes

Conceptual Model of Comprehensive Research Metrics for Improved Human Health and Environment

Performance measurement predominantly consisted of near-term outputs measured through bibliometrics, but the recent focus is on accountability for investment based on long-term outcomes. Our objective is to build a logic model and associated metrics through which to measure the contribution of environmental health research programs to improvements in human health, the environment, and the economy. We developed a logic model that defines the components and linkages between extramural environmental health research grant programs and the outputs and outcomes related to health and social welfare, environmental quality and sustainability, economics, and quality of life, focusing on the environmental health research portfolio of the National Institute of Environmental Health Sciences (NIEHS) Division of Extramural Research and Training and delineates pathways for contributions by five types of institutional partners in the research process. The model is being applied to specific NIEHS research applications and the broader research community. We briefly discuss two examples and discuss the strengths and limits of outcome- based evaluation of research programs

Gulf of Mexico Regional Collaborative Final Report

This report presents the results of the Gulf of Mexico Regional Collaborative (GoMRC), a year-long project funded by NASA. The GoMRC project was organized around end user outreach activities, a science applications team, and a team for information technology (IT) development. Key outcomes are summarized below for each of these areas. End User Outreach Successfully engaged federal and state end users in project planning and feedback With end user input, defined needs and system functional requirements Conducted demonstration to End User Advisory Committee on July 9, 2007 and presented at Gulf of Mexico Alliance (GOMA) meeting of Habitat Identification committee Conducted significant engagement of other end user groups, such as the National Estuary Programs (NEP), in the Fall of 2007 Established partnership with SERVIR and Harmful Algal Blooms Observing System (HABSOS) programs and initiated plan to extend HABs monitoring and prediction capabilities to the southern Gulf. Established a science and technology working group with Mexican institutions centered in the State of Veracruz. Key team members include the Federal Commission for the Protection Against Sanitary Risks (COFEPRIS), the Ecological Institute (INECOL) a unit of the National Council for science and technology (CONACYT), the Veracruz Aquarium (NOAA’s first international Coastal Ecology Learning Center) and the State of Veracruz. The Mexican Navy (critical to coastal studies in the Southern Gulf) and other national and regional entities have also been engaged. Training on use of SERVIR portal planned for Fall 2007 in Veracruz, Mexico Science Applications Worked with regional scientists to produce conceptual models of submerged aquatic vegetation (SAV) ecosystems Built a logical framework and tool for ontological modeling of SAV and HABs Created online guidance for SAV restoration planning Created model runs which link potential future land use trends, runoff and SAV viability Analyzed SAV cover change at five other bays in the Gulf of Mexico to demonstrate extensibility of the analytical tools Initiated development of a conceptual model for understanding the causes and effects of HABs in the Gulf of Mexico IT Tool Development Established a website with the GoMRC web-based tools at www.gomrc.org Completed development of an ArcGIS-based decision support tool for SAV restoration prioritization decisions, and demonstrated its use in Mobile Bay Developed a web-based application, called Conceptual Model Explorer (CME), that enables non-GIS users to employ the prioritization model for SAV restoration Created CME tool enabling scientists to view existing, and create new, ecosystem conceptual models which can be used to document cause-effect relationships within coastal ecosystems, and offer guidance on management solutions. Adapted the science-driven advanced web search engine, Noesis, to focus on an initial set of coastal and marine resource issues, including SAV and HABs Incorporated map visualization tools with initial data layers related to coastal wetlands and SAV

System Dynamics of Polysilicon for Solar Photovoltaics: A Framework for Investigating the Energy Security of Renewable Energy Supply Chains

Renewable energy, produced with widely available low-cost energy resources, is often included as a component of national strategies to address energy security and sustainability. Market and political forces cannot disrupt the sun or wind, unlike oil and gas supplies. However, the cost of renewable energy is highly dependent on technologies manufactured through global supply chains in leading manufacturing countries. The countries that contribute to the global supply chains may take actions that, directly or indirectly, influence global access to materials and components. For example, high-purity polysilicon, a key material in solar photovoltaics, has experienced significant price fluctuations, affecting the manufacturing capacity and cost of both polysilicon and solar panels. This study developed and validated an initial system dynamics framework to gain insights into global trade in polysilicon. The model represents an initial framework for exploration. Three regions were modeled—China, the United States, and the rest of the world—for a range of trade scenarios to understand the impacts of import duties and non-price drivers on the relative volumes of imports and domestic supply. The model was validated with the historical case of China imposing an import duty on polysilicon from the United States, the European Union, and South Korea, which altered the regional flows of polysilicon—in terms of imports, exports, and domestic production—to varying degrees. As expected, the model tracked how regional demand shares and influx volumes decrease as a duty on a region increases. Using 2016 as a reference point, in the scenarios examined for U.S. exports to China, each 10% increase in the import duty results in a 40% decrease in import volume. The model also indicates that, under the scenarios investigated, once a duty has been imposed on a region, the demand share from that region declines and does not achieve pre-duty levels, even as global demand increases. Adding additional countries and other components in the photovoltaic supply chain (panels, cells, wafers) to this model could enable policymakers to better understand the relative impact of trade measures across the entire photovoltaic module manufacturing supply chain and the conditions that encourage industry evolution and competitiveness

Integrating Renewable Energy into Mining Operations: Opportunities, Challenges, and Enabling Approaches

Mining is one of the most energy-intensive industries worldwide. It also provides a critical source of raw materials for the manufacturing, transportation, construction, and energy sectors. Demand for raw materials is projected to increase as the world population grows and many low-income economies become middle-income countries. This growth in mineral demand, coupled with falling mineral ore grade, will likely increase the mining industry\u27s energy demand, used for activities across exploration, extraction, beneficiation and processing, and refining. At the time of this writing, mine operations are -- due to their remoteness -- dependent on fossil fuels such as diesel, heavy oils, and coal. In principle, mining could use energy recovery, renewable energy, and carbon capture to supplement, replace, or mitigate the impacts of fossil fuel use. However, a combination of renewable-energy technologies would be required. We explore challenges, opportunities, and enabling approaches to integrate renewable energy technologies into mining operations by examining the literature, including academic work, technical reports, and data produced by international agencies. We find that despite numerous opportunities, technical issues still need to be considered, but solutions can tailor renewables to the mining industry. Further research should focus on identifying specific opportunities, technologies, and implementation strategies across the value chain of a variety of minerals with similar operational procedures