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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS2012

The Race To Understand A Changing Planet

The Earth's climate is changing rapidly. In some respects, the rate of change is outpacing the predictions of only a few years ago. The challenge to Earth Science is to put forward credible projections of possible future climates so that the public and policy makers can make science-based decisions about energy development strategies. Models, observations and experiments all play strong roles in improving knowledge and increasing confidence in our predictions. The models have progressed from simple, coarse-resolution descriptions of atmospheric dynamics and physics only twenty years ago, to full-up Earth System models (ESMs) that include complete descriptions of the oceans and cryosphere. It has been convincingly argued that such complexity - the construction of realistic "toy" Earth's - is necessary to address the complex processes involved in climate change, including not only the physical atmosphere, oceans and cryosphere, but also the carbon cycle - both its natural and anthropogenic components - and the biosphere. Observations, particularly satellite observations, have more or less kept pace with the demands of the modelers, being able to observe progressively more and different facets of the Earth system, but the global satellite fleet is in need of an overhaul very soon. Lastly, field experiments and process studies confront the models with facts and allow us to develop more sophisticated and accurate satellite data algorithms. The challenges facing our relatively small Earth and planetary science communities are considerable and the stakes are significant. The stakeholders, now numbering 7 billion but soon to be 10 billion, will be relying on our results and capabilitie's to guide them into the future.

Sellers, Piers J.↗
NASA NTRS2012

Climate Change Impacts on the Built Environment in the United States and Implications for Sustainability

As an integral part of the National Climate Assessment (NCA), technical assessment reports for 13 regions in the U.S. that describe the scientific rationale to support climate change impacts within the purview of these regions, and provide adaptation or mitigation measures in response to these impacts. These technical assessments focus on climate change impacts on sectors that are important environmental, biophysical, and social and economic aspects of sustainability within the U.S.: Climate change science, Ecosystems and biodiversity, Water resources, Human health, Energy supply and use, Water/energy/land use, Transportation, Urban/infrastructure/vulnerability, Agriculture, Impacts of climate change on tribal/indigenous and native lands and resources, Forestry, Land use/land cover change, Rural communities development, and Impacts on biogeochemical cycles, with implications for ecosystems and biodiversity. There is a critical and timely need for the development of mitigation and adaptation strategies in response to climate change by the policy and decision making communities, to insure resiliency and sustainability of the built environment in the future.

Quattrochi, Dale A.↗
NASA NTRS2015

Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information

Wheat is themost important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop typemasks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel (area within the CMG pixel occupied by wheat), and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: the Unites States (US), Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest), while conserving an accuracy of 10% in the production forecast.

Production↗
NASA NTRS2016

Quantifying PM2.5-Meteorology Sensitivities in a Global Climate Model

Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 micro-g/cu m3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by -0.06 micro-g/cu m (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 micro-g/cu m for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006-2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10e50% over the eastern United States for several variables), although the modeled PM2.5 is less sensitive to precipitation than in the observations due to weaker convective scavenging. We conclude that the hypothesized "climate penalty" of future increases in PM2.5 is relatively minor on a global scale compared to the influence of emissions on PM2.5 concentrations.

PM2.5↗
NASA NTRS2018

Enhancing Remote Sensing Based Yield Forecasting: Application to Winter Wheat in United States

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. In this study we present a new model based on the extrapolation of the pure wheat signal (100 percent of wheat within the pixel) from MODIS (Moderate-resolution Imaging Spectroradiometer) data at 1-kilometer resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national and state level yield of winter wheat in the United States from 2001 to 2016.

Agriculture↗
NASA NTRS2018

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100 percent of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (tonnes per hectare) (15-18 percent). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7 percent) while for Ukraine it is 0.27 t/ha (8.4 percent).

DVI↗
NASA NTRS2018

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100% of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (15–18%). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7%) while for Ukraine it is 0.27 t/ha (8.4%).

remote sensing↗
NASA NTRS2021

Peru Health & Air Quality: Land Use Change in the Rapidly Developing Peruvian Amazon and Implications on Zoonotic Disease Incidence

In the Madre de Dios region of the Peruvian Amazon, forests are being cleared for mining, timber harvesting, road construction, and hydroelectric dam development. These rapid land use changes are increasing human presence in previously sparsely populated areas, disrupting ecosystems and increasing the proximity of human settlement to zoonotic disease vectors. Dengue fever and leishmaniasis are two neglected tropical diseases which are prevalent in Madre de Dios and have been associated with urbanization and road construction. In partnership with the Peruvian Ministries of Health (MINSA) and the Environment (MINAM) and other in-country collaborators, our team examined Land Use Land Cover (LULC) correlations with reported dengue and leishmaniasis incidence in the Madre de Dios region to help partners understand the spatial relationship between land use change and zoonotic disease incidence. We created a LULC classification script using Google Earth Engine with Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager imagery to classify land cover in 2010, 2015, and 2020 and evaluate changes over this time period. We then used the quantified results of the LULC assessment in conjunction with reported disease cases to evaluate correlations between disease incidence and key land cover changes across Madre de Dios’s 11 districts. In the second term, the team will use these products to develop more detailed disease incidence risk maps and models. High risk areas will then be classified, using PeruSat-1 that allow for even higher resolution mapping at less than 3 meters. These products will allow the partners to understand hotspots of land cover change in Peru and the relationship with outbreaks to inform public health decision making and environmental policy.

Elizabeth Stapleton↗
NASA NTRS2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Ghada Y.H. El Serafy↗
NASA NTRSDate not supplied

Diversity and Inclusion in Spacecraft Science Teams: What Do We Know and What Can We Do About It?

Introduction: Not only does the planetary science community lack diversity [1-3], the subset of the community that participates on spacecraft science team is even less diverse than the community as a whole [1, 4]. Results of 2020 Workforce Survey: Previous studies of the diversity of members of spacecraft science teams made incorrect assumptions about the nature of the data before collecting the data. Those analyses assumed a binary gender and ignored the existence of planetary scientists who are neither men nor women [4-6]. We present here results where demographic data was collected without assumptions; each individual surveyed supplied their own answers to demographic questions. The April 2020 survey of Planetary Scientists, which was conducted by the Statistical Research Center of the American Institute of Physics (AIP) and funded by the American Astronomical Society (AAS)’s Division of Planetary Science (DPS) asked participants their gender with 4 possible responses: Woman, Man, Another identify (please specify if you wish), and Prefer not to answer. 32% of respondents chose Woman, 67% chose Man and 1% chose Another gender identity [1]. The survey also asked demographic questions on race, ethnicity, LGBTQ+ identity, and disability. For a full list of questions, see https://dps.aas.org/sites/dps.aas.org/files/reports/2020/survey2020_questionnaire.pdf. In addition to demographic questions, the 2020 Workforce survey asked how many times respondents had been involved in Mission proposals as a Principal Investigator (PI) and, separately, as a Co-Investigator (CoI) [1]. Answers to questions about mission involvement were correlated with answers to demographic questions and the results show that members of historically underrepresented groups (non-white scientists, women, members of the LGBTQ+ community, and disabled scientists) were less likely to be involved in spacecraft mission proposals than were members of historically overrepresented groups [1]. The figures below show the correlated responses for four different axes of underrepresentation [1]. Note that while the figure on gender shows only Women and Men (due to the small percentage of folks answering “Another gender”), non-binary respondents are included in the LGBTQ+ community figure. Conclusion: Being part of a spacecraft science team is a goal for many planetary scientists. With it comes brand new data, more stable funding, and a sense of awe and exploration. It can lead to a cascade of opportunities from conference and public presentations, to membership in subsequent mission teams, and prestige in the community [4]. As a result, participation in spacecraft teams can be used a measure of success within the field. From the survey results, we see that members of historically excluded groups, even after they have overcome barriers to participating in the field, are still experiencing barriers to success within the field itself. Why?: The diminishing percentage of members of underrepresented groups as a career progresses has been referred to as a “leaky pipeline”. However, this fails to adequately capture the experiences of the members of these underrepresented groups as it implies a passive process. In order to capture the active processes (bias, discrimination, harassment, and other exclusionary behaviors) that contribute to low retention in the workforce, the term “Hostile Obstacle Course” is more useful [7,8]. It is these processes that need to be addressed in order to retain valued members of our community. Moving Forward: In order to broaden participation in planetary science, particularly mission science teams, we need to address conditions that create hostile workplace climates. What can mission teams and other groups do to address these conditions? First, each group/team needs to evaluate their own members to determine what specific barriers exist in their own interactions. One tool to accomplish this would be an anonymous survey designed to understand how team members feel about working within the group. Working with professionals who know how to create and analyze such surveys (often called “climate surveys” when applied to University students, for example) would ensure that the survey meets its goals and does not make assumptions that counter the meaningfulness of the results. Such professionals in EDIA (Equity, Diversity, Inclusion, and Accessibility) and workplace culture can make suggestions for policy changes that would eliminate hostile workplace conditions. Policy changes that are often suggested include instituting professional EDIA training for the team and/or for team leadership, instituting and following a code of conduct [9], including more interactive group activities in group meetings, etc. Training and information on EDIA is available for all members of the planetary science community. The first place to look would be in your University or Institution’s EDIA or human resources offices. Bystander Intervention is often offered as part of other meetings [10]. A newer offering is a Workshop on EDIA for Leaders in Planetary Science led by Julie Rathbun (first author of this abstract) and JA Grier (https://edialps.psi.edu/). This 3-day workshop gives participants the tools they need to enact positive change in their personal and professional spheres. The first workshop was help in November 2022 and another workshop will take place in the late spring 2023 with exact dates to be announced soon.

J. A. Rathbun↗
NASA NTRS2024

Quantifying Food Security and Mitigation Risks Consequential to Climate Change Impacts on Crop Yields

Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the Integrated Model to Assess the Global Environment integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as agriculture, forestry and other land use emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

crop yields↗
DOE OSTI2016

Surrogate Post-Detonation Urban Debris (SPUD): Standard Reference Materials 4600 and 4601

If a terrorist nuclear explosion were to occur in the United States, high-quality (accurate and precise) legally defensible nuclear forensics measurements will be required to assure the certainty and confidence needed, for conclusions drawn from these data will be coupled with law enforcement and intelligence information for the purposes of attribution and retribution. Standard Reference Materials (SRMs)/Certified Reference Materials (CRMs) establish the traceability, accuracy, and precision of nuclear forensic measurements and provide the ability to benchmark measurement methods essential to meeting the requirements of legal scrutiny. Currently there is a critical shortage of key SRMs/CRMs required for accurate and precise measurements that are fundamental to nuclear measurements supporting pre- and post-detonation nuclear forensics. Supplies either do not exist, are not good enough, are in short supply, and/or are very expensive. The radionuclide measurement techniques and data quality objectives for pre- and post-detonation nuclear forensics are quite different than the applications for which the current suite of available SRMs/CRMs was developed. Specifically, 1) modern mass spectrometry methods have largely replaced traditional activity-based measurement methods for quantifying small quantities of long-lived radionuclides and most trace radionuclide SRMs/CRMs are certified for activity and are thus not adequate for current applications, 2) modern instrumental methods are capable of higher precision than historic measurement techniques, and in some cases exceed the precision of the available SRMs/CRMs, and 3) the quality assurance requirements for pre- and post-detonation nuclear forensics are such that the existing cadre of SRMs/CRMs does not adequately support the needs for method validation. There are numerous governmental stakeholders both within the US (DOE, DoD) and internationally (IAEA, JRC-ITU) whose missions are either directly involved with nuclear forensics measurements or rely on the forensic data obtained to make the exacting policy decisions (DOJ (FBI), DHS, CIA, DIA, DoD) associated with disrupting the production of illicit nuclear materials, interdicted nuclear materials or a nuclear/radiological detonation event. Starting in 2008 the DHS NTNFC, in collaboration with NBL and NIST, took on the production of suitable SRMs/CRMs for the pre-detonation nuclear forensics community. Two CRMs have been released since the start of this effort and two more are slated for completion in 2016. More recently, NIST, as a part of its mission as the US National Metrology Institute (NMI) to deliver standards (providing traceability) and foster homeland security, has launched the first certification campaign of a measurement traceable post nuclear detonation SRM. NIST, in cooperation with partner labs (AFIT (DoD), FBI (DOJ), and NPL) and with support from the FBI, has developed two Surrogate Post-Detonation Urban Debris (SPUD) Standard Reference Materials (SRMs) - SRM 4600 and 4601. These SRMs have been developed to simulate the expected debris mixture from the detonation of an Improvised Nuclear Device (IND) in an urban environment, which is capable of producing fresh fission as well as activation products. The elemental composition of the vitrified debris materials is a composite of minerals and metals characteristic of the concrete and steel, the building materials that would be exposed to a nuclear detonation and whose resulting activation products would be found in rubble samples collected for forensics evidence and attribution. Additionally, because post-detonation samples would also contain short-lived fission products, the debris materials have been doped with Uranium (U). To create the nuclear fission products, samples of the SPUD materials can be placed in a well-characterized nuclear reactor and exposed to a set neutron flux and energy, causing the encased U atoms to split and yield short-lived fission products. Because a known amount of U is added to the SPUD materials it is feasible to determine the concentration of the resulting fission products. The subsequent irradiated SPUD glass would be chemically similar to samples that would be generated in an actual detonation, and thus can serve as a standardized reference material for nuclear forensic post detonation measurements. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Exploring the effects of policy on stakeholder adoption and deployment of agrivoltaics: A case study of Massachusetts

Further deployment of agrivoltaics is likely to require a better understanding of how policies and agreements can shape the outcomes of solar siting on farmland. This study evaluates the Massachusetts agrivoltaics policy in terms of its implications on deployment and stakeholder experiences in adoption. We present findings from interviews with 26 state policymakers, Extension agents, representatives of non-governmental organizations, farm owners and operators, and solar developers. Our findings demonstrate how the policy has mixed effects on deployment processes and outcomes—in some instances, the policy enables deployment by formalizing cross-sector collaboration, increasing farm owner and operator participation in development, and facilitating novel business models. In other instances, the policy constrains deployment by prescribing operational requirements, creating liability risk, and developing dependency on empirical data to inform eligibility decisions. Interviewees explained how these mixed policy effects create both benefits and burdens for adopters, particularly farm owners and operators. These insights indicate the value of cross-sector collaboration during all phases of agrivoltaic policy implementation and project development; the importance of coordination across policy, research, and commercial activities; and the significant role of regulators and policy design in deployment. The evidence presented in this paper can inform decision making for emerging agrivoltaic policies and markets, both in the United States and internationally.

14 SOLAR ENERGY↗
DOE OSTI2015

Overcoming the barriers to implementation of decommissioning and environmental remediation projects, the CIDER project - 15160

Much remains to be done in terms of addressing the legacies from the early development of nuclear energy, including the dismantling of redundant research and fuel cycle facilities, research reactors, and power plants, and the remediation of sites affected by past uranium mining and processing operations. Long-term solutions still need to be found for management of the resulting waste, including development of disposal facilities that meet public acceptance and safety requirements. Some countries are moving forward with dealing with these legacies, and accordingly have built up appropriate technical resources and expertise, but many national programmes still face very significant challenges. Many are the factors that constrain progress in addressing past legacies. It is recognized the importance of early implementation of decommissioning and environmental remediation (D and ER) programmes in order to safeguard people and the environment from the undesirable effects of ionizing radiation and other hazards associated with these sites. There is also an urgent need to better understand the global status of these activities and to establish mechanisms to analyze and report the barriers impeding the implementation of D and ER programmes, with the aim of outlining actions that may improve the current situation. The IAEA has thus launched the CIDER Project (Constraints to Implementing Decommissioning and Environmental Remediation) with the broad aim of contributing to improve current levels of performance on D and ER programmes through promoting greater cooperation amongst its Member States and relevant international organizations. This paper provides early results from the first phase of the project. During this phase, a survey on the global situation of D and ER was undertaken in order to better understand why these programmes proceed faster in some countries than in others; to identify major constraining factors that affect the implementation of D and ER programmes and how these impediments might be overcome. The paper aims to address policy-level issues, regulatory aspects, technological aspects, and stakeholder involvement in the decision-making process. In the next phase of the project it is intended that specific actions and/or innovative approaches will be proposed at international, regional, or national levels with the goal of facilitating progress in programme implementation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Future of Energy Efficiency in Buildings: Drivers and Market Expectations [Slides]

This slide-deck report identifies drivers of energy efficiency in buildings over the next 10 years, for all fuels. The report also provides insights on what the future of efficiency may look like in that time period and considers other distributed energy resources, as well as decarbonization and demand flexibility, to the extent they are intertwined with efficiency activities. Understanding market drivers and possible future market attributes for energy efficiency can help policy makers, regulators and industry make informed decisions—for example, how best to design policies and investments to support desired outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Policies for Enabling Corporate Sourcing of Renewable Energy Internationally: A 21st Century Power Partnership Report

This paper explores the policy and regulatory enabling environment for corporate sourcing of renewables. The paper has been developed in support of the Corporate Sourcing of Renewables Campaign, which was launched at the Clean Energy Ministerial (CEM) meeting in June 2016. Through the campaign, a subset of CEM member governments is collaborating with corporate and nongovernmental organization partners to facilitate increased corporate procurement of renewables and pursue supportive policies for corporate procurement. This paper finds that policy certainty is essential to creating vibrant markets for renewable energy. While policymakers may need to adjust policy mechanisms over time as markets go through different stages of maturity, they must also consider the economic decisions that end-users make in evaluating projects. Policy interaction is also important to consider because buyers seek assurances that their investments in renewables have impact and wish to make clear claims about their renewable energy purchases.

21st Century Power Partnership↗