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DOE OSTI2024

LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]

We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming. Scientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246

Ghosh, Tapajyoti↗

DOE OSTI2017

Decomposing passenger transport futures: Comparing results of global integrated assessment models

The transport sector is growing fast in terms of energy use and accompanying greenhouse gas emissions. Integrated assessment models (IAMs) are used widely to analyze energy system transitions over a decadal time frame to help inform and evaluating international climate policy. As part of this, IAMs also explore pathways of decarbonizing the transport sector. This study quantifies the contribution of changes in activity growth, modal structure, energy intensity and fuel mix to the projected passenger transport carbon emission pathways. The Laspeyres index decomposition method is used to compare results across models and scenarios, and against historical transport trends. Broadly-speaking the models show similar trends, projecting continuous transport activity growth, reduced energy intensity and in some cases modal shift to carbon-intensive modes - similar to those observed historically in a business-as-usual scenario. In policy-induced mitigation scenarios further enhancements of energy efficiency and fuel switching is seen, showing a clear break with historical trends. Reduced activity growth and modal shift (towards less carbon-intensive modes) only have a limited contribution to emission reduction. Measures that could induce such changes could possibly complement the aggressive, technology switch required in the current scenarios to reach internationally agreed climate targets.

Edelenbosch, Oreane Y.↗

DOE OSTI2014

Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning. In this study, we presented a detailed building energy model with a U.S. state-level representation, nested in the GCAM integrated assessment framework. We projected state-level building energy demand and its spatial pattern over the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data. The result indicates that climate change has a large impact on heating and cooling building energy and fuel use at the state level, exhibiting large spatial heterogeneity across states (ranges from -10% to +10%). The sensitivity analysis reveals that the building energy demand is subject to multiple key factors, such as the magnitude of climate change, the choice of climate models, and the growth of population and GDP, and that their relative contributions vary greatly across the space. The scale impact in building energy use modeling highlights the importance of constructing a building energy model with the spatially-explicit representation of socioeconomics, energy system development, and climate change. These findings will help the climate-based policy decision and energy system, especially utility planning related to building sector at the U.S. state and regional level facing the potential climate change.

Building Energy Demand, Climate Change Impact, Sta↗

DOE OSTI2013

An integrated assessment of global and regional water demands for electricity generation to 2095

Electric power plants currently account for approximately one-half of the global industrial water withdrawal. While continued expansion of the electric sector seems likely into the future, the consequent water demands are quite uncertain, and will depend on highly variable water intensities by electricity technologies, at present and in the future. Using GCAM, an integrated assessment model of energy, agriculture, and climate change, we first establish lower-bound, median, and upper-bound estimates for present-day electric sector water withdrawals and consumption by individual electric generation technologies in each of 14 geopolitical regions, and compare them with available estimates of regional industrial or electric sector water use. We then explore the evolution of global and regional electric sector water use over the next century, focusing on uncertainties related to withdrawal and consumption intensities for a variety of electric generation technologies, rates of change of power plant cooling system types, and rates of adoption of a suite of water-saving technologies. Results reveal that the water withdrawal intensity of electricity generation is likely to decrease in the near term with capital stock turnover, as wet towers replace once-through flow cooling systems and advanced electricity generation technologies replace conventional ones. An increase in consumptive use accompanies the decrease in water withdrawal rates; however, a suite of water conservation technologies currently under development could compensate for this increase in consumption. Finally, at a regional scale, water use characteristics vary significantly based on characteristics of the existing capital stock and the selection of electricity generation technologies into the future.

electric power↗

NASA NTRS2020

Integrated assessment of climate change impacts on crop productivity and income of commercial maize farms in northeast South Africa

Agriculture in South Africa sustains about 70% of the region’s population for food, income and employment, playing an important role for food security and the local economy. The focus of the study was the commercial maize farms of the Free State Province given their importance in the National economy. The Regional Integrated Assessment (phase I) was implemented to assess climate change and adaptation that links climate, crops, economic data and tools developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP). In this context, the“system”is defined as a whole of agronomic and socio-economic factors. Within that framework three core questions were being evaluated: (i) Impacts of climate change under current system; (ii) Impacts of climate change under future system; (iii) The role of adaptation under climate change and the future system. Maize production will decrease between 10% to 16% as a result of projected climate impacts. Also, current agricultural production systems are negatively affected by climate change with an increase in poverty rates between 2% to 3%. The projected adoption of the adapted technology would result in positive increased net returns and a decrease in poverty rate of between 12%and 22%. The results of this study show that implementing adaptation measures and other strategies as indicated by the local stakeholders will have positive impacts on the agricultural production systems and can contribute to support and inform climate change policy decision making such as the development of National Adaptation Plans.

Integrated assessment↗

DOE OSTI2024

Carbon neutrality in Malaysia and Kuala Lumpur: Insights from stakeholder-driven integrated assessment modeling

Several cities in Malaysia have established plans to reduce their CO2 emissions, in addition to Malaysia submitting a Nationally Determined Contribution to reduce its carbon intensity (against GDP) by 45% in 2030 compared to 2005. Meeting these emissions reduction goals will require a joint effort between governments, industries, and corporations at different scales and across sectors. In collaboration with national and sub-national stakeholders, we developed and used a global integrated assessment model to explore emissions mitigation pathways in Malaysia and Kuala Lumpur. Guided by current climate action plans, we created a suite of scenarios to reflect uncertainties in policy ambition, level of adoption, and implementation for reaching carbon neutrality. Through iterative engagement with all parties, we refined the scenarios and focus of the analysis to best meet the stakeholders’ needs. We found that Malaysia can reduce its carbon intensity and reach carbon neutrality by 2050, and that action in Kuala Lumpur can play a significant role. Decarbonization of the power sector paired with extensive electrification, energy efficiency improvements in buildings, transportation, and industry, and the use of advanced technologies such as hydrogen and carbon capture and storage will be major drivers to mitigate emissions, with carbon dioxide removal strategies being key to eliminate residual emissions. This study highlights the participatory process in which stakeholders contributed to the development of the model and guided the analysis, as well as insights into Malaysia’s decarbonization potential and the role of multilevel governance.

cities↗

DOE OSTI2021

Heavy-Duty Electric Fleet Depot Charging Load Profiles & Substation Load Integration Assessment Results

This data set includes the 24-hour fleet depot charging load profiles (15-min. average demand) and substation load integration assessment results produced for the study, "Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems", published in 2021 (https://doi.org/10.1038/s41560-021-00855-0). The code developed to generate these load profiles is publicly available at https://github.com/NREL/hdev-depot-charging-2021. Please cite as: Borlaug, B., Muratori, M., Gilleran, M., Woody, D., Muston, W., Canada, T., Ingram, A., Gresham, H., and McQueen, C., (2021). "Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems". https://doi.org/10.1038/s41560-021-00855-0.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Downscaling Global Land Cover Projections from an Integrated Assessment Model for Use in Regional Analyses: Results and Evaluation for the US from 2005 to 2095

Projections of land cover change generated from Integrated Assessment Models (IAM) and other economic-based models can be applied for analyses of environmental impacts at subregional and landscape scales. For those IAM and economic models that project land use at the sub-continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30m) and at the global extent with relatively coarse spatial resolution (0.5 degree).

West, Tristram O.↗

NASA NTRS2015

Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impacts, Vulnerability, and Adaptation: Chapter - 5

The global change research community has recognized that new pathway and scenario concepts are needed to implement impact and vulnerability assessment where precise prediction is not possible, and also that these scenarios need to be logically consistent across local, regional, and global scales. For global climate models, representative concentration pathways (RCPs) have been developed that provide a range of time-series of atmospheric greenhouse-gas concentrations into the future. For impact and vulnerability assessment, new socio-economic pathway and scenario concepts have also been developed, with leadership from the Integrated Assessment Modeling Consortium (IAMC).This chapter presents concepts and methods for development of regional representative agricultural pathways (RAOs) and scenarios that can be used for agricultural model intercomparison, improvement, and impact assessment in a manner consistent with the new global pathways and scenarios. The development of agriculture-specific pathways and scenarios is motivated by the need for a protocol-based approach to climate impact, vulnerability, and adaptation assessment. Until now, the various global and regional models used for agricultural-impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation, public availability, and consistency across disciplines. These practices have reduced the credibility of assessments, and also hampered the advancement of the science through model intercomparison, improvement, and synthesis of model results across studies. The recognition of the need for better coordination among the agricultural modeling community, including the development of standard reference scenarios with adequate agriculture-specific detail led to the creation of the Agricultural Model Intercomparison and Improvement Project (AgMIP) in 2010. The development of RAPs is one of the cross-cutting themes in AgMIP's work plan, and has been the subject of ongoing work by AgMIP since its creation.

agriculture↗

DOE OSTI2014

From land use to land cover: Restoring the afforestation signal in a coupled integrated assessment - earth system model and the implications for CMIP5 RCP simulations

Climate projections depend on scenarios of fossil fuel emissions and land use change, and the IPCC AR5 parallel process assumes consistent climate scenarios across Integrated Assessment and Earth System Models (IAMs and ESMs). To facilitate consistency, CMIP5 used a novel land use harmonization to provide ESMs with seamless, 1500-2100 land use trajectories generated by historical data and four IAMs. However, we have identified and partially addressed a major gap in the CMIP5 land coupling design. The CMIP5 Community ESM (CESM) global afforestation is only 22% of RCP4.5 afforestation from 2005 to 2100. Likewise, only 17% of the Global Change Assessment Model’s (GCAM’s) 2040 RCP4.5 afforestation signal, and none of the pasture loss, were transmitted to CESM within a newly integrated model. This is a critical problem because afforestation is necessary for achieving the RCP4.5 climate stabilization. We attempted to rectify this problem by modifying only the ESM component of the integrated model, enabling CESM to simulate 66% of GCAM’s afforestation in 2040, and 94% of GCAM’s pasture loss as grassland and shrubland losses. This additional afforestation increases vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, implying different climate scenarios between CMIP5 GCAM and CESM. Similar inconsistencies likely exist in other CMIP5 model results, primarily because land cover information is not shared between models, with possible contributions from afforestation exceeding model-specific, potentially viable forest area. Further work to harmonize land cover among models will be required to adequately rectify this problem.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

AgMIP Regional Integrated Assessment of Agricultural Systems in Nioro, Senegal: Representative Agricultural Pathways, Climate, Crop and Economic Datasets

This paper describes the datasets that were used to implement an AgMIP Regional Integrated Assessment for the Nioro region of Senegal to assess the potential impacts of climate change on the principal agricultural system in the Senegal peanut basin and to assess adaptations of that system to climate change under current as well as future climate and socio-economic conditions. This dataset includes the Representative Agricultural Pathways developed for Nioro from 2000-2050; the climate data that were used to implement crop yield simulations; the data that were used to parameterize the DSSAT and APSIM crop models, including historical climate data and future climate scenarios; and the data that were used to parameterize the Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOAMD) economic simulation model, as well as simulated model outputs.

AgMIP↗

DOE OSTI2016

Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and behaviorally-realistic model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. Moreover, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2018

An information diffusion technique to assess integrated hazard risks

An integrated risk is a scene in the future associated with some adverse incident caused by multiple hazards. An integrated probability risk is the expected value of disaster. Due to the difficulty of assessing an integrated probability risk with a small sample, weighting methods and copulas are employed to avoid this obstacle. To resolve the problem, in this paper, we develop the information diffusion technique to construct a joint probability distribution and a vulnerability surface. Then, an integrated risk can be directly assessed by using a small sample. A case of an integrated risk caused by flood and earthquake is given to show how the suggested technique is used to assess the integrated risk of annual property loss.

58 GEOSCIENCES↗

DOE OSTI2020

The role of nuclear in China’s energy future: insights from integrated assessment

China, the world’s largest electricity consumer, has strong motivations to deploy nuclear power due to increasing electricity demand and environmental concerns. However, there are social, institutional, and technical barriers to future nuclear expansion. This paper provides an updated assessment of nuclear energy potential in China with analyses at both national and provincial levels and compares results with studies previously conducted. Using an integrated assessment model, this paper considers the interactions among different socioeconomic development pathways, technology options, climate policies, and social/political concerns on inland siting. Among all factors explored, climate policies have the most significant impact on accelerating the deployment of nuclear technologies. Inland siting of nuclear power plants increases total capacity, but the impact is limited without climate policy. The amount of annual nuclear generation across scenarios and studies is unlikely to rise above 11% by 2030 and 30% by 2050 of total Chinese electricity generation. A dramatic increase in total Chinese nuclear energy generating capacity – around 3900 TWh of nuclear generation by 2050 – is only possible in scenarios where China sees electricity demand increase substantially, sticks to and tightens its current Paris Accord commitments, achieves low costs of nuclear technologies, and allows inland siting of nuclear power plants.

China, integrated assesment, Nuclear Power Plants↗

DOE OSTI2012

Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the U.S. Pulp and Paper Sector

Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. How to effectively analyze and manage the costs associated with GHG reductions becomes extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models. In this report, we first conduct a brief review of different representations of end-use technologies (mitigation measures) in various energy-climate models, followed by the problem statement, and a description of the basic concepts of quantifying the cost of conserved energy including integrating no-regrets options.

03 NATURAL GAS↗

DOE OSTI2017

Evaluation of integrated assessment model hindcast experiments: a case study of the GCAM 3.0 land use module

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data are available) are being undertaken increasingly often by the integrated assessment model (IAM) community, across many scales of models. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation-based measures that can be applied on different spatial scales (regional versus global) to make evaluating the large number of variable–region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. An ideal evaluation method for hindcast experiments in IAMs would feature both absolute measures for evaluation of a single experiment for a single model and relative measures to compare the results of multiple experiments for a single model or the same experiment repeated across multiple models, such as in community intercomparison studies. The performance benchmarks highlight the use of this scheme for model evaluation in absolute terms, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. To demonstrate the use of and types of results possible with the evaluation method, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. The question of how to more holistically evaluate models as complex as IAMs is an area for future research. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs that require global supply to equal global demand at each time period, such as GCAM. The results of this work indicate it is unlikely that a single evaluation measure for all variables in an IAM exists, and therefore sector-by-sector evaluation may be necessary.

58 GEOSCIENCES↗

DOE OSTI2017

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Evaluating the regional risks to food availability and access from land-based climate policies in an Integrated Assessment Model

Mitigating greenhouse gas (GHG) emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the Global Change Analysis Model (GCAM4.0). We then project consumer prices and our measure of food security along the Shared Socioeconomic Pathways (SSPs). Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions is more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.

Cui, Ryna↗