25 research outputs found
The impact of live supervision on the family therapist\u27s level of immediacy, anxiety, responsiveness, and genuineness
The effects of live supervision via telephone on therapists was explored. Three supervisors experienced in live supervision were each asked to supervise live, two family therapists until they had each made a minimum of three phone interventions per therapist. The therapists\u27 behavior two minutes immediately before the interventions and two minutes immediately after the phone interventions were then rated by judges using nonverbal and scale measures. Therapists\u27 behavior were rated on the following factors: anxiety, responsiveness, immediacy, and genuineness. The results did not indicate any significant differences between therapist\u27s behavior before and after phone interventions, and only modest differences in behaviors between therapists using different supervisors. The findings are supportive of live supervision as there was no evidence the live interventions affect the therapists negatively on the above dimensions. The findings are discussed with implications for the field of supervision
Electric Sector Policy, Technological Change, and U.S. Emissions Reductions Goals: Results from the EMF 32 Model Intercomparison Project
The Energy Modeling Forum (EMF) 32 study compares a range of coordinated scenarios to explore implications of U.S. climate policy options and technological change on the electric power sector. Harmonized policy scenarios (including mass-based emissions limits and various power-sector-only carbon tax trajectories) across 16 models provide comparative assessments of potential impacts on electric sector investment and generation outcomes, emissions reductions, and economic implications. This paper compares results across these policy alternatives, including a variety of technological and natural gas price assumptions, and summarizes robust findings and areas of disagreement across participating models. Under a wide range of policy, technology, and market assumptions, model results suggest that future coal generation will decline relative to current levels while generation from natural gas, wind, and solar will increase, though the pace and extent of these changes vary by policy scenario, technological assumptions, region, and model. Climate policies can amplify trends already under way and make them less susceptible to future market changes. The model results provide useful insights to a range of stakeholders, but future research focused on intersectoral linkages in emission reductions (e.g., the role of electrification), effects of energy storage, and better coverage of bioenergy with carbon capture and storage (BECCS) can improve insights even further
Electric sector policy, technological change, and U.S. emissions reductions goals: Results from the EMF 32 model intercomparison project
The Energy Modeling Forum (EMF) 32 study compares a range of coordinated scenarios to explore implications of U.S. climate policy options and technological change on the electric power sector. Harmonized policy scenarios (including mass-based emissions limits and various power-sector-only carbon tax trajectories) across 16 models provide comparative assessments of potential impacts on electric sector investment and generation outcomes, emissions reductions, and economic implications. This paper compares results across these policy alternatives, including a variety of technological and natural gas price assumptions, and summarizes robust findings and areas of disagreement across participating models. Under a wide range of policy, technology, and market assumptions, model results suggest that future coal generation will decline relative to current levels while generation from natural gas, wind, and solar will increase, though the pace and extent of these changes vary by policy scenario, technological assumptions, region, and model. Climate policies can amplify trends already under way and make them less susceptible to future market changes. The model results provide useful insights to a range of stakeholders, but future research focused on intersectoral linkages in emission reductions (e.g., the role of electrification), effects of energy storage, and better coverage of bioenergy with carbon capture and storage (BECCS) can improve insights even further
Emissions and Energy Impacts of the Inflation Reduction Act
If goals set under the Paris Agreement are met, the world may hold warming
well below 2 C; however, parties are not on track to deliver these commitments,
increasing focus on policy implementation to close the gap between ambition and
action. Recently, the US government passed its most prominent piece of climate
legislation to date, the Inflation Reduction Act of 2022 (IRA), designed to
invest in a wide range of programs that, among other provisions, incentivize
clean energy and carbon management, encourage electrification and efficiency
measures, reduce methane emissions, promote domestic supply chains, and address
environmental justice concerns. IRA's scope and complexity make modeling
important to understand impacts on emissions and energy systems. We leverage
results from nine independent, state-of-the-art models to examine potential
implications of key IRA provisions, showing economy wide emissions reductions
between 43-48% below 2005 by 2035
Turn Down for What? The Economic Value of Operational Flexibility in Electricity Markets
Social cost of carbon pricing of power sector CO2: accounting for leakage and other social implications from subnational policies
In environments where climate policy has partial coverage or unequal participation, carbon dioxide (CO2) emissions or economic activity may shift to locations and sectors where emissions are unregulated. This is referred to as leakage. Leakage can offset or augment emissions reductions associated with a policy, which has important environmental and economic implications. Although leakage has been studied at national levels, analysis of leakage for subnational policies is limited. This is despite greater market integration and many existing state and regional environmental regulations in the US. This study explores leakage potential, net emissions changes, and other social implications in the US energy system with regionally differentiated pricing of power sector CO2 emissions. We undertake an economic analysis using EPRI's US-REGEN model, where power sector CO2 emissions are priced in individual US regions with a range of social cost of carbon (SCC) values. SCC estimates are being considered by policy-makers for valuing potential societal damages from CO2 emissions. In this study, we evaluate the emissions implications within the SCC pricing region, within the power sector outside the SCC region, and outside the power sector (i.e. in the rest of the energy system). Results indicate that CO2 leakage is possible within and outside the electric sector, ranging from negative 70% to over 80% in our scenarios, with primarily positive leakage outcomes. Typically ignored in policy analysis, leakage would affect CO2 reduction benefits. We also observe other potential societal effects within and across regions, such as higher electricity prices, changes in power sector investments, and overall consumption losses. Efforts to reduce leakage, such as constraining power imports into the SCC pricing region likely reduce leakage, but could also result in lower net emissions reductions, as well as larger price increases. Thus, it is important to look beyond leakage and consider a broader set of environmental and economic metrics. Leakage rates, net emissions outcomes, electricity price changes, fuel market effects, and macroeconomic costs vary by region of the country, time, policy stringency, policy design (e.g. leakage mitigation provisions), policy environment in neighboring regions, and price responsiveness of demand
The role of carbon capture technologies in greenhouse gas emissions-reduction models: A parametric study for the U.S. power sector
This paper analyzes the potential contribution of carbon capture and storage (CCS) technologies to greenhouse gas emissions reductions in the U.S. electricity sector. Focusing on capture systems for coal-fired power plants until 2030, a sensitivity analysis of key CCS parameters is performed to gain insight into the role that CCS can play in future mitigation scenarios and to explore implications of large-scale CCS deployment. By integrating important parameters for CCS technologies into a carbon-abatement model similar to the EPRI Prism analysis (EPRI, 2007), this study concludes that the start time and rate of technology diffusion are important in determining emissions reductions and fuel consumption for CCS technologies. Comparisons with legislative emissions targets illustrate that CCS alone is very unlikely to meet reduction targets for the electric-power sector, even under aggressive deployment scenarios. A portfolio of supply and demand-side strategies is needed to reach emissions objectives, especially in the near term. Furthermore, model results show that the breakdown of capture technologies does not have a significant influence on potential emissions reductions. However, the level of CCS retrofits at existing plants and the eligibility of CCS for new subcritical plants have large effects on the extent of greenhouse gas emissions reductions.Carbon capture and storage Integrated assessment modeling Technological diffusion
Economic drivers of wind and solar penetration in the US
Much has been made of the potential for wind and solar generation to supply cheap, low-emissions electricity, but considerable disagreement exists as to which combinations of many potential drivers will enable deep penetration of these technologies. Most existing analyses consider limited factors in isolation, such as investment costs or energy storage, and do not provide rigorous support for understanding which combinations of factors could underpin a leading role for wind and solar. This study addresses this gap by undertaking a systematic sensitivity analysis using a state-of-the-art energy-economic model to comprehensively evaluate the relative magnitudes of five key drivers that may influence future wind and solar deployment in the United States. We find future wind and solar capital costs and carbon policy are the dominant factors, causing the average wind and solar share to vary by 38 and 31 percentage points, respectively. Transmission and storage availability have much smaller effects, causing the average share to vary by no more than 15 and 5 percentage points, respectively. No single factor unilaterally determines wind and solar deployment. The variable renewable share of electricity generation never reaches 100% nationally in any scenario even with low-cost storage, as decreasing marginal returns at higher deployments eventually outpace cost reductions. Average wind and solar shares and ranges of possible outcomes are higher in this study relative to recent multi-model comparison studies due to lower renewable costs and the potential for more stringent policies. Understanding drivers and barriers to renewable deployment has important ramifications for technology developers, infrastructure, market design, and policymakers, and this research provides insights as to which combinations of drivers lead to the greatest share of economic wind and solar deployment and why
Electric Sector Capacity Planning under Uncertainty: Shale Gas and Climate Policy in the US ∗
This research investigates how uncertainties related to shale gas production will influence the longterm deployment of supply-side technologies in US electricity markets, particularly under uncertain climate policy constraints. Using a two-stage stochastic programming approach, model results suggest that there is considerable value to limiting fugitive methane emissions from shale gas. This strategy would give the electric sector the flexibility of waiting to observe the resolution of uncertainties before building new capacity. Information about the stringency of greenhouse gas abatement is most valuable to utilities and generators when tight emissions caps are realized. The stochastic solution is especially valuable if no pre-2030 mitigation is assumed, if the uncertainty resolution date is delayed, or if the social cost of carbon is incorporated into the calculations