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At least 631 records · Page 35

Salt Hydrate Eutectic Thermal Energy Storage for Building Thermal Regulation (Final Technical Report)

Thermal energy storage is anticipated to play an important role in developing the power grid of the future - a power grid that meets increasing demands of users, is resistant to disruptions, but also allows for greater penetration of renewable resources. Specifically, thermal energy storage materials can be integrated into HVAC systems and building envelopes, where they can be used to shift power demands for building climate control from periods of peak demand to periods of low demand. Phase change materials (PCMs) are compelling as low-cost, high energy density thermal energy storage materials for building thermal management. However, there is a lack of high performance low-cost PCMs within the specific temperature ranges which would most effectively allow for power load shifting. Inorganic salt hydrates represent a promising class of PCMs, but their inherent limitations cause them to be currently unavailable for reliable building applications. The overarching goals of this research effort are to: 1) Discover low-cost, high volumetric density salt hydrate eutectic PCMs to store low-quality heat (10 to 40 °C); 2) Introduce a high thermal conductivity matrix to reduce the time constant for energy storage to ~0.1 to 1 hr, incorporate nucleation catalysts to decrease undercooling, and utilize microencapsulation and shape stabilization approaches, minimizing moisture loss/gain, mitigating phase separation, and maintaining stable melting behavior over the lifetime of the compounds; 3) Evaluate the impact these systems have on peak load shifting, and the potential for overall energy savings under different climatic scenarios and building configurations. These goals will be achieved by an integrated research program consisting of six cohesive research subtasks: 1) Materials discovery of eutectic salt hydrate PCMs by using computationally predicted thermodynamic equilibria, coupled with high-throughput experimental validation, 2) Rapid experimental screening of nucleation catalysts identified through robust computational databases, 3) Embedding salt hydrate PCM into a low cost and scalable high conductivity matrix, 4) Microencapsulation of salt hydrate microspheres using hybrid inorganic-polymer microencapsulation approach, 5) Shape stabilization by thermoreversible salt hydrate salogels, and 6) Analysis of end-use using thermal simulations, and characterization of mock-up energy storage finished components.

25 ENERGY STORAGE↗

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗

Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report

In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

Recharge Demand Mitigation for Latent Heat Thermal Energy Storage at Off-peak Hours

The utilization of integrated heat pump thermal energy storage (HP-TES) systems for space conditioning applications can reduce electrical power demand and achieve utility savings resulting from peak shaving and load shifting. However, issues arise when the energy required to recharge the TES exceeds the shifted energy demand, especially in extreme climates where high-temperature lifts between the outdoor air conditions and phase-change materials (PCMs) during recharging may occur. In this work, a single room-temperature (22°C) PCM-TES is integrated into a single-speed heat pump system using a secondary hydronic loop where the TES is recharged using the outdoor unit during off-peak hours. Three recharge strategies were investigated as potential pathways to reduce recharging power demand: (i) considering different heat source/sink temperatures, (ii) using a variable-speed compressor, and (iii) using a variable-speed pump. Simulations were conducted using Modelica for HP-TES recharging at different heat source/sink temperatures from -30 – 20℃ in heating mode and 0 – 30℃ in cooling mode. Results show that the most effective recharge demand reduction strategy is an HP-TES system using a single-speed compressor with a variable-speed pump for the hydronic loop run at preferable heat source/sink temperatures when the temperature lifts were reduced. Utilizing a variable-speed compressor for the HP-TES system reduced recharge time in extreme cases at the cost of additional compressor power input. The findings motivate potential control strategies that minimize recharge energy and maximize peak energy savings, hence reducing overall operating costs and annual energy consumption for HP-TES systems for space conditioning applications.

25 ENERGY STORAGE↗

Critical adjustment of land mitigation pathways for assessing countries' climate progress

Collective progress towards the Paris Agreement’s temperature targets will be assessed by the Agreement’s Global Stocktake process. Global emission pathways by Integrated Assessment Models (IAMs) are a likely benchmark against which aggregated countries’ greenhouse gas mitigation pledges will be assessed. However, this approach requires comparability, which is currently hampered by a 5 GtCO2yr-1 mismatch between the estimated global land anthropogenic flux of IAMs and countries’ GHG inventories (GHGIs) for 2005-2015. We show that this gap is mostly the result of differences in how the anthropogenic forest sink is defined. Countries define managed forest more broadly than IAMs, and on this larger area typically consider anthropogenic also fluxes due to human-induced environmental change, which IAMs do not include their pathways. Using five IAMs and a dynamic global vegetation model (DGVM), we present and apply a novel method that adjusts IAM results to the countries’ definition, closing the gap with GHGIs at global and regional scale. When expressed in a way compatible with GHGIs, adjusted 1.5°C and well-below 2°C pathways have a cumulative CO2 balance until carbon neutrality that is 110–176 GtCO2 lower than the original IAMs pathways. The use of these country-compatible emission pathways under the Global Stocktake would therefore be essential for an accurate assessment of the collective progress towards the Paris Agreement’s climate goals.

Grassi, Giacomo↗

Interdisciplinary Workshop on the Impacts of Land Use and Land Management on Earth System Evolution, Biogeochemical Cycles, Extremes, and Inter-Sectoral Dynamics (Final Report)

The Aspen Global Change Institute (AGCI) convened a week-long interdisciplinary science workshop from September 15-20, 2019 entitled, “Impacts of Land Use and Land Management on Earth System Evolution, Biogeochemical Cycles, Extremes, and Inter-Sectoral Dynamics.” The purpose of the workshop was to advance research on the impacts of land use and land management on climate, carbon emissions, and extremes, as well as the impact of land-use change on important societal issues such as food, water, and energy security. The workshop was co-chaired by Kate Calvin (PNNL), George Hurtt (University of Maryland), and Dave Lawrence (National Center for Atmospheric Research). Co-funders of the workshop included NASA, NOAA, and travel support for European colleagues through CRESCENDO. This workshop brought together 31 professionals with expertise across biogeochemistry, climate impacts, mitigation, land use datasets, and societal impacts to coordinate on upcoming research and publications on the role of biogeochemical and biophysical properties of the Earth surface and their implications for climate, as conducted through the Land Use model Intercomparison Project (LUMIP), which is part of Phase 6 of the Coupled Model Intercomparison Project (CMIP6). A primary outcome of the meeting was the definition and planning of a series of LUMIP papers that will rely on the LUMIP and CMIP6 simulations. By the end of the meeting more than twenty papers and paper lead authors had been identified and scoped out. Around ten of these papers were submitted by the December 31, 2019 IPCC deadline.

54 ENVIRONMENTAL SCIENCES↗

Monitoring Methane Emissions from Oil and Gas Operations

The atmospheric concentration of methane has more than doubled since the start of the Industrial Revolution. Methane is the second-most-abundant greenhouse gas created by human activities and a major driver of climate change. This APS-Optica report provides a technical assessment of the current state of monitoring U.S. methane emissions from oil and gas operations, which accounts for roughly 30% of U.S. anthropogenic methane emissions. The report identifies current technological and policy gaps and makes recommendations for the federal government in three key areas: methane emissions detection, reliable and systematized data and models to support mitigation measures, and effective regulation.

02 PETROLEUM↗

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Climate projections over the Great Lakes Region: using two-way coupling of a regional climate model with a 3-D lake model

Abstract. Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large lakes. Using the three carefully selected Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs), we show that the GLARM ensemble average substantially reduces surface air temperature and precipitation biases of the driving GCM ensemble average in present-day climate simulations. The improvements are not only displayed from an atmospheric perspective but are also evident in the accurate simulations of lake temperature and ice coverage. We further present the GLARM projected climate change for the mid-21st century (2030–2049) and the late 21st century (2080–2099) in the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.1 ∘C by the mid-21st century and 4.1–5.0 ∘C by the end of the century relative to the early century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.8 ∘C and late-century warming to 1.8–2.7 ∘C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from 0 % to 13 % during the mid-century and from 9 % to 32 % during the late century in different scenarios and simulations. The most significant increases are projected in spring and fall when current precipitation is highest and a minimal increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial variability. The most significant LST increases occur in Lakes Superior and Ontario. The strongest warming is projected in spring that persists into the summer, resulting from earlier and more intense stratification in the future. In addition, diminishing winter stratification in the future suggests the transition from dimictic lakes to monomictic lakes by the end of the century. In contrast, a relatively smaller increase in LSTs during fall and winter is projected with heat transfer to the deep water due to the strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to reduce to 3 %–15 % and 10 %–40 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration is projected to decrease by up to 60 d.

Xue, Pengfei (ORCID:000000025702421X)↗

Impacts of Thawing Permafrost on Residential Infrastructure: Results and Resources

Permafrost underlies approximately 20% of the landmass in the Northern Hemisphere. Inevitably human infrastructure has been and will be built on permafrost; however, due to climate change, the permafrost in many regions has begun to thaw. Using past reports and surveys as guidance, a survey was conducted to track the effects of permafrost thaw on housing infrastructure in the community of Point Lay, Alaska. The Cold Climate Housing Research Center, Inc. and the National Renewable Energy Lab conducted a literature review and interviews to document community issues from thawing permafrost and identify potential mitigation strategies for existing and new infrastructure. Researchers also identified strategies for individual homeowners to inspect their foundations for current issues or anticipate future ones. This poster will cover the results from the survey on the effects of permafrost thawing to Point Lay and include permafrost basics, common concerns from thawing permafrost, steps to identify permafrost sites and visible signs of permafrost degradation, and potential mitigation strategies that may be beneficial to Alaskans and increase resilience in the Arctic.

Alaska↗

Aerosol-Cloud Interactions From Aviation Soot Emissions

Current models estimate global aviation contributes approximately 5% to the total anthropogenic climate forcing, with aerosol-cloud interactions having the greatest effect. However, radiative forcing estimates from aviation aerosol-cloud interactions remain undetermined. There is an expected significant increase in aircraft emissions with aviation demand expected to rise by over 4% per year. Soot may play an important role in the ice nucleation of aircraft-induced cirrus formation due to a high emission rate, but the ice nucleating properties are poorly constrained. Understanding the microphysical processes leading to atmospheric ice crystal formation is crucial for the reliable parameterization of aerosol-cloud interactions in climate models due to their impact on precipitation and cloud radiative properties. Ice nucleation of aircraft-emitted soot is potentially affected by particle morphology with condensation of supercooled water occurring in pores followed by ice nucleation. However, soot has heterogeneous properties and undergoes atmospheric aging and oxidation that could change surface properties and contribute to complex ice nucleation processes. Further, this review synthesizes current knowledge of ice nucleation catalyzed by aviation in the cirrus regime and its effects on global radiative forcing. Further research is required to determine the ice nucleation and microphysical processes of cirrus cloud formation from aviation emissions in both controlled laboratory and field investigations to inform models for more accurate climate predictions and to provide efficient mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗

Recent Widespread Deceleration of Global Surface Urban Heat Islands Unveiled by Satellites

Tracking the temporal dynamics of urban heat island (UHI) is critical for urban heat adaptation and mitigation strategies. However, whether UHI trends have shifted recently and their underlying drivers remain unknown. Here we investigate the variabilities in surface UHI trends and their associated determinants in 2,104 cities worldwide from 2000 to 2022. Our findings reveal that approximately half of the world's cities have experienced notable shifts in surface UHI trends, predominantly characterized by UHI deceleration. These shifts can be primarily attributed to alterations in vegetation trends during the day and to modifications in surface albedo and local warming trends at night. Our study challenges the conventional linear models commonly employed to estimate surface UHI trends, suggesting potential biases in such estimates. Our findings underscore the need for nuanced policies to curtail UHI growth by considering changes in urban underlying surfaces and background climate, particularly from a nonlinear perspective.

54 ENVIRONMENTAL SCIENCES↗

Which “second-best” climate policies are best? Simulating cost-effective policy mixes for passenger vehicles

In the real-world of political opposition and complex market failures, carbon pricing alone will not achieve deep GHG mitigation targets. Hence, in this study, we search for the most cost-effective “second-best” policies. Focusing on the light-duty vehicle sector in the case of Canada, we compare several policies in terms of effectiveness (regarding 2030 GHG goals) and mitigation costs, namely: (i) a carbon tax; (ii) a vehicle emission standard (or VES); (iii) a zero emissions vehicle (ZEV) mandate, and (iv) combinations of all three at various stringencies. In this effort, we apply the AUtomaker-consumer Model (AUM), which endogenously simulates consumer and automaker decisions and technological change. Comparing individual policies, the regulations are about three times more expensive than the carbon tax. Among “second-best” policies, the VES is cheaper than a ZEV mandate at lower stringencies, but at higher stringencies the two are similarly efficient (both incentivize widespread ZEV deployment). In policy mixes, cost-effectiveness is improved by a carbon tax. Specifically, inclusion of a CDN$100–150/tonne tax can achieve targets while being 30–40% less costly than a regulation alone. We suggest that policymakers implement carbon pricing as stringently as politically feasible (for efficiency), complemented by regulations as needed (for efficacy) to meet GHG targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Investigation of pre-cooling as a recommended measure to improve residential buildings’ thermal resilience during heat waves

More intense heat waves are expected to occur more frequently in the twenty-first century. During severe heat waves, cooling capacity shortfall and overheating are likely to occur in residential buildings, and this will adversely affect occupant's thermal comfort and productivity. We propose a strategy of pre-cooling the house during off-peak hours to mitigate overheating during heat waves. Additionally, simulation results of a prototype single-family house show that adopting the rule-based control (RBC) of pre-cooling thermostat setpoint schedule is effective in reducing thermal discomfort, and that the efficacy of pre-cooling depends upon several building characteristics. An optimized control (OC) of the thermostat setpoint schedule was developed based on the simulation of a prototype building. A simplified yet improved RBC (IRBC) pre-cooling schedule was then extracted from the OC schedule for practical implementation at a larger scale. The effects of the RBC schedule and IRBC schedule were evaluated in the King District of Fresno, which contains 814 residential buildings. Results show that both thermostat setpoint schedules can reduce overheating effectively and that IRBC is slightly better than RBC for most buildings. The findings support the California government's recommendation on pre-cooling to mitigate overheating, which can be further improved with an optimized thermostat setpoint schedule broadcast to residents through early alert messages before a heat wave.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗