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We need human behavioural change to decarbonize our buildings. This requirement arises from our needs, lifestyle energy choices and interactions with buildings, and is an underexploited, yet essential demand-side opportunity for rapid and sustainable decarbonization. We propose a sufficiency-oriented approach that fosters equitable building decarbonization, while maintaining planetary boundaries.

With climate change leading to more frequent, more intense, and longer durations of extreme weather events such as heat waves and cold snaps, it is essential to maintain safe indoor environmental conditions for occupants during such events, which may coincide with, or even cause, power outages that expose residents to health risks. Analyzing the impacts of extreme weather events on the thermal resilience of buildings can help stakeholders (including occupants) understand the risk and inform them about mitigation and adaptation actions. Moreover, analyzing the technological, social and policy dimensions of thermal resilience is critical for climate-proofing buildings. This paper presents 10 questions that highlight the most important issues regarding the thermal resilience of buildings for occupants in the face of climate change. The proposed questions and answers aim to provide insights into current and future building thermal resilience research and applications, and more importantly to inspire new significant questions in the field.

California has a state-wide goal of carbon neutrality by 2045. Decarbonization for disadvantaged communities (DACs) poses extra challenges due to financial, informational, language, and other barriers. This paper presents the methodology, results, and analysis of energy efficiency measures (EEMs) to save energy, reduce CO2 emission, and promote clean energy access at the district scale for two DACs in Fresno, California. The methods are broadly applicable to other neighborhoods across the U.S. 22 EEMs were identified and modelled for all residential buildings in the two DACs both individually and as packages. Results show that for energy and CO2 reduction purposes, the top performing EEM package can decrease energy use and CO2 emissions by an average of 60%. For electrification, heat pump water heaters are a viable solution, coupled with air source or mini-split heat pumps. Replacing gasoline vehicles with electric vehicles is another important measure in electrification and reducing GHG emissions.

At scale, biomass-based fuels are seen as long-term alternatives to conventional shipping fuels to reduce greenhouse gas emissions in the maritime sector. While the operational benefits of renewable methanol as a marine fuel are well-known, its cost and environmental performance depend largely on production method and geographic context. In this study, a techno-economic and environmental assessment of renewable methanol produced by gasification of forestry residues is performed. Two biorefinery systems are modeled thermodynamically for the first time, integrating several design changes to extend past work: (1) methanol synthesized by gasification of torrefied biomass while removing and storing underground a fraction of the carbon initially contained in it, and (2) integration of a polymer electrolyte membrane (PEM) electrolyzer for increased carbon efficiency via hydrogen injection into the methanol synthesis process. The chosen use case is set in California, with forest residue biomass as the feedstock and the ports of Los Angeles and Long Beach as the shipping fuel demand point. Methanol produced by both systems achieves substantial lifecycle greenhouse gas emissions savings compared to traditional shipping fuels, ranging from 38 to 165%, from biomass roadside to methanol combustion. Renewable methanol can be carbon-negative if the CO2 captured during the biomass conversion process is sequestered underground with net greenhouse gas emissions along the lifecycle amounting to −57 gCO2eq/MJ. While the produced methanol in both pathways is still more expensive than conventional fossil fuels, the introduction of CO2eq abatement incentives available in the U.S. and California could bring down minimum fuel selling prices substantially. The produced methanol can be competitive with fossil shipping fuels at credit amounts ranging from $150 to $300/tCO2eq, depending on the eligible credits.

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. 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.

Disadvantaged communities face a growing threat to staying safe during heat waves, especially during coincident power outages. This study develops a methodology to evaluate the effectiveness of passive cooling measures (those that operate without power) to improve residential building heat resilience. Building performance is simulated for representative homes and on district scales in two disadvantaged communities in Fresno, California. Eleven passive measures are evaluated using four heat resilience metrics with and without grid power. Results show performance of the mitigation measures varies by building characteristics, surrounding environment, and power scenario. The two most effective measures were installing solar-control window films and adding roof insulation. For pre-1978 single-family homes, these two measures can reduce unmet degree-hours (UDH) indoors by 12% and 11% respectively without grid power, or 28% and 37% with grid power. Their respective UDH reductions at district scale typically range 8% — 20% and 4% — 12% without grid power, or 14% — 44% and 8% — 51% with grid power. Top floors have higher overheating risk than lower floors during extreme heat events with coincident power outages. Natural ventilation can help, reducing UDH by 21% — 26%. The methodology and findings from this study can help cities, communities, and utilities develop effective and targeted strategies to promote greater residential heat resilience.

Extreme heat is one of the leading causes of weather-related deaths in the U.S. Exposure to extreme heat will be exacerbated due to global climate change. It is thus crucial to design a key performance indicator, heat vulnerability index (HVI), to represent overall heat risk which can help identify susceptible regions and sub-populations in cities in the face of heatwaves. Most existing HVI tools only consider outdoor heat exposure. This paper developed an HVI web map tool incorporating both the outdoor and the indoor heat exposure, as well as population sensitivity and adaptation capability across census tracts in the city of Fresno, California. The tool can assist the planning of infrastructure and resources to reduce residents’ vulnerability to extreme heat events.

Long-distance road-freight transport emits a large share of Germany's greenhouse gas (GHG) emissions. A potential solution for reducing GHG emissions in this sector is to use green hydrogen in fuel cell electric vehicles (FC-HDV) and establish an accompanying hydrogen refueling station (HRS) network. In this paper, we apply an existing refueling network design model to a HDV-HRS network for Germany until 2050 based on German traffic data for heavy-duty trucks and estimate its costs. Comparing different fuel supply scenarios (pipeline vs. on-site), The on-site scenario results show a network consisting of 137 stations at a cost of 8.38 billion € per year in 2050 (0.40 € per vehicle km), while the centralized scenario with the same amount of stations shows a cheaper cost with 7.25 billion euros per year (0.35 € per vehicle km). The hydrogen cost (LCOH) varies from 5.59 €/kg (pipeline) to 6.47 €/kg (on-site) in 2050.

Unitized regenerative fuel cells (URFC) convert electrical energy to and from chemical bonds in hydrogen. URFCs have the potential to provide economical means for efficient long-term, seasonal, energy storage and on-demand conversion back to electrical energy. We first optimize the catalyst layer for discrete electrolyzer and fuel cell and then configure the URFC. The goal is to identify a cost competitive configuration for URFCs, and demonstrate it in terms of upper limit of round trip efficiencies (RTEs). Two possible configurations of URFCs are compared via experiments and techno-economic analysis (TEA), which emphasize the advantages of the unconventional constant-electrode (CE) URFC over the traditional constant-gas (CG) configuration. We also study the stability via accelerated stress tests (ASTs) and demonstrate steady state operation in a daily cycle for day to night energy shifting. From the investigations, the optimum composition of the URFC anode catalyst layer is 90 at% Ir-black balanced by Pt-black for both CE and CG configurations. At 80 °C and 1 A cm-2, the optimized CE URFC achieves 57% and 60% RTE with air and O2 as the reductant gases, respectively. We then evaluated the differences in durability using an AST over 10k charge-discharge cycles; the results reveal that the wider potential window at the anode in CE (0.05-1.55 V) has minimal effect on catalyst layer stability compared to CG (0.55-1.55 V). Furthermore, there was no degradation up to the range of 2k-5k cycles; beyond that the fuel cell (discharge) performance degraded while the electrolyzer (charge) performance was still stable. The observations here indicate substantial potential to employ URFCs as efficient and cost-effective bidirectional energy-conversion devices within energy storage and utilization systems after appropriate technological and operational optimizations.

Hydrofluorocarbons (HFCs) are widely used as cooling agents in refrigeration and air conditioning, as solvents in industrial processes, as fire-extinguishing agents, for foam blowing, and as aerosol propellants. They have been used in large quantities as the primary substitutes for ozonedepleting substances regulated under the Montreal Protocol. However, many HFCs are potent greenhouse gases (GHGs) and as such subject to global phase-down under the Kigali Amendment (KA) to the Montreal Protocol. In this study, we develop a range of long-Term scenarios for HFC emissions under varying degrees of stringency in climate policy and assess co-benefits in the form of electricity savings and associated reductions in GHG and air pollutant emissions. Due to technical opportunities to improve energy efficiency in cooling technologies, there exist potentials for significant electricity savings under a well-managed phase-down of HFCs. Our results reveal that the opportunity to simultaneously improve energy efficiency in stationary cooling technologies could bring additional climate benefits of about the same magnitude as that attributed to the HFCs phase-down. If technical energy efficiency improvements are fully implemented, the resulting electricity savings could exceed 20% of future global electricity consumption, while the corresponding figure for economic energy efficiency improvements would be about 15 %. The combined effect of HFC phase-down, energy efficiency improvement of the stationary cooling technologies, and future changes in the electricity generation fuel mix would prevent between 411 and 631 PgCO2 equivalent of GHG emissions between 2018 and 2100, thereby making a significant contribution towards keeping the global temperature rise below 2 C. Reduced electricity consumption also means lower air pollution emissions in the power sector, estimated at about 5 % 10% for sulfur dioxide (SO2), 8 % 16% for nitrogen oxides (NOx ), and 4 % 9% for fine particulate matter (PM2:5) emissions compared with a pre-Kigali baseline.

Purpose of the Review: Industry is one of the most difficult sectors to decarbonize. With the rapidly falling cost of solar PV, wind power, and battery storage, industry electrification coupled with renewable electricity supply has the potential to be a key pathway to achieve industry decarbonization. This paper summarizes the latest research on the possibility of electrification of the industry sector. Recent Findings: The transition to industry electrification would entail major changes in the energy system: large scale increases in renewable electricity or nuclear power supplies, the expansion of electricity transmission and distribution networks, completely different end-use technologies for process heating, and new infrastructure for distributing and dispensing hydrogen. Thus, aggressive and sustained supportive policies and much wider research, development, demonstration, and deployment activities are required to meet net zero carbon emissions goals in the industrial sector. Summary: Existing economically competitive electrified industrial processes (such as electric arc furnaces for secondary steelmaking from scrap steel), coupled with zero-carbon electricity sources can sharply reduce greenhouse gas emissions (GHG) compared to manufacturing processes that rely on fossil fuels. Fuel switching in industry from fossil fuel–based process heating to electrified heat can offer many product and productivity benefits, but operating costs in general are much higher than fossil fuel-based heating. Either much lower costs of electricity and energy storage are required and/or new, cost-competitive electric-technology applications are needed to enable further electrification of industry. Indirect electrification i.e., hydrogen production via water electrolysis is another complimentary technology reliant on electricity. Hydrogen can be used as an energy carrier, industrial feedstock for products and fuels, or for long-duration energy storage, and thus can also play a key role in industry decarbonization when the hydrogen is produced from zero-carbon electricity and/or with carbon capture and storage. As with direct electrification, cost is the key barrier for the deployment of hydrogen resources.

Climate change and increased electrification of space and water heating in buildings can significantly affect future electricity demand and hourly demand profiles, which has implications for electric grid greenhouse gas emissions and capacity requirements. We use EnergyPlus to quantify building energy demand under historical and under several climate change projections of 32 kinds of building prototypes in 16 different climate zones of California and imposed these impacts on a year 2050 electric grid configuration by simulation in the Holistic Grid Resource Integration and Deployment (HIGRID) model. We find that climate change only prompted modest increases in grid resource capacity and negligible difference in greenhouse gas emissions since the additional electric load generally occurred during times with available renewable generation. Heating electrification, however, prompted a 30-40% reduction in greenhouse gas emissions but required significant grid resource capacity increases, due to the higher magnitude of load increases and lack of readily available renewable generation during the times when electrified heating loads occurred. Overall, this study translates climate change and electrification impacts to system-wide endpoint impacts on future electric grid configurations and highlights the complexities associated with translating building-level impacts to electric system-wide impacts.

This paper presents the first detailed long-term stock turnover model to investigate scenarios to decarbonize the residential water heating sector in California, which is currently dominated by natural gas. We model a mix of water heating (WH) technologies including conventional and on-demand (tank-less) natural gas heating, electric resistance, existing electric heat pumps, advanced heat pumps with low global warming refrigerants and solar thermal water heaters. Technically feasible policy scenarios are developed by considering combinations of WH technologies with efficiency gains within each technology, lowering global warming potential of refrigerants and decreasing grid carbon intensity. We then evaluate energy demand, emissions and equipment replacement costs of the pathways. We develop multiple scenarios by which the annual greenhouse gas emissions from residential water heaters in California can be reduced by over 80% from 1990 levels resulting in an annual savings of over 10 Million Metric Tons by 2050. The overall cost of transition will depend on future cost reductions in heat pump and solar thermal water heating equipment, energy costs, and hot water consumption.

Technology learning rates can be dynamic quantities as a technology moves from early development to piloting and from low volume manufacturing to high volume manufacturing. This work describes a generalizable technology analysis approach for disaggregating observed technology cost reductions and presents results of this approach for one specific case study (micro-combined heat and power fuel cell systems in Japan). We build upon earlier reports that combine discussion of fuel cell experience curves and qualitative discussion of cost components by providing greater detail on the contributing mechanisms to observed cost reductions, which were not quantified in earlier reports. Greater standardization is added to the analysis approach, which can be applied to other technologies. This paper thus provides a key linkage that has been missing from earlier literature on energy-related technologies by integrating the output of earlier manufacturing cost studies with observed learning rates to quantitatively estimate the different components of cost reduction including economies of scale and cost reductions due to product performance and product design improvements. This work also provides updated fuel cell technology price versus volume trends from the California Self-Generation Incentive Program, including extensive data for solid-oxide fuel cells (SOFC) reported here for the first time. The Japanese micro-CHP market is found to have a learning rate of 18% from 2005 to 2015, while larger SOFC fuel cell systems (200 kW and above) in the California market are found to have a flat (near-zero) learning rate, and these are attributed to a combination of exogenous, market, and policy factors.

This paper presents the first detailed long-term stock turnover model to investigate scenarios to decarbonize the residential water heating sector in California, which is currently dominated by natural gas. We model a mix of water heating (WH) technologies including conventional and on-demand (tank-less) natural gas heating, electric resistance, existing electric heat pumps, advanced heat pumps with low global warming refrigerants and solar thermal water heaters. Technically feasible policy scenarios are developed by considering combinations of WH technologies with efficiency gains within each technology, lowering global warming potential of refrigerants and decreasing grid carbon intensity. We then evaluate energy demand, emissions and equipment replacement costs of the pathways. We develop multiple scenarios by which the annual greenhouse gas emissions from residential water heaters in California can be reduced by over 80% from 1990 levels resulting in an annual savings of over 10 Million Metric Tons by 2050. The overall cost of transition will depend on future cost reductions in heat pump and solar thermal water heating equipment, energy costs, and hot water consumption.

Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North American datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate.

Fuel cells are both a longstanding and emerging technology for stationary and transportation applications, and their future use will likely be critical for the deep decarbonization of global energy systems. As we look into future applications, a key challenge for policy-makers and technology market forecasters who seek to track and/or accelerate their market adoption is the ability to forecast market costs of the fuel cells as technology innovations are incorporated into market products. Specifically, there is a need to estimate technology learning rates, which are rates of cost reduction versus production volume. Unfortunately, no literature exists for forecasting future learning rates for fuel cells. In this paper, we look retrospectively to estimate learning rates for two fuel cell deployment programs: (1) the micro-combined heat and power (CHP) program in Japan, and (2) the Self-Generation Incentive Program (SGIP) in California. These two examples have a relatively broad set of historical market data and thus provide an informative and international comparison of distinct fuel cell technologies and government deployment programs. We develop a generalized procedure for disaggregating experience-curve cost-reductions in order to disaggregate the Japanese fuel cell micro-CHP market into its constituent components, and we derive and present a range of learning rates that may explain observed market trends. Finally, we explore the differences in the technology development ecosystem and market conditions that may have contributed to the observed differences in cost reduction and draw policy observations for the market adoption of future fuel cell technologies. The scientific and policy contributions of this paper are the first comparative experience curve analysis of past fuel cell technologies in two distinct markets, and the first quantitative comparison of a detailed cost model of fuel cell systems with actual market data. The resulting approach is applicable to analyzing other fuel cell markets and other energy-related technologies, and highlights the data needed for cost modeling and quantitative assessment of key cost reduction components.

© 2015 The Author(s) Jurisdictions throughout the world are contemplating greenhouse gas (GHG) mitigation strategies that will enable meeting long-term GHG targets. Many jurisdictions are now focusing on the 2020–2050 timeframe. We conduct an inter-model comparison of nine California statewide energy models with GHG mitigation scenarios to 2050 to better understand common insights across models, ranges of intermediate GHG targets (i.e., for 2030), necessary technology deployment rates, and future modeling needs for the state. The models are diverse in their representation of the California economy: across scenarios with deep reductions in GHGs, annual statewide GHG emissions are 8–46 % lower than 1990 levels by 2030 and 59–84 % lower by 2050 (not including the Wind-Water-Solar model); the largest cumulative reductions occur in scenarios that favor early mitigation; non-hydroelectric renewables account for 30–58 % of electricity generated for the state in 2030 and 30–89 % by 2050 (not including the Wind-Water-Solar model) ; the transportation sector is decarbonized using a mix of energy efficiency gains and alternative-fueled vehicles; and bioenergy is directed almost exclusively towards the transportation sector, accounting for a maximum of 40 % of transportation energy by 2050. Models suggest that without new policies, emissions from non-energy sectors and from high-global-warming-potential gases may alone exceed California’s 2050 GHG goal. Finally, future modeling efforts should focus on the: economic impacts and logistical feasibility of given scenarios, interactive effects between two or more climate policies, role of uncertainty in the state’s long-term energy planning, and identification of pathways that achieve the dual goals of criteria pollutant and GHG emission reduction.

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

A key challenge for policy-makers and technology market forecasters is to estimate future technology costs and in particular the rate of cost reduction versus production volume. A related, critical question is what role should state and federal governments have in advancing energy efficient and renewable energy technologies? This work provides retrospective experience curves and learning rates for several energy-related technologies, each of which have a known history of federal and state deployment programs. We derive learning rates for eight technologies including energy efficient lighting technologies, stationary fuel cell systems, and residential solar photovoltaics, and provide an overview and timeline of historical deployment programs such as state and federal standards and state and national incentive programs for each technology. Piecewise linear regimes are observed in a range of technology experience curves, and public investments or deployment programs are found to be strongly correlated to an increase in learning rate across multiple technologies. A downward bend in the experience curve is found in 5 out of the 8 energy-related technologies presented here (electronic ballasts, magnetic ballasts, compact fluorescent lighting, general service fluorescent lighting, and the installed cost of solar PV). In each of the five downward-bending experience curves, we believe that an increase in the learning rate canbe linked to deployment programs to some degree. This work sheds light on the endogenous versus exogenous contributions to technological innovation and highlights the impact of exogenous government sponsored deployment programs. This work can inform future policy investment direction and can shed light on market transformation and technology learning behavior.

The article focuses on comparing the accuracy of Invisalign in achieving predicted tooth movement of the maxillary central incisors and locating the center of rotation in labio-palatal direction, analyzing the impact of different wear protocols. Topics include assessing the discrepancy between predicted and achieved angular movements, exploring root movement control, and comparing wear protocols' efficacy in achieving predicted tooth movements and center of rotation.