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The climate change policy debate and ensuing discussions about industrial energy use and carbon emissions have highlighted the need to: (a) aggregate engineering information to a level relevant for economic policy analysis while maintaining sufficient detail so that results are meaningful for industry decision makers, (b) properly represent an industry’s capital vintage structure to better understand inertia associated with changes in aggregate industrial emissions profiles, and (c) identify policy instruments that leverage an industry’s potential for technological change such that carbon emissions can be noticeably reduced. This paper presents an econometric analysis of energy use and emissions profiles of the US Pulp and Paper Industry and uses the resulting set of equations to specify a dynamic model for the analysis of select climate change policies. Scenarios of cost of carbon, energy tax, and investment-led policies indicate that a combination of cost of carbon and investment-led policies can achieve the desired result of rapidly improving overall efficiency of the industry and promoting changes in fuel mix, which together can result in drastic reductions of carbon emissions. [Copyright &y& Elsevier]

Paper as a consumer product offers a undisputed benefits to human society, and it has been proven to be critical in driving most sensitive needs of mankind—principally in areas of security, education, sanitation, and communication—and thus has been produced and consumed worldwide. Its sustainable production and usage is one topic that has featured prominently in many discussion fronts and more often than not ends with recommendations for an alternative source of raw material, improvement in production procedures, and ecological concerns. Paper use is an ecological concern that has triggered many paper intervention actions around the world such as the Paper Task Force in USA, Sustainable Paper Alliance in China, and Paper and Beyond in Europe. In Nigeria, however, challenges associated with paper production, consumption, and economic prospects have not been adequately tackled. This is conspicuously evident in the huge volume of paper products imported annually into the country as a result of unsustainable local production. The cumulative impact of these issues reflect negatively on the Nigeria's paper industry and spread indirectly to the entire country's economy in terms of high capital freight spent on importation, volatile product price, and loss of employment opportunities. This work sought to review the challenges and opportunities associated with raw material sources, energy and water consumption, environmental pollution, paper consumption, and disposal of used paper products in Nigeria. The current review also advocated for wastepaper as a variant of raw material with a sustainable potential. [ABSTRACT FROM AUTHOR]

This paper uses data from the 2015 Residential Energy Consumption Survey to explore the extent to which renters' electricity use in the United States exceeds that of otherwise similar non-renters. Renting households are found to use approximately 9% more electricity than non-renters when controlling for location, socioeconomic, and many appliance-quantity controls. There are multiple factors that explain this extra electricity use, including inferior energy efficiency of appliances, behavioral factors, differences in bill payment responsibilities, and additional reliance by renters on electric space and water heaters. The paper finds that none of these factors are dominant. The phenomenon of renters' (conditionally) higher electricity use is thus best understood as one that emerges from multiple sources. [ABSTRACT FROM AUTHOR]

Policymakers at the federal and state level have begun to incorporate energy burden into equity goals and program evaluations, aiming to reduce energy burden below a high level of 6% for lower income households in the United States. Pairing an empirical household-level dataset spanning United States geographies together with modeled hourly energy demand curves, we show that rooftop solar reduces energy burden across a majority of adopters during our study period from a median of 3.3% to 2.6%. For low- and moderate-income adopters (at or below 80% and 120% of area median income, respectively), solar reduces median 2021 energy burden from 7.7% to 6.2%, and 4.1% to 3.3%, respectively. Importantly, solar reduces the rate of high or severe energy burden from 67% of all low-income households before adoption to 52% of households following adoption, and correspondingly from 21% to 13% for moderate-income households. Here, we show rooftop solar can support policy goals to reduce energy burden along with strategies such as weatherization and bill assistance. Modeled results show that rooftop solar reduced energy burden for most adopters in 2021 from a median of 3.3% to 2.6% with the average adopter seeing a 0.6 point ($691 annual) reduction in burden, accounting for costs, incentives, and savings. [ABSTRACT FROM AUTHOR]

This paper provides an example of several modeling and econometric advances used in the panel estimation of energy demand elasticities. The paper models the demand of total, industrial, and transport energy consumption and residential and commercial electricity consumption by analyzing US state-based panel data. The paper employs recently developed dynamic panel methods that address heterogeneity, nonstationarity, and cross-sectional dependence. In addition, the paper (i) considers possible nonlinear relationships between energy consumption and income without employing polynomial transformations of integrated income; and (ii) allows for and calculates possible asymmetric relationships between energy consumption and price. Finally, the paper models energy efficiency improvements by a nonlinear time trend. To our knowledge no other paper has combined all of the econometric and modeling advances that are applied here. Most of the results conformed to expectations; however, limited to no evidence of nonlinearities and asymmetries were uncovered. [ABSTRACT FROM AUTHOR]

Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating–cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non- White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities. [ABSTRACT FROM AUTHOR]

Efficient energy consumption is crucial for achieving sustainable energy goals in the era of climate change and grid modernization. Thus, it is vital to understand how energy is consumed at finer resolutions such as household in order to plan demand-response events or analyze impacts of weather, electricity prices, electric vehicles, solar, and occupancy schedules on energy consumption. However, availability and access to detailed energy-use data, which would enable detailed studies, has been rare. In this paper, we release a unique, large-scale, digital-twin of residential energy-use dataset for the residential sector across the contiguous United States covering millions of households. The data comprise of hourly energy use profiles for synthetic households, disaggregated into Thermostatically Controlled Loads (TCL) and appliance use. The underlying framework is constructed using a bottom-up approach. Diverse open-source surveys and first principles models are used for end-use modeling. Extensive validation of the synthetic dataset has been conducted through comparisons with reported energy-use data. We present a detailed, open, high resolution, residential energy-use dataset for the United States. [ABSTRACT FROM AUTHOR]

Energy efficiency improvement is often hindered by the energy efficiency gap. This paper examines the effect of short-run temperature fluctuations on the Energy Star air conditioner purchases in the United States from 2006 to 2019 using transaction-level data. Results show that the probability of purchasing an Energy Star air conditioner increases as the weekly temperature before the transaction deviates from 20–22 °C. A larger response is related to fewer cooling degree days in the previous years, higher electricity prices/income/educational levels/age/rate of owners, more common use of electricity, and stronger concern about climate change. 1 °C increase and decrease from 21 °C would lead to a reduction of total energy expenditure by 35.46 and 17.73 million dollars nationwide (0.13% and 0.06% of the annual total energy expenditure on air conditioning), respectively. Our findings have important policy implications for demand-end interventions to incorporate the potential impact of the ambient physical environment. The probability of purchasing an energy-efficient air conditioner increases as the temperature deviates from 20–22 °C in the United States, with the response varying by electricity price, background climate, and demographic characteristics. [ABSTRACT FROM AUTHOR]

Energy prosumer participates in the balance of the energy system actively through their production and consumption of energy and will become a major participant in the open energy market increasingly in the future. This paper used the bibliometric method to sort out 1251 literature data related to energy prosumer in the "Web of Science Core Collection" and used the software named CiteSpace to perform statistics and cooccurrence analysis. The research found the following: (a) journals in the field of prosumer have their emphasis on theory, application, policy, and modeling; (b) the United States and European institutions have published the articles most, and the academic influence of Chinese scholars needs to be further improved; (c) the focus of the prosumers' research in the past decade has turned the energy system designing to the market transaction research; (d) P2P, P2G, and prosumer community are three market models that have attracted attention for scholars; besides, self-consumption, market matching, district heating, aggregators, and household energy management systems are also the current research hotspots; (e) digital technologies such as big data, the Internet of Things, and blockchain have a significant impact on the prosumer participating in energy market transactions, which will change the existing energy supply chain model profoundly. In the context of the energy Internet, energy trading platforms, digital ecosystems, cross-border innovation, and other fields will become the hotspots in future research on prosumer. [ABSTRACT FROM AUTHOR]

Energy efficiency policies require the implementation of strategies to reduce energy use during the operation of integrated urban water systems. In Italy, the overall amount of electrical energy consumption for water systems is close to 2.3% of the total national consumption, thus efforts to minimize costs are crucial. This paper analyzes a case study of urban water systems in a specific area in the Piedmont Region, Italy; the case study includes the data collection methodology and the analysis of the energy consumption of seven large water providers. The discussion includes the quantification of the energy consumption reduction, achievable with the replacement of existing transformers with high-efficiency transformers, power factor correction, and the use of variable-frequency drives for the centrifugal pumps. [ABSTRACT FROM PUBLISHER]

Load participation is vital for the smart grid development. As an effective tool to improve reliability, stability, and financial efficiency of the power grids, demand response (DR) has brought significant financial and technical benefits to power systems. As one of the price-based DR programs with less control costs, the time-of-use (TOU) program has been applied as the default rate structure by many utility companies. To avoid financial risks and make the most profit from the market, utility companies treat TOU as an effective strategy to change customers’ electricity consumption patterns. As reported in many literature, existing TOU programs are not as effective as expected in many developed countries due to the complexity of human behaviors and disparities of residential customers. To examine whether to obtain different outcomes of TOU on the residential customers in developing countries, actual utility usage data from residential consumers in Shanghai, China, are analyzed in this paper. The result shows current TOU in Shanghai, China, has similar trends as TOU in developed countries. With high penetration level of renewable energy, an effective TOU program is urgently needed in the utility industry. In recent years, a creative TOU pricing structure has been introduced at the Electrical Reliability Council of Texas deregulated market, and it shows that the introduced “zero pricing” strategy has a significant impact on customers’ consumption patterns. The purpose of this research is to examine the key reasons that underlie ineffectiveness/effectiveness of TOU programs at residential level. [ABSTRACT FROM PUBLISHER]

In this paper, a management strategy is developed to realize the real-time optimal torque distribution between the internal combustion (IC) engine and the electric motor of parallel hybrid electric vehicles (HEVs). Without depending on future information, a set of instantaneous cost functions is defined as the objective of a multiobjective problem, which includes vehicle energy consumption, selected emission species, and an evaluation criterion for the battery state of charge (SOC). The varying-domain method is then utilized to introduce a flexible priority among objectives and to transform the multiobjective problem into a nonlinear programming problem, the optimal solution of which is subsequently found by a genetic algorithm, i.e., GENOCOPIII. A comparison of the simulation results demonstrates the flexibility of the proposed varying-domain optimal management strategy (VOMS) under different driving conditions. Compared with the rule-based management strategy (RBMS) and the weighted sum management strategy (WSMS), the VOMS potentially improves the fuel economy, emission reduction, and stability of the SOC. [ABSTRACT FROM PUBLISHER]

This paper examines the actions and the factors driving those actions to reduce energy consumption and enhance energy efficiency taken by United States cities. While not much empirical evidence is available on why governments pursue practical sustainability actions, we attempt to shed more light on this important topic by empirically identifying factors that contribute to concrete actions toward sustainability policies. We adopt political market theory as a basic theoretical framework with policy-making applied to city energy consumption. Using the 2010 ICMA (local government sustainability policies and program) data, this study expands the focus of analyses to evaluate the effect of the form of government on energy consumption and energy efficiency by using multiple regression analysis. The findings show that at the city level, the mayorcouncil form of government are negatively associated with governments' efforts to reduce energy consumption. However, cities with at-large elections and municipal ownership are more likely to adopt sustainability actions. We also find that a large-scale economy has significant effects on the effort to reduce city energy consumption and improve energy efficiency. This shows that environmental policies are directly connected to locally relevant affairs, including housing, energy use, green transportation, and water. Thus, local level administrators could take an executive role to protect the environment, encourage the development of alternative energy, and reduce the use of fossil fuel and coal energy. These efforts can lead to important environmental ramifications and relevant actions by municipal governments. [ABSTRACT FROM AUTHOR]

• Decoupling of GDP from all energy sources under multiple principles are examined. • World economy achieved weak energy decoupling in most years during 2000–2011. • World economy coupled with coal use and tended to couple with cleaner energy use. • None of studied economies achieved long-term GDP-embodied energy decoupling. • Decoupling delusions occurred when only considering direct and total energy use. Decoupling indicators are widely used to understand links between economic growth and energy use. However, traditional decoupling analyses mostly focus on domestic energy consumption (i.e., the production-based principle) and neglect off-site energy use across global supply chains to satisfy an economy's final consumption (i.e., the consumption-based principle). Moreover, analyses for total primary energy conceal an economy's preference for different energy sources. Therefore, this paper evaluates decoupling states of GDP from all types of primary energy use under consumption-based principle, for world economy and eight typical economies during 2000–2011. Regarding total primary energy, world economy witnessed weak decoupling in most years, and most economies studied (e.g., USA, Japan and China) achieved decoupling initially but performed negative decoupling finally. For EU, USA, Japan, Russia and India, production-based decoupling performances were generally better than consumption-based ones. Decoupling phenomena detected under production-based principle even became coupling or negative decoupling under consumption-based principle in some cases. As for each energy source, world economy decoupled from oil use, but still coupled with coal use, and gradually showed a trend to couple with natural gas and renewables use. Different energy sources showed distinct decoupling degrees from GDP, affected by individual embodied energy requirement structure. This paper uncovers potential energy decoupling delusions to deepen the understanding of relationships between energy use and economic growth. [ABSTRACT FROM AUTHOR]

Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence's potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050. AI reduces building energy and emissions in design/construction, equipment, occupancy, and control/operation. By accelerating high-efficiency and net-zero buildings, AI could cut energy and emissions by 40-90% by 2050 combined with adequate policies. [ABSTRACT FROM AUTHOR]

In 2023, residential and commercial sectors together consumed approximately 27.6% of total United States (U.S.) energy, equivalent to about 20.6 quadrillion Btu. Factoring in the electrical system energy losses, the residential sector represented approximately 19.7% of total U.S. energy consumption during that time. There were approximately 144 million housing units in the United States in 2023, which is increasing yearly. In this study, information on energy usage in the United States residential sector has been analyzed and then represented as energy intensities to establish benchmark data and to compare energy consumption of varying sizes and locations. First, public sources were identified and data from these previously published sources were aggregated to determine the energy use of the residential sector within the US. Next, as part of this study, the energy data for seven houses/apartments from five different United States climate zones were collected firsthand. That data were analyzed, and the energy intensity of each home was calculated and then compared with the energy intensities of the other homes in the same states using Residential Energy Consumption Survey (RECS) data. The energy intensity for each facility was calculated based on the actual energy bills. Finally, the study evaluated the carbon footprint associated with residential energy consumption in all 50 states to reinforce the importance of sustainable development initiatives. [ABSTRACT FROM AUTHOR]

This article comments on a paper which studied the implications of pro-cyclical capital utilization rates for inference regarding cyclical movements in labor productivity and the degree of returns to scale in the U.S. This paper sets itself an ambitious task: it attempts to explain a fundamental stylized facts of modern macroeconomics using an empirical model that nests the three main explanations for this fact: technology shocks, increasing returns to scale, and unobserved input variation. This separation is not really that straightforward, since the first is an impulse and the other two are propagation mechanisms. As the paper notes, Robert Hall's early work suggested that markups and returns to scale are very large. These papers consistently find approximately constant returns and small markups. A number of papers also investigate the role of variable factor utilization in dynamic optimizing models, and generally conclude that variable utilization can explain a substantial fraction of the cyclicality of productivity. Even viewed from this background, the paper makes a number of useful contributions. Its substantive message is that using electricity consumption as a proxy for capital utilization leads to more sensible results in short-run time-series analysis, and controlling for capacity utilization changes the estimated properties of technology shocks.

This paper investigates the interaction between energy consumption and oil shocks in the U.S. from 1974 to 2018 using monthly data. Its contributions rely on the double disaggregation of energy consumption and oil shocks in a time-varying context. Oil shocks are disaggregated into oil supply, oil demand and aggregated demand shocks following the method of Kilian (2009). Energy consumption is disaggregated according to the production source in distinguishing between renewable and non-renewable energy consumption (hydropower, geothermal, wood, waste, coal, natural gas and petroleum). The impulse response function results show that renewable energy consumption responds the most to aggregate demand and oil supply shocks while for non-renewable energy consumption, it is oil demand shocks. The dynamic connectedness results show that oil supply and demand shocks spillover the most to hydropower consumption while aggregate demand shocks spillover the less. However, these relationships change over time and recommend the flexibility of energy policies. [ABSTRACT FROM AUTHOR]

In recent years, output responses to oil price shocks have not only been weaker, but have also reached their trough earlier. This paper builds a model that incorporates a realistic structure of U.S. petroleum consumption and explores three possible explanations for the changes. The possible factors considered are (i) deregulation in the transportation industry, (ii) improved energy efficiency, and (iii) a lower degree of persistence of oil price shocks. Under realistic parameter values, the three factors play an important role quantitatively, accounting for half of the reduction in the largest impact on output of an oil price shock over time. [ABSTRACT FROM AUTHOR]

Carbon Capture, Utilization, and Storage (CCUS) represents a vital technology for addressing pressing global challenges such as climate change and carbon emissions. This research aims to explore the relationship between the CCUS capability and carbon emissions in the United States considering thirteen predictors of CCUS and carbon emissions. Incorporating these predictors, we aim to offer policymakers insights to enhance CCUS capabilities and reduce carbon emissions. We utilize diverse econometric techniques: OLS, Lasso, Ridge, Elastic Net, Generalized Method of Moments, and Seemingly Unrelated Regression. Elastic Net outperforms the other models in explaining CCUS, while OLS is effective for carbon emissions. We observe positive impacts of the number of projects and foreign direct investment on the CCUS capacity, but limited influence from the CCUS technology level. However, the relationship between the CCUS capacity and carbon emissions remains limited. Our study highlights the importance of incentivizing projects to increase CCUS capabilities and recognizes the critical role of legal and regulatory frameworks in facilitating effective CCUS implementation in the US. Moreover, we emphasize that achieving decarbonization goals necessitates the development of affordable green alternatives. It is essential to view CCUS as a complementary, rather than a sole, solution for emission reduction as we work towards achieving net-zero emission targets. [ABSTRACT FROM AUTHOR]

As financial firms have increased their positions in the oil futures market during the past ten years, oil prices have increased dramatically as well. The coincidence of these two events has led some observers to argue that financial speculation caused the oil-price increases. Yet several arguments cast doubt on the validity of this claim. For example, although the quantity of oil implied by the number of open futures contracts is much larger than U.S. daily oil consumption, comparing these two statistics is misleading because not all paper oil is immediately deliverable. In addition, changes in financial firms' positions do not predict oil-price changes, but oil-price changes predict changes in positions. Other explanations for the oil-price increases include macroeconomic fundamentals such as increased demand from emerging Asia. Of these explanations, the most consistent with the facts relates the oil-price increases to a series of positive demand shocks emanating from emerging Asia. [ABSTRACT FROM AUTHOR]

This paper presents a brief overview of air-breathing propulsion research conducted at the National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) over the last 70 years. It includes a historical perspective of the center and its various stages of propulsion research in response to the country's different periods of crises and growth opportunities. The GRC's research and technology development covered a broad spectrum, from a short-term focus on improving the energy efficiency of aircraft engines to advancing the frontier technologies of high-speed aviation in the supersonic and hypersonic speed regimes. This paper highlights major research programs, showing their impact on industry and aircraft propulsion, and briefly discusses current research programs and future aeropropulsion technology trends in related areas. [ABSTRACT FROM AUTHOR]

The United States consumes more petroleum-based liquid fuel per capita than any other OECD high-income country―30 percent more than the second-highest country (Canada) and 40 percent more than the third-highest (Luxembourg). The transportation sector accounts for 70 percent of U.S. oil consumption and 30 percent of U.S. greenhouse gas emissions. Taking the externalities associated with high U.S. gasoline consumption as largely given, I focus on understanding the policy tools that seek to reduce this consumption. I consider four main channels through which reductions in U.S. oil consumption might take place: 1) increased fuel economy of existing vehicles, 2) increased use of non-petroleum-based, low-carbon fuels, 3) alternatives to the internal combustion engine, and 4) reduced vehicle miles traveled. I then discuss how these policies for reducing petroleum consumption compare with the standard economics prescription for using a Pigouvian tax to deal with externalities. Taking into account that energy taxes are a political hot button in the United States, and also considering some evidence that consumers may not 'correctly' value fuel economy, I offer some thoughts about the margins on which policy aimed at reducing petroleum consumption might usefully proceed. [ABSTRACT FROM AUTHOR]

This paper investigates the fuel consumption minimization problem of a blended-mode plug-in hybrid electric vehicle (PHEV). A simplified mathematical model of the PHEV was constructed to obtain optimal solutions for depleting the battery to a given final state of charge (SOC) under constant vehicle speed. An optimal power strategy was constructed from theoretical analysis and simulation for constant speed cases and then applied to typical drive-cycle simulations for a middle-size plug-in sport utility vehicle in the Urban Dynamometer Driving Schedule, the U.S. Environmental Protection Agency US06 (Supplemental Federal Test Procedure), and the CR-City drive cycles. Simulation results indicate that the proposed control strategy is more efficient than other strategies of interest. Only the electric system loss characteristics, vehicle power demand, total battery energy, and trip distance are needed to implement the proposed control strategy in a PHEV. It does not rely on the detailed trip information other than the total trip distance. Therefore, it is possible to implement the control strategy in real time if the total trip distance is known before the trip. [ABSTRACT FROM PUBLISHER]

global consumption of energy continues to increase at an exponential rate, the need to find technologies that can help reduce this rate of consumption, particularly in passenger vehicles, is imperative. This paper provides a progress report on the BSST-led US Department of Energy-sponsored automotive thermoelectric waste heat recovery project, which has transitioned from phase 3 and is completing phase 4. Thermoelectric generator (TEG) development will be discussed, including modeling and thermal cycling of subassemblies. The design includes the division of the TEG into different temperature zones, where the subassembly materials and aspect ratios are optimized to match the temperature gradients for the particular zone. Test results for a phase 3 quarter-scale device of the phase 4 high-temperature TEG will be discussed, where power outputs of up to 125 W were achieved on a 600°C hot-air test bench. The design of the TEG, which uses high-power-density segmented thermoelectric elements, has evolved from a planar design in phase 3 to a cylindrical design in phase 4. The culmination of phase 4 includes testing of the generator on a dynamometer at the National Renewable Energy Laboratory with a high-performance production engine. [ABSTRACT FROM AUTHOR]

Buildings are the dominant driver of daily and seasonal electric load cycles, and account for 40 percent of U.S. final energy use. They account for roughly 10 percent of direct U.S. CO2 emissions and roughly 40 percent once indirect emissions from electricity generation are included. This paper explores possible evolution of this sector over the coming century, its potential role climate action and response to climate policies, and the potential benefits advances in building technologies for addressing climate change. The paper presents a set of scenarios based on a detailed, service-based model of the buildings sector that is embedded within a long-term, global, integrated assessment model, MiniCAM. Eight scenarios are created in total, combining sets of assumptions regarding U.S. building service demand growth, two assumptions regarding the improvements in building energy technologies, two assumptions regarding long-term U.S. climate action --- a no-climate-action assumption and an assumption of market-based policies to reduce U.S. emissions consistent with a 450 ppmv global target. Through these eight scenarios, the paper comments on the implications of continued growth in building service demands, the ability of efficiency measures to reduce emissions, the strong link between decarbonization of electricity generation and building sector emissions. [ABSTRACT FROM AUTHOR]

This paper describes an inexpensive technology called AWARE@home that was designed for households to receive information regarding their utility consumption patterns through at-home wireless networks. Utility information devices have been proposed or developed in the past but to the authors’ knowledge this is the first to be: 1) designed specifically for homeowners to facilitate choices regarding consumption 2) built on existing home wireless “WiFi” networks and 3) developed with retrofit sensors that do not require meter replacement. Given that AWARE@home is designed to empower consumers to save money and conserve resources, the technology was selected as a winner of the inaugural EPA P3 competition in 2005. The system is designed for minimal effort by consumers: first, a service professional installs the AWARE@home retrofit device onto the existing meters in a process that takes approximately 30 minutes. Then the consumer receives a startup kit that includes a CD and, if needed, a USB wireless antenna for the computer. After loading software from the CD onto the computer, the homeowner is asked basic questions about utility rates, billing cycles and how much he or she wants to spend on utilities each month. At any point in the month that the desired expenditure on utilities set by the consumer is likely to be exceeded, AWARE@home will send an e-mail message or pop-up window message providing a warning about this predicted over-spending on utilities. This paper describes the prototype AWARE@home system that was produced for the EPA P3 competition and later installed in the home of an author for further testing. The AWARE@home prototype meets a number of design specifications related to simplicity, reliability, and cost. It includes both hardware and software components for “Wi-Fi” monitoring and alerting of home water, gas, and electricity consumption. The prototype for electricity monitoring has been operating continuously for over eight months at a home in Ann Arbor, Michigan, it has consistently and securely relayed usage rates to the local utility, and it has reliably predicted, notified, and helped the consumers to avoid excess expenditures on electricity. Preliminary research conducted during this project has shown that a majority of homeowners responding to a marketing survey would be interested in owning AWARE@home to reduce monthly expenditures and/or environmental emissions. [ABSTRACT FROM AUTHOR]

In this paper, a novel multihop virtual multiple-input-multiple-output (MIMO) communication protocol is proposed by the cross-layer design to jointly improve the energy efficiency, reliability, and end-to-end (ETE) QoS provisioning in wireless sensor network (WSN). In the protocol, the traditional low-energy adaptive clustering hierarchy protocol is extended by incorporating the cooperative MIMO communication, multihop routing, and hop-by-hop recovery schemes. Based on the protocol, the overall energy consumption per packet transmission is modeled and the optimal set of transmission parameters is found. Then, the issues of ETE QoS provisioning of the protocol are considered. The ETE latency and throughput of the protocol are modeled in terms of the bit-error-rate (BER) performance of each link. Then, a nonlinear constrained programming model is developed to find the optimal BER performance of each link to meet the ETE QoS requirements with a minimum energy consumption. The particle swarm optimization (PSO) algorithm is employed to solve the problem. Simulation results show the effectiveness of the proposed protocol in energy saving and QoS provisioning. [ABSTRACT FROM AUTHOR]

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

This paper examines how demographic changes can help explain changes/differences in personal transport using both International Energy Agency country panel regressions and decompositions of U.S. household data. An environmental Kuznets curve for per capita road energy use was rejected; instead, the relationship between income and road energy was found to be monotonic. The ideas that more densely populated countries have less personal transport demands, the young drive more, and smaller households mean higher per capita driving were confirmed. The household decompositions indicated that changes in demand were more important than compositional changes; yet, during some periods the compositional change component was considerable. [ABSTRACT FROM AUTHOR]

Over the last 20 years, the offshore exploratory success rate has more than doubled for a group of large producers which includes Exxon, Shell, Mobil, and Texaco, according to the U.S. Energy Information Administration (EIA). It is tempting to conclude that this increase can be attributed to the many advances in seismic and drilling technologies that have occurred over the same period. However, such a conclusion may be premature given that much of the increase in the success rate occurred in the late 1970s and early 1980s, well before the major advancements in seismic technology. The conclusion may also be premature in that it ignores the relationship between price and the success rate. Increases in the price may positively (negatively) affect the success rate. Given this, and the decline in price over the past decade, one would expect the success rate to have declined (increased) in the absence of technological change. This paper develops an econometric model that attempts to disentangle and quantify the effects of the major factors hypothesized to affect the offshore exploratory success rate. The analysis relies on company level data from the EIA's Financial Reporting System over the period 1978 through 1995. [ABSTRACT FROM AUTHOR]

Power split configurations exhibit potential on decreasing fuel consumption. However, how to select the best power split configuration among all the possible configurations still need to be explored. In this paper, a one-dimensional searching ECMS (Equivalent Consumption Minimization Strategy) is developed to evaluate fuel consumption for input power split configuration. Additionally, a battery degradation model based on experimental data is applied to evaluate the battery degradation for input power split configuration. According to one-dimensional searching ECMS and battery degradation model, the impact of different input power split configurations on fuel consumption and battery degradation is investigated. Simulations show that configuration T1 has fuel consumption and battery degradation advantages for PHEV city bus application in China. These advantages are observed because the system efficiency operation points of configuration T1 are closer to the high efficiency area than the system efficiency operation points of other input power split configurations. Furthermore, according to the lever model and one-dimensional searching ECMS method, a power split configuration selection method is provided in this paper. The simulation results based on configuration selection method still indicate that configuration T1 appears to have the best fuel economy for PHEV city bus application. Moreover, configuration T5, with a lever length close to 0, exhibits the worst fuel consumption and battery degradation. [ABSTRACT FROM AUTHOR]

Using a multi-regional input-output (MRIO) framework, we estimate the direct and indirect carbon dioxide (CO2) content of consumption across regions of the United States. We improve on existing estimates by accounting for emissions attributable to domestically and internationally imported goods using data describing bilateral trade between U.S. states and with international countries and regions. This paper presents two major findings. First, attributing emissions to states on a consumption basis leads to very different state-level emissions responsibilities than when attributed on a production basis; for example, California's emissions are over 25 percent higher. Second, heterogeneity of emissions across trading partners significantly affects the indirect emissions intensity of consumption (kg of carbon per $ of consumption), so regional differences in intensity across the U.S. go well beyond direct energy consumption. These findings have implications for evaluating the distributional impacts of national climate policies and for understanding differing incentives to implement state-level policies. [ABSTRACT FROM AUTHOR]

As the leader of the largest economy, President of the United States has substantive influence on addressing climate change problems. However, a presidential election is often dominated by issues other than energy problems. This paper focuses on the 2016 presidential election, and examines the energy plans proposed by the leading Democrat and Republican candidates. Our data from the Iowa caucus survey in January 2016 suggests that voters were more concerned about terrorism and economic issues than environmental issues. We then compare the Democratic and Republican candidate's view of America's energy future, and evaluate their proposed renewable energy targets. We find that the view on renewable energy is polarized between Democratic and Republican candidates, while candidates from both parties agree on the need for energy efficiency. Results from our ordinal least squares regression models suggests that Democratic candidates have moderate to ambitious goals for developing solar and other renewables. The Republican candidates favor fossil fuels and they choose not to provide any specific target for developing renewable energy. In addition, this trend of party polarization has grown more significant when compared with the past three presidential elections. Our observation suggests that energy policies need to be discussed more often regarding the diversification and decarbonization of the nation's energy system. [ABSTRACT FROM AUTHOR]

Residential weatherization programs have become a major component of U.S. energy policy. Through these programs, households receive heavily subsidized energy efficiency upgrades as well as informational and behavioral treatments designed to encourage conservation. While previous work demonstrates that weatherization programs provide sizable energy savings, all have measured the composite effect of efficiency upgrades and behavioral treatments. In this paper, we present the first estimates which disentangle the energy savings provided by each of the individual interventions. Our results reveal that the actual energy savings achieved by the efficiency upgrades are substantially smaller than exante, engineering predictions. Moreover, we present evidence that the energy savings provided by the simple behavioral interventions can exceed the savings resulting from the much more costly efficiency upgrades. [ABSTRACT FROM AUTHOR]