• Energy Research

Long-term energy systems models have been used extensively in energy planning and climate policy analysis. However, specifically in energy systems optimization models, heterogeneity of consumer preferences for competing energy technologies (e.g., vehicles), has not been adequately represented, leading to behaviorally unrealistic modeling results. This can lead to policy analysis results that are viewed by stakeholders as clearly deficient. This paper shows how heterogeneous consumer behavioral effects can be introduced into these models in the form of perceived disutility costs, to more realistically capture consumer choice in making technology purchase decisions. We developed a novel methodology that incorporates the theory of a classic consumer choice model into a commonly used long-term energy systems modeling framework using a case study of light-duty vehicles. A diverse set of consumer segments (thirty-six) is created to represent observable, identifiable differences in factors such as annual driving distances and attitude towards risks of new technology. Non-monetary or “disutility” costs associated with these factors are introduced to capture the differences in preferences across consumer segments for various technologies. We also create clones within each consumer segment to capture randomly distributed unobservable differences in preferences. We provide and review results for a specific example that includes external factors such as recharging/refueling station availability, battery size of electric vehicles, recharging time and perceived technology risks. Although the example is for light-duty vehicles in the US using a specific modeling system, this approach can be implemented more broadly to model the adoption of consumer technologies in other sectors or regions in similar energy systems modeling frameworks.

The use of biofuels can increase land competition, leading to global land use change (LUC). LUC poses risks such as increased greenhouse gas emissions and food prices. The magnitude of the risk is uncertain, but could be significant. Given these uncertainties and risks, we suggest that policymakers pursue a mix of the following three strategies: (1) promote feedstocks that rely less on land; (2) reduce LUC risk for land-using feedstocks; and (3) stimulate investments that increase land productivity and environmental protection. To realize these three strategies, we recommend that policymakers distinguish among feedstocks based on LUC risk; explore certifying production that avoids land competition; and adopt policy mechanisms that encourage investments in LUC-prone areas. We favor including feedstock-specific LUC emissions estimates in policies despite relatively large scientific uncertainty. While misleadingly precise, point estimates can be selected from science-based ranges to directly link LUC policy to emissions and provide strong transparent signals to biofuel investors. LUC emissions estimates can be updated regularly (∼3–5 years) to reflect improvements in scientific understanding, and global changes in policy and economic environments. With or without LUC emissions point estimates, additional policies, some outside the biofuel sector, will be needed to pursue the three strategies above.

Brazil aims to increase palm oil production to meet the growing national and global demand for edible oil and biodiesel while preserving environmentally and culturally significant areas. As land use change (LUC) is the result of complex interactions between socio-economic and biophysical drivers operating at multiple temporal and spatial scales, the type and location of LUC depend on drivers such as neighboring land use, conversion elasticity, access to infrastructure, distance to markets, and land suitability. The purpose of this study is to develop scenarios to measure the impact of land conversion under three different enforcement scenarios (none, some, and strict enforcement). We found that converting 22.5 million hectares of land can produce approximately 29 billion gallons (110 billion liters) of biodiesel a year. Of that, 22–71% of the area can come from forest land, conservation units, wetland and indigenous areas, emitting 14–84 gCO _2 e MJ ^−1 . This direct land use emission alone can be higher than the carbon intensity of diesel that it intends to displace for lowering greenhouse gas emissions. This letter focuses narrowly on GHG emissions and does not address socio-economic–ecological prospects for these degraded lands for palm oil or for other purposes. Future studies should carefully evaluate these tradeoffs.

This paper reviews the regulatory history for nitrogen oxides (NOx) pollutant emissions from stationary sources, primarily in coal-fired power plants. Nitrogen dioxide (NO2) is one of the six criteria pollutants regulated by the 1970 Clean Air Act where National Ambient Air Quality Standards were established to protect public health and welfare. We use patent data to show that in the cases of Japan, Germany, and the United States, innovations in NOx control technologies did not occur until stringent government regulations were in place, thus "forcing" innovation. We also demonstrate that reductions in the capital and operation and maintenance (O&M) costs of new generations of high-efficiency NOx control technologies, selective catalytic reduction (SCR), are consistently associated with the increasing adoption of the control technology: the so-called learning-by-doing phenomena. The results show that as cumulative world coal-fired SCR capacity doubles, capital costs decline to approximately 86% and O&M costs to 58% of their original values. The observed changes in SCR technology reflect the impact of technological advance as well as other factors, such as market competition and economies of scale.

The Bakken formation has contributed to the recent rapid increase in U.S. oil production, reaching a peak production of >1.2 × 106 barrels per day in early 2015. In this study, we estimate the energy intensity and greenhouse gas (GHG) emissions from 7271 Bakken wells drilled from 2006 to 2013. We model energy use and emissions using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE) model, supplemented with an open-source drilling and fracturing model, GHGfrack. Overall well-to-refinery-gate (WTR) consumption of natural gas, diesel, and electricity represent 1.3%, 0.2%, and 0.005% of produced crude energy content, respectively. Fugitive emissions are modeled for a “typical” Bakken well using previously published results of atmospheric measurements. Flaring is a key driver of emissions: wells that flared in 2013 had a mean flaring rate that was ≈500 standard cubic feet per barrel or ≈14% of the energy content of the produced crude oil. Resulting production-weighted mean GHG emissions in 2013 wer...

Large emission reductions in buildings and transport are possible by integrating demand-side strategies to electrify energy use, improve technological efficiency, and reduce or shift patterns of activity. With enabling policies and infrastructures, final energy users can make significant contributions to climate goals, particularly through widespread deployment of heat pumps and electric vehicles.