Genetic Toolkit for Assessment and Prediction of Population-Level Impacts of Bridge Construction on Birds

Recent studies have highlighted alarming rates of declines in bird populations across the country. The State of California is home to over 650 resident and migrant avian species. Legislation for protecting these species has existed for over a century now, yet tools for identifying populations and understanding seasonal movement remain limited. Recently, genetic and genomic tools have provided a method for understanding population structure, allowing for more informed delineation of management units. The goal of this project was to create a genetic toolkit for identifying breeding populations and assigning individuals to those populations. Ultimately, such tools could be used to assess population-level impacts when there are conflicts with birds at infrastructure construction sites. As a test case, we sequenced entire genomes for 40 individual Anna’s hummingbirds (Calypte anna) from across the state. Based on this initial data, we found low levels of differentiation between sampled locations, suggesting that C. anna in California are not subdivided into different population units. However, there was a weak signal of geography suggesting there may be localized genetic differences in a small proportion of the genome. Follow-up work will focus on a broader sampling across the state of California to clarify any possible population subdivision or geographical patterns of differentiation.View the NCST Project Webpag

Energy Efficiency Analysis: Biomass-to-Wheel Efficiency Related with Biofuels Production, Fuel Distribution, and Powertrain Systems

BACKGROUND: Energy efficiency analysis for different biomass-utilization scenarios would help make more informed decisions for developing future biomass-based transportation systems. Diverse biofuels produced from biomass include cellulosic ethanol, butanol, fatty acid ethyl esters, methane, hydrogen, methanol, dimethyether, Fischer-Tropsch diesel, and bioelectricity; the respective powertrain systems include internal combustion engine (ICE) vehicles, hybrid electric vehicles based on gasoline or diesel ICEs, hydrogen fuel cell vehicles, sugar fuel cell vehicles (SFCV), and battery electric vehicles (BEV). METHODOLOGY/PRINCIPAL FINDINGS: We conducted a simple, straightforward, and transparent biomass-to-wheel (BTW) analysis including three separate conversion elements--biomass-to-fuel conversion, fuel transport and distribution, and respective powertrain systems. BTW efficiency is a ratio of the kinetic energy of an automobile's wheels to the chemical energy of delivered biomass just before entering biorefineries. Up to 13 scenarios were analyzed and compared to a base line case--corn ethanol/ICE. This analysis suggests that BEV, whose electricity is generated from stationary fuel cells, and SFCV, based on a hydrogen fuel cell vehicle with an on-board sugar-to-hydrogen bioreformer, would have the highest BTW efficiencies, nearly four times that of ethanol-ICE. SIGNIFICANCE: In the long term, a small fraction of the annual US biomass (e.g., 7.1%, or 700 million tons of biomass) would be sufficient to meet 100% of light-duty passenger vehicle fuel needs (i.e., 150 billion gallons of gasoline/ethanol per year), through up to four-fold enhanced BTW efficiencies by using SFCV or BEV. SFCV would have several advantages over BEV: much higher energy storage densities, faster refilling rates, better safety, and less environmental burdens

Genetic Toolkit for Assessment and Prediction of Population-Level Impacts of Bridge Construction on Birds

Recent studies have highlighted alarming rates of declines in bird populations across the country. The State of California is home to over 650 resident and migrant avian species. Legislation for protecting these species has existed for over a century now, yet tools for identifying populations and understanding seasonal movement remain limited. Recently, genetic and genomic tools have provided a method for understanding population structure, allowing for more informed delineation of management units. The goal of this project was to create a genetic toolkit for identifying breeding populations and assigning individuals to those populations. Ultimately, such tools could be used to assess population-level impacts when there are conflicts with birds at infrastructure construction sites. As a test case, we sequenced entire genomes for 40 individual Anna’s hummingbirds (Calypte anna) from across the state. Based on this initial data, we found low levels of differentiation between sampled locations, suggesting that C. anna in California are not subdivided into different population units. However, there was a weak signal of geography suggesting there may be localized genetic differences in a small proportion of the genome. Follow-up work will focus on a broader sampling across the state of California to clarify any possible population subdivision or geographical patterns of differentiation.View the NCST Project Webpag

Improved heavy-duty vehicle fuel efficiency in India, benefits, costs and environmental impacts

The main objectives of this analysis are to examine the benefits and costs of fuel-saving technologies for new heavy-duty vehicles (HDVs) in India over the next 10 years and, to explore how various scenarios for the deployment of vehicles with these technologies will impact petroleum consumption and carbon dioxide (CO2) emissions over the next three decades. The study team developed simulation models for three representative HDV types—a 40-tonne tractor-trailer, 25-tonne rigid truck, and 16-tonne transit bus—based on top-selling vehicle models in the Indian market. The baseline technology profiles for all three vehicles were developed using India-specific engine data and vehicle specification information from manufacturer literature and input from industry experts. For each of the three vehicles we developed a comprehensive set of seven efficiency technology packages drawing from five major areas: engine, transmission and driveline, tires, aerodynamics, and weight reduction. Our analysis finds that India has substantial opportunity to improve HDV fuel efficiency levels using cost-effective technologies. Results from our simulation modeling of three representative HDV types—a tractor-trailer, rigid truck, and transit bus—reveal that per-vehicle fuel consumption reductions between roughly 20% and 35% are possible with technologies that provide a return on the initial capital investment within 1 to 2 years. Though most of these technologies are currently unavailable in India, experiences in other more advanced markets such as the US and EU suggest that with sufficient incentives and robust regulatory design, significant progress can be made in developing and deploying efficiency technologies that can provide real-world fuel savings for new commercial vehicles in India over the next 10 years. Bringing HDVs in India up to world-class technology levels will yield substantial petroleum and GHG reductions. By 2030, the fuel and CO2 reductions of the scenarios range from 10% to 34%, and at the end of 2050, these reductions grow to 13% and 41%. If we constrain the analysis to select the most efficient technology package that provides the fleets with payback times of 3 years or less, there are annual fleet-wide savings of roughly 11 MTOE of diesel and 34 MMT of CO2 in 2030, and this grows to 31 MTOE and 97 MMT by 2050

Using Genetic Tools to Identify Populations Within Species Could Ease Infrastructure Mitigation

Recent research suggests that bird populations are declining at alarming rates across the United States. Over the last century, local, national, and international efforts to limit declines in bird populations have resulted in state and federal laws that now protect most of California’s 650 bird species. To comply with these protections, transportation infrastructure projects often face strict mitigation requirements, which can be expensive and cause delays. Understanding a project’s effects on specific bird populations can refine mitigation requirements and optimize infrastructure planning.The tools for identifying separate populations within species and understanding protected birds’ seasonal movement have been limited until recently. New genetic and genomic tools now provide a method for understanding population differentiation, which is vital to a wide array of conservation goals including estimating population declines, identifying potential for adaptation to stressors, measuring connectivity between populations, and estimating inbreeding. Because infrastructure projects can directly impact genetic diversity and connectivity, a toolkit to assess population structure and the distribution of genetic variation could aid in predicting and mitigating the impacts of such projects. As a test case, researchers at the University of California, Davis, sequenced entire genomes for 40 individual Anna’s hummingbirds (Calypte anna) from across California to identify breeding populations and develop a genetic toolkit to assign individuals to those populations. The presence of this species at bridge construction sites has resulted in construction delays in part because little information exists on the status of different populations within the species.This research brief summarizes findings and implications from the project.View the NCST Project Webpag

From Laboratory to Road. A 2016 update of official and real-world fuel concumption and CO2 values for passenger cars in Europe

Official average carbon dioxide (CO2) emission values of new passenger cars in the European Union declined from 170 grams per kilometer (g/km) in 2001 to 120 g/km in 2015. The rate of reduction in CO2 emission values increased from roughly 1% per year to almost 4% per year after CO2 standards were introduced in 2009. Today, car manufacturers are on track to meet the 2021 target of 95 g/km. This rapid decline in CO2 emission values seems to be a rousing success for CO2 standards, but does not consider the real-world performance of vehicles. Our From Laboratory to Road series focuses on the real-world performance of new European passenger cars and compares on-road and official CO2 emission values. The studies have documented a growing divergence between real-world and official figures, and this divergence has become increasingly concerning. This fourth update of the From Laboratory to Road series adds another year of data (2015), one new country (France), two new data sources (Allstar fuel card and Fiches- Auto.fr), and approximately 400,000 vehicles to the analysis. The key takeaway from the analysis, however, remains unchanged. The divergence between type-approval and real-world CO2 emission values of new European cars continues to grow. Data on approximately 1 million vehicles from 13 data sources and seven countries indicate that the divergence, or gap, between official and real-world CO2 emission values of new European passenger cars increased from approximately 9% in 2001 to 42% in 2015 (see Figure ES- 1). We consider these findings to be robust given the considerable regional coverage; the heterogeneity of the data collected from consumers, company fleets, and vehicle tests; and the unambiguous upward trend in all samples

Evolutionary Algorithm Optimization of Staggered Biological or Biomimetic Composites Using the Random Fuse Model

In Nature, biological materials such as nacre, bone, and dentin display an enhanced mechanical strength due to their structure characterized by hard inclusions embedded in a soft matrix. This structure has inspired the design of artificial materials with optimized properties. Thus, for given the mechanical properties of matrix and inclusions, it is fundamental to understand how the global observables, essentially strength, and ultimate strain are determined by the geometrical parameters of the inclusions. In this paper, we address this question by extending the two-dimensional random fuse model, which has been widely used to extract statistical properties of fracture processes, to the case of staggered stiff inclusions. We thus investigate numerically how emergent mechanical properties can be optimized by tuning geometrical dimensions and the arrangement of the inclusions. To do this, we adopt an optimization procedure based on an evolutionary algorithm to efficiently explore the parameter space and to determine the most favorable geometrical features of the inclusions for improved strength or ductility, or both. Various lattice sizes and volume fractions are considered. Depending on inclusion sizes and aspect ratios, composite strength or ultimate strain can be maximized, with the Pareto front for simultaneous optimization of the two being interpolated by a simple power law. Characteristic exponents for damage avalanche distributions are found to vary with respect to homogeneous structures, indicating increased fracture ductility simply due to optimized geometrical features. Our study indicates the possibility through structural optimization of creating staggered composites that allow significant advantages in terms of weight reduction and fuel consumption in automotive applications