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Raw datasets (.mat and .fig files) and codes (.mlx and .m files) used in our manuscript of the same title. Figure numbers correspond with the figure numbers in the corresponding manuscript. Figure 4: Effects of kinetic parameters on Solar-to-chemical (STC) efficiencies and reaction selectivity Figure 5: Solar-to-chemical (STC) efficiencies for a model incorporating competing undesired redox reactions implemented for different redox shuttle pairs Figure 7: Solar-to-chemical efficiencies for an ensemble of light absorbers Figure 8: Maximum solar-to-chemical (STC) efficiencies and corresponding number of light absorbers as a function of asymmetry factors in limiting current density for redox shuttle reduction Figure 9: Solar-to-chemical efficiencies for an increasing number of light absorbers for different total absorptance values (99%, 75%, 50%). Figure 10: Qualitative comparisons between experimental measurements and model predictions for a photocatalytic suspension reactor The main piece of the code developed is provided as an interactive .mlx file; not all subfunction calls within the main code is included, and can be shared upon reasonable request via email from the lead (luisab@umich.edu) and the corresponding authors (rbchan@umich.edu) of this paper.

Correlations between chlorophyll a and total phosphorus in freshwater ecosystems were first documented in the 1960s and have been used since then to infer phosphorus limitation, build simple models, and develop management targets. Often these correlations are considered indicative of a cause-effect relationship. However, many scientists regard the use of these associations for modeling and inference to be misleading due to their potentially spurious nature. Using data from Saginaw Bay, Lake Huron, we examine the relationship among chlorophyll a, total phosphorus, and algal biomass measurements. We apply graphical models and recently developed "structure learning" principles that use conditional dependencies to help identify causal relationships among observational data. The spurious relationship suspected by some is not supported by our data, whereas a direct relationship between chlorophyll a and total phosphorus is always supported, and an additional indirect relationship with an algal biomass intermediary is plausible under some circumstances. Thus, we conclude that these correlations are useful for simple model building but encourage the use of modern statistical methods to avoid common model-assumption violations.

Mode of access: Internet.

Abstract Mesoscale in situ meteorological observations are essential for better understanding and forecasting the weather and climate and to aid in decision-making by a myriad of stakeholder communities. They include, for example, state environmental and emergency management agencies, the commercial sector, media, agriculture, and the general public. Over the last three decades, a number of mesoscale weather and climate observation networks have become operational. These networks are known as mesonets. Most are operated by universities and receive different levels of funding. It is important to communicate the current status and critical roles the mesonets play. Most mesonets collect standard meteorological data and in many cases ancillary near-surface data within both soil and water bodies. Observations are made by a relatively spatially dense array of stations, mostly at subhourly time scales. Data are relayed via various means of communication to mesonet offices, with derived products typically distributed in tabular, graph, and map formats in near–real time via the World Wide Web. Observed data and detailed metadata are also carefully archived. To ensure the highest-quality data, mesonets conduct regular testing and calibration of instruments and field technicians make site visits based on “maintenance tickets” and prescheduled frequencies. Most mesonets have developed close partnerships with a variety of local, state, and federal-level entities. The overall goal is to continue to maintain these networks for high-quality meteorological and climatological data collection, distribution, and decision-support tool development for the public good, education, and research.

Abstract A novel multi-scale domain overlapping coupling methodology designed to couple a computational fluid dynamics (CFD) code with a system thermal hydraulic (STH) code was developed and its performance was investigated. The methodology has been implemented in the coupling infrastructure code Janus, developed at the University of Michigan, providing methods for the on-the-fly data transfer through memory between the commercial CFD code STAR-CCM+ and the US NRC best-estimate thermal hydraulic system code TRACE. Coupling between these two software packages is motivated by the desire to extend the range of applicability of TRACE to scenarios in which local momentum and energy transfer are important, such as three-dimensional mixing of localized slugs of deborated or cold water in the downcomer and lower plenum of a reactor pressure vessel. The intra-fluid shear forces necessary to correctly capture these effects are neglected in the TRACE equations of motion, but are readily calculated from CFD solutions. CFD/STH coupling implementations therefore have applications in reactor transients such as boron dilution scenarios, Anticipated Transient Without SCRAM (ATWS) and Main Steam Line Break (MSLB). The proposed method is based on aliasing all spatial sources and sinks of momentum in the CFD domain as frictional losses in the system code domain. The internal velocity fields and, consequently, the inertial component of the pressure field are maintained consistent between the CFD and STH domains through a complementary velocity-matching interface. In this paper, coupled simulations are performed on Cartesian and cylindrical geometry with emphasis on consistency, convergence, and stability during transient scenarios. Results show that the presented domain overlapping coupling method is capable of adjusting pressure and velocity profiles of multi-dimensional system code solutions to match CFD solutions accurately. Important characteristics of transient simulations were found to include the background flow rate, specifically the stabilizing effect of viscous forces, as well as the time derivative of the flow rate. Under certain adverse conditions, the basic coupling method is found to produce unstable behavior. A stabilization method for adjusting CFD data is laid out and found to significantly improve the method’s performance under the most challenging conditions. Recommendations are laid out for further improving the coupling via advanced time stepping methods.

Cover title. ; Mode of access: Internet.

Variation in evolutionary rates among species is a defining characteristic of the tree of life and may be an important predictor of species’ capacities to adapt to rapid environmental change. It is broadly assumed that generation length is an important determinant of microevolutionary rates, and body size is often used as a proxy for generation length. However, body size has myriad biological correlates that could affect evolutionary rates independently from generation length. We leverage two large, independently collected datasets on recent morphological change in birds (52 migratory species breeding in North America and 77 South American resident species) to test how body size and generation length are related to rates of contemporary morphological change. Both datasets show that birds have declined in body size and increased in wing length over the past 40 years. We found, in both systems, a consistent pattern wherein smaller species declined proportionally faster in body size and increased proportionally faster in wing length. By contrast, generation length explained less variation in evolutionary rates than did body size. Although the mechanisms warrant further investigation, our study demonstrates that body size is an important predictor of contemporary variation in morphological rates of change. Given the correlations between body size and a breadth of morphological, physiological, and ecological traits predicted to mediate phenotypic responses to environmental change, the relationship between body size and rates of phenotypic change should be considered when testing hypotheses about variation in adaptive responses to climate change. For information on data collection see https://doi.org/10.5061/dryad.8pk0p2nhw and https://doi.org/10.5061/dryad.fqz612jsp.

"Published also in the Proceedings of the National Academy of Sciences, February, 1920, vol. 6, no. 2, p. 82-95." ; Cover title. ; Mode of access: Internet. ; 5

We present Vehicle Energy Dataset (VED), a novel large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures GPS trajectories of vehicles along with their time-series data of fuel, energy, speed, and auxiliary power usage. A diverse fleet consisting of 264 gasoline vehicles, 92 HEVs, and 27 PHEV/EVs drove in real-world from Nov, 2017 to Nov, 2018, where the data were collected through onboard OBD-II loggers. Driving scenarios range from highways to traffic-dense downtown area in various driving conditions and seasons. In total, VED accumulates approximately 374,000 miles. We discuss participant privacy protection and develop a method to de-identify personally identifiable information while preserving the quality of the data. After the de-identification, we conducted case studies on the dataset to investigate the impacts of factors known to affect fuel economy and identify energy-saving opportunities that hybrid-electric vehicles and eco-driving techniques can provide. The case studies are supplemented with a number of examples to demonstrate how VED can be utilized for vehicle energy and behavior studies. Potential research opportunities include data-driven vehicle energy consumption modeling, driver behavior modeling, machine and deep learning, calibration of traffic simulators, optimal route choice modeling, prediction of human driver behaviors, and decision making of self-driving cars. We believe that VED can be an instrumental asset to the development of future automotive technologies. The dataset can be accessed at https://github.com/gsoh/VED. 11 pages, 15 figures