Using attenuated-total-reflection Fourier-transformed spectroscopy to reveal molecular structural differences among willow (Salix spp.) foliage cultivars in relation to their potential as fodders.

BACKGROUND: Willow trees represent a suitable species for the development of agroforestry systems, integrating bioenergy and animal feed production. However, there is a lack of information regarding the suitability of leaves and stems, considered a bioenergy by-product, as animal feed. The aim of this study was the employment of attenuated total reflectance Fourier transform infrared spectroscopy (550-4000 cm-1 ) to investigate differences in the nutrient molecular structure profile of leaves and stems of selected willow cultivars to understand their utility for ruminant nutrition. RESULTS: Univariate analysis of variance of leaves showed lower intensities of cellulosic compounds and higher of protein in comparison with stems, which suggests higher leaf dry matter and protein digestibility. Spectral analyses revealed differences in both plant parts between Salix cv. Terra Nova and Salix cv. Beagle, cv. Resolution, and cv. Olof. The higher α-helix to ß-sheet ratio, which is related to a higher protein digestibility, was in correlation with the lower content of condensed tannins. Principal component and agglomerative hierarchical cluster analyses showed significant discrimination among willow cultivars in the cellulosic, structural carbohydrate, and amide regions, whereas differences were less evident for total carbohydrate and lipid-related regions. CONCLUSION: The application of attenuated total reflectance Fourier transform infrared molecular spectroscopy is an effective tool to rapidly identify spectral features related to the nutritional composition of willow foliage and to discriminate between cultivars and parts of the plant. This information would be useful to optimize the use of willow fodders in agroforestry systems. © 2021 Society of Chemical Industry.

Electrolytic Seawater Mineralization and the Mass Balances That Demonstrate Carbon Dioxide Removal.

We present the mass balances associated with carbon dioxide (CO2) removal (CDR) using seawater as both the source of reactants and as the reaction medium via electrolysis following the "Equatic" (formerly known as "SeaChange") process. This process, extensively detailed in La Plante E.C.; ACS Sustain. Chem. Eng.2021, 9, ( (3), ), 1073-1089, involves the application of an electric overpotential that splits water to form H+ and OH- ions, producing acidity and alkalinity, i.e., in addition to gaseous coproducts, at the anode and cathode, respectively. The alkalinity that results, i.e., via the "continuous electrolytic pH pump" results in the instantaneous precipitation of calcium carbonate (CaCO3), hydrated magnesium carbonates (e.g., nesquehonite: MgCO3·3H2O, hydromagnesite: Mg5(CO3)4(OH)2·4H2O, etc.), and/or magnesium hydroxide (Mg(OH)2) depending on the CO32- ion-activity in solution. This results in the trapping and, hence, durable and permanent (at least ∼10 000-100 000 years) immobilization of CO2 that was originally dissolved in water, and that is additionally drawn down from the atmosphere within: (a) mineral carbonates, and/or (b) as solvated bicarbonate (HCO3-) and carbonate (CO32-) ions (i.e., due to the absorption of atmospheric CO2 into seawater having enhanced alkalinity). Taken together, these actions result in the net removal of ∼4.6 kg of CO2 per m3 of seawater catholyte processed. Geochemical simulations quantify the extents of net CO2 removal including the dependencies on the process configuration. It is furthermore indicated that the efficiency of realkalinization of the acidic anolyte using alkaline solids depends on their acid neutralization capacity and dissolution reactivity. We also assess changes in seawater chemistry resulting from Mg(OH)2 dissolution with emphasis on the change in seawater alkalinity and saturation state. Overall, this analysis provides direct quantifications of the ability of the Equatic process to serve as a means for technological CDR to mitigate the worst effects of accelerating climate change.

Regional economic conditions and crash fatality rates--a cross-county analysis.

INTRODUCTION: Most studies that evaluate the relationship between economic conditions and traffic fatalities focus on the time-series relationship between the two factors. This analysis considers the cross-sectional perspective by estimating the cross-county correlation between per capita income and fatalities per vehicle mile traveled (VMT) in Ohio. METHOD: The empirical model employed in this analysis allows for interaction effects between per capita income and highway usage, in the determination of fatality rates. RESULTS: The resultant least squares estimates indicate that a significant interaction effect exists between per capita income and the percentage of highway VMT, indicating a nonlinear correlation between per capita income and fatality rates. This correlation rises as the proportion of VMT on highways rises, such that there is an inverse relationship with fatality rates when the highway share of county VMT is low and a direct relationship with fatality rates when the highway share of county VMT is high. Additionally, population density, the presence of interstate highways in rural counties, the prior prevalence of severe alcohol abuse, and the proportion of teen drivers all proved to be significant correlates with county fatality rates. CONCLUSIONS: These observations suggest factors that state and federal policy makers should consider when allocating resources that impact (whether directly or indirectly) traffic fatalities.

The impact of state level behavioral regulations on traffic fatality rates.

INTRODUCTION: A state by year panel is analyzed to simultaneously explore the statistical correlation between state level traffic fatality rates and state level behavioral regulations regarding teen licensing, seat belt use, and driving under the influence (DUI) in a model that also controls for other correlates. METHOD: By including measures of all three of these policies, the estimated policy effects should not be overstated due to underspecification bias. The panel includes the 48 contiguous U.S. states for the time period from 1999 through 2003. State fatality rates are measured as fatalities per million miles traveled. Measures of state policies regarding traffic safety related behavior are based on information gathered by the Insurance Institute for Highway Safety. Estimates are calculated via a time fixed effects model that uses the double-log form to allow for interaction effects between the independent variables. RESULTS: Least squares estimates indicate that, on average, more restrictive graduated teen licensing and DUI policies significantly reduce traffic fatality rates, while stricter seat belt enforcement policies have a statistically insignificant negative impact on fatality rates.

The relationship between regional economic conditions and the severity of traffic crashes.

OBJECTIVES: To evaluate the relationship between regional economic conditions and the severity of injury suffered by victims of traffic crashes. This analysis augments the research on the relationship between economic conditions and traffic safety by focusing on injury severity per victim, which isolates the protective effect to individuals from other traffic safety effects such as crashes per mile and aggregate exposure to crashes. METHODS: A crash-specific data set from the State of Ohio is used together with county-level economic and demographic data to generate estimates that measure the impact of county-level per capita income and unemployment rate on the severity of injury suffered by each individual who is involved in a crash. The estimates are derived from an ordered probit model that controls for other factors that influence injury severity independently of economic conditions. RESULTS: The resulting estimates indicate that on average, individuals involved in crashes that occur in relatively prosperous counties suffer less severe injuries than those in less prosperous counties, holding other influential factors constant. Regional per capita income has a proportionally greater impact on injury severity than does regional unemployment rate. CONCLUSIONS: The estimates indicate that regional economic conditions have a statistically significant beneficial impact on traffic safety by improving the level of injury suffered by crash victims. Therefore, state and federal public policy makers should consider this factor when allocating traffic safety-related resources among geographical regions.