Framework for improved confidence in modeled nitrous oxide estimates for biofuel regulatory standards

Biofuels vary greatly in their carbon intensity, depending on the specifics of how they are produced. Policy frameworks are needed to ensure that biofuels actually achieve intended reductions in greenhouse gas emissions. Current approaches do not account for important variables during cultivation that influence emissions. Estimating emissions based on biogeochemical models would allow accounting of farm-specific conditions, which in turn provides an incentive for producers to adopt low emissions practices. However, there are substantial uncertainties in the application of biogeochemical models. This paper proposes a policy framework that manages this uncertainty while retaining the ability of the models to account for (and hence incentivize) low emissions practices. The proposed framework is demonstrated on nitrous oxide (N₂O) emissions from the cultivation of winter barley. The framework aggregates uncertainties over time, which (1) avoids penalizing producers for uncertainty in weather, (2) allows for a high degree of confidence in the emissions reductions achieved, and (3) attenuates the uncertainty penalties borne by producers within a timescale of several years. Results indicate that with effective management, N₂O emissions from feedstock cultivation may be <?5% of the carbon intensity of gasoline, whereas the existing policy approach estimates emissions >?20% of the carbon intensity of gasoline. If these emissions reductions are monetized, the framework can provide up to $0.002 per liter credits (0.8 cents per gallon) to fuel producers, which could incentivize emissions mitigation practices by biofuel feedstock suppliers, such as avoiding fall N application on silty clay loam soils. The conservatism in the current approach fails to incentivize the adoption of biofuels, while the lack of specificity fails to incentivize site-level mitigation practices. Improved uncertainty accounting and consideration of farm-level practices will incentivize mitigation efforts at landscape to global scales.     

“I feel your pain”: A critical review of organizational research on empathy

Empathy, a multidimensional construct comprised of cognitive, affective, and behavioral dimensions, has been advanced as a critical predictor of prosocial behavior and effectiveness in the workplace. However, despite organizational interest in empathy, there is a lack of consensus on what empathy is, how empathy should be measured, and how empathy research can meaningfully contribute to our understanding of organizational behavior. This paper aims to provide a roadmap for researchers and practitioners interested in empathy in the workplace. We first provide an updated overview of the state of the broader multidisciplinary literature on empathy. On the basis of this literature, we outline the three dimensions of empathy, discuss the distinctions between state/trait and observer/judged empathy, and compare empathy with related constructs. This integrated multidimensional conceptualization provides the basis for our critical review and recommendations. We review the organizational research on empathy (1983–2018), identifying critical issues with how empathy has been conceptualized, measured, and designed, and offer practical recommendations for the advancement of organizational research on empathy. We conclude by highlighting two fundamental questions: (a) is empathy associated with important outcomes of interest to organizations and employees, and (b) can empathy be changed, and if so, how?     

Cross-combined composite sampling designs for identification of elevated regions

Analyzing soils for contaminants can be costly. Generally, discrete samples are gathered from within a study area, analyzed by a laboratory and the results are used in a site-specific statistical analysis. Because of the heterogeneities that exist in soil samples within study areas, a large amount of variability and skewness may be present in the sample population. This necessitates collecting a large number of samples to obtain reliable inference on the mean contaminant concentration and to understand the spatial patterns for future remediation. Composite, or Incremental, sampling is a commonly applied method for gathering multiple discrete samples and physically combining them, such that each combination of discrete samples requires a single laboratory analysis, which reduces cost and can improve the estimates of the mean concentration. While incremental sampling can reduce cost and improve mean estimates, current implementations do not readily facilitate the characterization of spatial patterns or the detection of elevated constituent regions within study areas. The methods we present in this work provide efficient estimation and inference for the mean contaminant concentration over the entire spatial area and enable the identification of high contaminant regions within the area of interest. We develop sample design methodologies that explicitly define the characteristics of these designs (such as sample grid layout) and quantify the number of incremental samples that must be obtained under a design criteria to control false positive and false negative (Type I and II) decision errors. We present the sample design theory and specifications as well as results on simulated and real data.     

The metabolic demands of swimming behavior influence the evolution of skeletal muscle fiber design in the brachyuran crab family Portunidae

We investigated the influence of intracellular diffusion on muscle fiber design in several swimming and non-swimming brachyuran crabs. Species with sustained swimming behavior had aerobic dark fibers subdivided into small metabolic functional units, creating short diffusion distances necessary to support the high rates of aerobic ATP turnover associated with endurance activity. This dark fiber design was observed in all swimming species including Ovalipes ocellatus, which has apparently evolved swimming behavior independently of other Portunidae. In addition, we observed fiber and subdivision size-dependent differences in organelle distribution. Mitochondria, which rely on oxygen to function, were uniformly distributed in small fibers/subdivisions, but were clustered at the fiber periphery in larger fibers. The inverse pattern was observed for nuclei, which are not oxygen dependent, but rely on the transport of slow diffusing macromolecules. Phylogenetically independent contrast analysis revealed that these relationships were largely independent of phylogeny. Our results demonstrate cellular responses to diffusion that were necessary for the evolution of swimming and that are likely to be broadly applicable.     

Accumulation of anticoagulant rodenticides in a non-target insectivore, the European hedgehog (Erinaceus europaeus)

Studies on exposure of non-targets to anticoagulant rodenticides have largely focussed on predatory birds and mammals; insectivores have rarely been studied. We investigated the exposure of 120 European hedgehogs (Erinaceus europaeus) from throughout Britain to first- and second-generation anticoagulant rodenticides (FGARs and SGARs) using high performance liquid chromatography coupled with fluorescence detection (HPLC) and liquid-chromatography mass spectrometry (LCMS). The proportion of hedgehogs with liver SGAR concentrations detected by HPLC was 3-13% per compound, 23% overall. LCMS identified much higher prevalence for difenacoum and bromadiolone, mainly because of greater ability to detect low-level contamination. The overall proportion of hedgehogs with LCMS-detected residues was 57.5% (SGARs alone) and 66.7% (FGARs and SGARs combined); 27 (22.5%) hedgehogs contained >1 rodenticide. Exposure of insectivores and predators to anticoagulant rodenticides appears to be similar. The greater sensitivity of LCMS suggests that hitherto exposure of non-targets is likely to have been under-estimated using HPLC techniques.     

Evaluating local air pollution control administration efectiveness

Data were collected on the Los Angeles County Air Pollution Control District (APCD) and on Los Angeles air pollution and its effects. The information collected was used to define the air pollution control system in terms of inputs to the agency, agency actions and accomplishments, and outputs from the agency. It was further analyzed to determine which parameters of the system could be quantitatively assessed and how. Quantitative measures were normalized to facilitate comparisons between different time periods (and to allow comparisons between cities, regions, states, and nations). Preparations are underway for using these data to assess the severity of the air pollution problem in Los Angeles, to determine the overall effectiveness of the APCD, and to evaluate its administrative operation.     

The Silver Valley Lead Study:The Relationship between Childhood Blood Lead Levels and Environmental Exposure

This paper is directed to those persons concerned with the relationship between blood lead levels and environmental exposures to lead. Information presented in this paper represents one of the largest collections of epidemiologica! data relating blood lead levels to environmental exposures. The observed annual average ambient air lead concentration ranged from approximately 0.5 ng Pb/m³ to 23 ng Pb/m³, while lead in soil ranged from 50-24,600 ppm. Blood lead levels of children (ages 1-9 years) are related to a host of environmental variables via regression techniques. Blood lead levels were found to be most influenced by five variables. These variables are: ambient air lead, soil lead, age of the child, dustiness of the home, and occupational status of the parents. It is concluded, based upon the results of this study, that any environmental control strategy should address both the air and the soil. Soil levels in excess of 1000 ppm lead as well as air lead levels greater than 2 jug Pb/m³, 30 day average, were found to be unacceptable.