Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

Embodied pollution in Spanish household consumption: a disaggregate analysis

[spa] En este artículo aplicamos un modelo input-output ampliado medioambientalmente para analizar un aspecto específico de la hipótesis de la curva de Kuznets ambiental. El propósito del estudio es analizar si las estructuras de consumo de los hogares con una mejor ‘posición económica’ pueden tener un efecto positivo para reducir las presiones medioambientales. Para ello combinamos información de diferentes bases de datos para analizar el impacto de la contaminación atmosférica del consumo de diferentes hogares españoles en el año 2000. Consideramos nueve gases, i.e. los seis gases de efecto invernadero (CO2, CH4, N2O, SF6, HFCs, y PFCs) y otros tres gases (SO2, NOx, y NH3). Clasificamos los hogares en quintiles de gasto per capita y quintiles de gasto equivalente. Los resultados obtenidos muestran que hay una relación positiva y elevada entre el nivel de gasto y las emisiones directas e indirectas generadas por el consumo de los hogares; sin embargo, las intensidades de emisión tienden a disminuir con el nivel de gasto para los diferentes gases, con la excepción de SF6, HFCs, y PFCs.

Iowa Wetland Management District: Environmental Assessment and Draft Comprehensive Conservation Plan

This Environmental Assessment documents the National Environmental Policy Act (NEPA) process for developing a Comprehensive Conservation Plan (CCP) for the Iowa Wetland Management District (WMD, district). In general, scoping reveals issues that drive alternative ways of managing the district. Implementation of each of those alternative management styles (including the No Action Alternative) may have different effects on the physical, biological, and socio-economic environment. Analysis of these effects reveals the “preferred” alternative, which constitutes the CCP. The CCP includes goals, objectives, and strategies for the district to guide overall management for the next 15 years. The Iowa WMD consists of scattered tracts of habitat (both wetland and upland grassland) known as Waterfowl Production Areas (WPAs). As of 2011, there are 75 WPAs in 18 counties in north-central Iowa totaling 24,712 acres in fee title primarily managed by the Iowa Department of Natural Resources (DNR). Even though district acquisition has only occurred in 18 counties to date, a larger 35-county boundary is approved. This boundary follows the historic range of the poorly drained Prairie Pothole Region (PPR) in Iowa, an area known for its waterfowl production. The district also includes 575 WPA acres and approximately 434 Farm Service Agency acres in conservation easements on private land. This plan was prepared with the intent that the strong partnership with the Iowa DNR will continue over the next 15 years.

Final Research and Analysis Report: Iowa Energy Poll, January 15, 2009

 The Iowa Power Fund and the Office of Energy Independence are charged with the responsibility of creating an economically viable and sound energy future for Iowa through energy independence. This vision can only be achieved if a majority, if not all Iowans, are united in this cause and actively participate in it

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

The structure of Mediterranean rocky reef ecosystems across environmental and human gradients, and conservation implications

Historical exploitation of the Mediterranean Sea and the absence of rigorous baselines makes it difficult to evaluate the current health of the marine ecosystems and the efficacy of conservation actions at the ecosystem level. Here we establish the first current baseline and gradient of ecosystem structure of nearshore rocky reefs at the Mediterranean scale. We conducted underwater surveys in 14 marine protected areas and 18 open access sites across the Mediterranean, and across a 31-fold range of fish biomass (from 3.8 to 118 g m22). Our data showed remarkable variation in the structure of rocky reef ecosystems. Multivariate analysis showed three alternative community states: (1) large fish biomass and reefs dominated by non-canopy algae, (2) lower fish biomass but abundant native algal canopies and suspension feeders, and (3) low fish biomass and extensive barrens, with areas covered by turf algae. Our results suggest that the healthiest shallow rocky reef ecosystems in the Mediterranean have both large fish and algal biomass. Protection level and primary production were the only variables significantly correlated to community biomass structure. Fish biomass was significantly larger in well-enforced no-take marine reserves, but there were no significant differences between multi-use marine protected areas (which allow some fishing) and open access areas at the regional scale. The gradients reported here represent a trajectory of degradation that can be used to assess the health of any similar habitat in the Mediterranean, and to evaluate the efficacy of marine protected areas.

A detailed urinary excretion time course study of captan and folpet biomarkers in workers for the estimation of dose, main route-of-entry and most appropriate sampling and analysis strategies

Captan and folpet are two fungicides largely used in agriculture, but biomonitoring data are mostly limited to measurements of captan metabolite concentrations in spot urine samples of workers, which complicate interpretation of results in terms of internal dose estimation, daily variations according to tasks performed, and most plausible routes of exposure. This study aimed at performing repeated biological measurements of exposure to captan and folpet in field workers (i) to better assess internal dose along with main routes-of-entry according to tasks and (ii) to establish most appropriate sampling and analysis strategies. The detailed urinary excretion time courses of specific and non-specific biomarkers of exposure to captan and folpet were established in tree farmers (n = 2) and grape growers (n = 3) over a typical workweek (seven consecutive days), including spraying and harvest activities. The impact of the expression of urinary measurements [excretion rate values adjusted or not for creatinine or cumulative amounts over given time periods (8, 12, and 24 h)] was evaluated. Absorbed doses and main routes-of-entry were then estimated from the 24-h cumulative urinary amounts through the use of a kinetic model. The time courses showed that exposure levels were higher during spraying than harvest activities. Model simulations also suggest a limited absorption in the studied workers and an exposure mostly through the dermal route. It further pointed out the advantage of expressing biomarker values in terms of body weight-adjusted amounts in repeated 24-h urine collections as compared to concentrations or excretion rates in spot samples, without the necessity for creatinine corrections.

Carbonic anhydrase activity in primary sensory neurons. II. Influence of environmental factors on the phenotypic expression of the enzyme in dissociated cultures of chicken dorsal root ganglion cells.

Neuronal subpopulations of dorsal root ganglion (DRG) cells in the chicken exhibit carbonic anhydrase (CA) activity. To determine whether CA activity is expressed by DRG cells maintained in in vitro cultures, dissociated DRG cells from 10-day-old chick embryos were cultured on a collagen substrate. The influence exerted by environmental factors on the enzyme expression was tested under various conditions of culture. Neuron-enriched cell cultures and mixed DRG-cell cultures (including numerous non-neuronal cells) were performed either in a defined medium or in a horse serum-supplemented medium. In all the tested conditions, subpopulations of cultured sensory neurons expressed CA activity in their cell bodies, while their neurites were rarely stained; in each case, the percentage of CA-positive neurons declined with the age of the cultures. The number and the persistence of neurons possessing CA activity as well as the intensity of the reaction were enhanced by addition of horse serum. In contrast, the expression of the neuronal CA activity was not affected by the presence of non-neuronal cells or by the rise of CO2 concentration. Thus, the appearance and disappearance of neuronal subpopulations expressing CA activity may be decisively influenced by factors contained in the horse serum. The loss of CA-positive neurons with time could result from a cell selection or from genetic repression. Analysis of the time curves does not support a preferential cell death of CA-positive neurons but suggests that the eventual conversion of CA-positive neurons into CA-negative neurons results from a loss of the enzyme activity. These results indicate that the phenotypic expression of cultured sensory neurons is dependent on defined environmental factors.

Violent adolescents and their educational environment: a multilevel analysis.

OBJECTIVE: This study examined the respective roles of personal and environmental factors in youth violence in a nationally representative sample of 7548 postmandatory school students and apprentices ages 16-20 years in Switzerland. METHODS: Youth violence was defined as having committed at least one of the following in the previous 12 months: attacking an adult, snatching something, carrying a weapon, or using a weapon in a fight. Different ecological levels were tested, resulting in a three-level model only in males (individual, classroom, and school) as the low prevalence of female violence did not allow for a multilevel analysis. Dependent variables were attributed to each level. For males, the classroom level (10%) and the school level (24%) accounted for more than one third in interindividual variance. RESULTS: Factors associated with violence perpetration in females were being a victim of physical violence and sensation seeking at the individual level. In males, practicing unsafe sex, sensation seeking, being a victim of physical violence, having a poor relationship with parents, being depressed, and living in a single-parent household at the individual level; violence and antisocial acts at the classroom level; and being in a vocational school at the school level showed a correlation with violence perpetration. CONCLUSION: Interventions at the classroom level as well as an explicit school policy on violence and other risk behaviors should be considered a priority when dealing with the problem of youth violence. Furthermore, prevention should take into account gender differences.

International Equity on Greenhouse Gas Emissions and World Levels: an integrated analysis through distributive welfare indices

Up until now, analyses of the international distribution of pollutant emissions have not paid sufficient attention to the implications that, in terms of social welfare, the combined evolution of the global world average entails. In this context, this paper proposes the use of environmental welfare indices, taken and adapted from the literature on social welfare and inequality, in order to make a comprehensive examination of the international equity factor and the mean factor in this field. The proposed methodology is implemented empirically in order to explore the evolution in distributive-based environmental welfare on a global level for the three main pollutants with greenhouse gas effects: CO2, CH4 and NO, both globally and for selected years during the period of 1990- 2005. The main results found are as follows: firstly, typically, the environmental welfare associated with the overall greenhouse gases decreased significantly over the period, due primarily to the role of CO2; secondly, in contrast, the global welfare associated with CH4 and NO improved; and thirdly, typically, the evolutions can be attributed to a greater extent to the mean component than to the distributive component, although there are exceptions. These results would seem to be relevant in policy terms. JEL codes: D39; Q43; Q56. Keywords: environmental welfare: greenhouse gases; environmental equity.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

Comparative genome analysis of Pseudomonas knackmussii B13, the first bacterium known to degrade chloroaromatic compounds.

Pseudomonas knackmussii B13 was the first strain to be isolated in 1974 that could degrade chlorinated aromatic hydrocarbons. This discovery was the prologue for subsequent characterization of numerous bacterial metabolic pathways, for genetic and biochemical studies, and which spurred ideas for pollutant bioremediation. In this study, we determined the complete genome sequence of B13 using next generation sequencing technologies and optical mapping. Genome annotation indicated that B13 has a variety of metabolic pathways for degrading monoaromatic hydrocarbons including chlorobenzoate, aminophenol, anthranilate and hydroxyquinol, but not polyaromatic compounds. Comparative genome analysis revealed that B13 is closest to Pseudomonas denitrificans and Pseudomonas aeruginosa. The B13 genome contains at least eight genomic islands [prophages and integrative conjugative elements (ICEs)], which were absent in closely related pseudomonads. We confirm that two ICEs are identical copies of the 103 kb self-transmissible element ICEclc that carries the genes for chlorocatechol metabolism. Comparison of ICEclc showed that it is composed of a variable and a 'core' region, which is very conserved among proteobacterial genomes, suggesting a widely distributed family of so far uncharacterized ICE. Resequencing of two spontaneous B13 mutants revealed a number of single nucleotide substitutions, as well as excision of a large 220 kb region and a prophage that drastically change the host metabolic capacity and survivability.

Stability and adaptability of runner peanut genotypes based on nonlinear regression and AMMI analysis

The objective of this work was to estimate the stability and adaptability of pod and seed yield in runner peanut genotypes based on the nonlinear regression and AMMI analysis. Yield data from 11 trials, distributed in six environments and three harvests, carried out in the Northeast region of Brazil during the rainy season were used. Significant effects of genotypes (G), environments (E), and GE interactions were detected in the analysis, indicating different behaviors among genotypes in favorable and unfavorable environmental conditions. The genotypes BRS Pérola Branca and LViPE‑06 are more stable and adapted to the semiarid environment, whereas LGoPE‑06 is a promising material for pod production, despite being highly dependent on favorable environments.