Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

Optimization of the high-pressure, near-critical liquid-based microsortation of recyclable post-consumer plastics

High-pressure, near-critical liquids were used as float-sink separation media for the microsortation of polyolefin mixtures and PET/PVC mixtures. Near-critical carbon dioxide was used for the refinement of the polyolefins, and sulfur hexafluoride was used to separate post-consumer PVC from PET. Preliminary experiments indicated that there was no overlap in the density ranges of post-consumer HDPE, LDPE and PP containers. There was no overlap in the PET and PVC densities, with the exception of a single PVC packaging material with a density in the PET range. These initial results indicated that a float-sink separation was a viable means of microsortation. Separations of 91% LDPE (1/8′ beads)/9% PP (1/8′ chopped strands) resin mixtures and mixed post-consumer polyolefin flakes were then conducted in a laboratory-scale, 1-I batch apparatus. This apparatus not only permitted the observation of the separation, but also enabled the separated fractions to be removed from the high-pressure environment. The results indicated that LDPE purity of greater than 98.9% was obtained in 3 min or less if (a) the fluid density was 0.018 g/cm³ greater than the PP density and only 0.002 g/cm³ less than the LDPE density, thereby providing the greatest buoyancy force for the removal of the PP, (b) the fluid was recirculated upward through the bed of mixed plastics, facilitating the upward movement of the PP, and (c) the loading was kept at levels below 40% by volume. HDPE purity of 99% was also attained with clean, dry, post-consumer mixed plastic flakes. The loadings for these separations were very low, however, due to the difficulty in agitating the mixed bed of plastics using fluid recirculation. An economic analysis of these microsortation processes indicated that the value of the sorted plastics relative to the mixed feed must increase by approx. $0.08/lb for the CO₂-based separation and approx. $0.27/lb for the SF₆-based separation to justify the implementation of these high-pressure processes.     

Adult-supervised practice driving for adolescent learners: The current state and directions for interventions

IntroductionThe aim of this study was to quantify and identify correlates to the amount of parent-supervised behind-the-wheel practice hours by novice teen drivers.MethodsA national survey of 945 parents of recently licensed teen drivers was conducted. Multivariate logistic regression was used to identify factors related to the number of practice hours completed.ResultsSixty-one percent of parents reported practicing 50 or more hours with their teen. Two-parent involvement was associated with more practice hours, though use of a professional driving instructor was not. Parents of teens licensed in states mandating 50 or more hours of practice driving were more likely to report at least 50 practice hours than those in states mandating 20–40 hours or in states without mandates.Impact on IndustryThe findings underscore the integral role of parents in the learning to drive process and provide further support for GDL requirements for practice hours.     

How humans shape wolf behavior in Banff and Kootenay National Parks, Canada

This paper describes the conceptualization and implementation of an agent-based model to investigate how varying levels of human presence could affect elements of wolf behavior, including highway crossings; use of areas in proximity to roads and trails; size of home ranges; activities, such as hunting, patrolling, resting, and feeding pups; and survival of individuals in Banff and Kootenay National Parks, Canada. The model consists of a wolf module as the primary component with five packs represented as cognitive agents, and grizzly bear, elk, and human modules that represent dynamic components of the environment. A set of environmental data layers was used to develop a friction model that serves as a base map representing the landscape over which wolves moved. A decision model was built to simulate the sequence of wolf activities. The model was implemented in a Java Programming Language using RePast, an agent-based modeling library. Six months of wolf activities were simulated from April 16 to October 15 (i.e., a season coherent with regard to known wolf behaviors), and calibrated with GPS data from wolf radiocollars (n = 15) deployed from 2002 to 2004. Results showed that the simulated trajectories of wolf movements were correlated with the observed trajectories (Spearman's rho 0.566, P < 0.001); other critical behaviors, such as time spent at the den and not traveling were also correlated. The simulations revealed that wolf movements and behaviors were noticeably affected by the intensity of human presence. The packs’ home ranges shrank and wolves crossed highways less frequently with increased human presence. In an extreme example, a wolf pack whose home range is traversed by a high-traffic-volume highway was extirpated due to inability to hunt successfully under a scenario wherein human presence levels were increased 10-fold. The modeling prototype developed in this study may serve as a tool to test hypotheses about human effects on wolves and on other mammals, and guide decision-makers in designing management strategies that minimize impacts on wolves and on other species functionally related to wolves in the ecosystem.     

When all life counts in conservation

Conservation science involves the collection and analysis of data. These scientific practices emerge from values that shape who and what is counted. Currently, conservation data are filtered through a value system that considers native life the only appropriate subject of conservation concern. We examined how trends in species richness, distribution, and threats change when all wildlife count by adding so-called non-native and feral populations to the International Union for Conservation of Nature Red List and local species richness assessments. We focused on vertebrate populations with founding members taken into and out of Australia by humans (i.e., migrants). We identified 87 immigrant and 47 emigrant vertebrate species. Formal conservation accounts underestimated global ranges by an average of 30% for immigrants and 7% for emigrants; immigrations surpassed extinctions in Australia by 52 species; migrants were disproportionately threatened (33% of immigrants and 29% of emigrants were threatened or decreasing in their native ranges); and incorporating migrant populations into risk assessments reduced global threat statuses for 15 of 18 species. Australian policies defined most immigrants as pests (76%), and conservation was the most commonly stated motivation for targeting these species in killing programs (37% of immigrants). Inclusive biodiversity data open space for dialogue on the ethical and empirical assumptions underlying conservation science.     

Dimethylphthalate hydrolysis by specific microbial esterase

TWO BACTERIAL STRAINS: Arthrobacter sp. and Sphingomonas paucimobilis were isolated from soil by enrichment cultures using dimethylphthalate (DMP) or monomethylphthalate (MMP) as sole carbon source, respectively. DMP was rapidly transformed by an Arthrobacter sp. culture with formation of MMP and phthalic acid (PA) which is further degraded. This strain was unable to hydrolyse MMP. A mechanism of degradation of DMP was proposed with two ways: DMP-->PA and DMP-->MMP. The S. paucimobilis strain hydrolyses only MMP and a coculture of the two strains allowed a complete degradation of DMP.